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Monitoring HIV Care in the United States: Indicators and Data Systems (2012)

Chapter: 3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services

« Previous: 2 Indicators Related to Continuous HIV Care and Access to Supportive Services
Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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3


Sources of Data on HIV Care to
Assess Indicators of HIV Care and
Access to Supportive Services

In this chapter the committee describes data from public and private data systems to assess the indicators for HIV care and mental health, substance abuse, and supportive services identified in Chapter 2. The chapter identifies what the committee determined to be the best sources of data for assessing the indicators, discusses ways to maximize their usefulness, and recommends approaches for supplementing current data systems to gauge the impact of the National HIV/AIDS Strategy (NHAS) and the Patient Protection and Affordable Care Act (ACA) in improving HIV care (statement of task heading text and question 1). The chapter also describes other data collection and standardization efforts that could be utilized to monitor improvements in HIV care and how to regularly obtain data that capture the care experiences of people living with HIV/AIDS (PLWHA) without substantial new investments (statement of task questions 2 and 3). The chapter ends with the committee’s conclusions and recommendations.

IDENTIFICATION OF DATA SYSTEMS

To identify the best public and private sources of data to estimate the indicators related to continuous HIV care and access to services for PLWHA, the committee first compiled an initial list of 32 public and private data systems or data collection agencies, including those that are HIV specific and those that are not HIV specific but include information on PLWHA. The list included data collection efforts and systems highlighted in the project proposal as well as others identified by committee members as important or potential sources of information on PLWHA, including care

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

and services provided to them. Box 3-1 summarizes the data systems and collection activities identified by the committee for further consideration.

Requests for information were sent to individuals familiar with 29 of the data systems and agencies. Several other potential sources of data—accountable care organizations, the Enhanced Comprehensive HIV Prevention Planning (ECHPP) Project, and the 12 Cities Project—were still being implemented at the time of the inquiry.1 Information was obtained from 27 of the data systems or agencies contacted. The committee was unable to obtain information from Aetna and the HMO (Health Maintenance Organization) Research Network. The Substance Abuse and Mental Health Services Administration provided information on several data collection activities. In total, the committee reviewed information on 31 different data collection activities. The committee requested background information (e.g., the population for which data are collected; the method and frequency of data collection; whether the data are public, private, or proprietary) and details about the data elements captured by each of the data systems in the areas of HIV testing and linkage to care, clinical care, access to care, treatment and adherence, financial security, demographics, risk behavior assessment, and patient experience with care.

The data systems vary with respect to their design; the size, nature, and representativeness of population; the source and type of data; and the specific data elements included. The committee took account of these factors when considering which data systems, individually and in aggregate, would be most helpful for estimating the indicators presented in Chapter 2 and for assessing the impact of the NHAS and the ACA in improving HIV care in the United States.

The committee identified 12 data systems it considered to be most useful for tracking the impact of the NHAS and the ACA on HIV care in the United States:

  • National HIV Surveillance System
  • Medical Monitoring Project
  • Ryan White Services Report
  • Ryan White AIDS Drug Assistance Program Reports
  • Medicaid Statistical Information System
  • Chronic Condition Data Warehouse
  • North American AIDS Cohort Collaboration on Research and Design
  • CFAR Network of Integrated Clinical Systems
  • HIV Research Network
  • Clinical Case Registry: HIV

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1Complete descriptions of ECHPP and the 12 Cities Project are provided later in this chapter.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

BOX 3-1
Data Collection Activities Considered by the Committee

HIV Care–Specific Data Systems

Public

  • National HIV Surveillance System
  • Medical Monitoring Project
  • Ryan White HIV/AIDS Program (Ryan White Services Report; Ryan White AIDS Drug Assistance Program Reports; Ryan White Dental Services Report)
  • Clinical Case Registry: HIV
  • Housing Opportunities for Persons with AIDS
  • Minority AIDS Initiative
  • HIV Outpatient Study
  • Study to Understand the Natural History of HIV/AIDS in the Era of Effective Therapy
  • Enhanced Comprehensive HIV Prevention Planning Project
  • 12 Cities Project

Private

  • North American AIDS Cohort Collaboration on Research and Design
  • CFAR Network of Integrated Clinical Systems
  • HIV Research Network
  • AIDS United

Data Systems with Information that Includes People Living with HIV

Public

  • Medicaid Statistical Information System
  • Chronic Condition Data Warehouse
  • Resource and Patient Management System
  • Bureau of Prisons Electronic Medical Record
  • Bureau of Primary Health Care–Federally Qualified Health Center Uniform Data System
  • Substance Abuse and Mental Health Services Administration
  • Healthcare Cost and Utilization Project
  • National Ambulatory Medical Care Survey
  • National Hospital Ambulatory Medical Care Survey
  • National Vital Statistics System

Private

  • Private health insurers (Aetna, Kaiser Permanente, United Health [Ingenix Normative Health Information Database®], Wellpoint [HealthCore Integrated Research Database®])
  • MarketScan Research Databases
  • HMO Research Network
Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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  • Kaiser Permanente
  • National Vital Statistics System

Two additional data systems provide useful information for tracking the impact of the initiatives on HIV care for two small but important subpopulations of HIV-infected individuals (American Indians and Alaska Natives; federal prisoners) and a third provides information relevant to housing assistance and other supportive services for PLWHA:

  • Resource and Patient Management System
  • Bureau of Prisons Electronic Medical Record
  • Housing Opportunities for Persons with AIDS

Appendix Table 3-1 provides an overview of the data systems, including their strengths and limitations, potential enhancements to consider, and implications of the ACA for each. Although no single data system can fully track the progress of the NHAS and the ACA, the committee concluded that a combination of these 15 data systems can provide a collective platform for helping to evaluate these initiatives and for estimating the indicators identified to measure the quality of HIV care and access to supportive services. Appendix Tables 3-2a through 3-2e show which of the data elements associated with the indicators are available in each data system. Appendix Table 3-2f shows which data systems capture additional data elements that were identified by the committee to be of interest, but not required to estimate the indicators. Appendix Tables 3-3a through 3-3d summarize the indicators that can be estimated using information available from each of the data systems. Some of the data collection instruments are publicly available on the Internet (see Appendix Table 3-4); these provide more complete information on the data captured by the relevant data system.

SOURCES OF HIV CARE DATA

National HIV Surveillance System

The Centers for Disease Control and Prevention (CDC) maintains the National HIV Surveillance System (NHSS), which provides data about the HIV/AIDS epidemic for program planning and resource allocation. Started in 1981, the surveillance system is conducted in all 50 states and the District of Columbia, as well as American Samoa, Guam, Puerto Rico, the U.S. Virgin Islands, and the Northern Mariana Islands. In addition, the three freely associated states (the Federated States of Micronesia, the Republic of the Marshall Islands, and the Republic of Palau) report HIV surveillance

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

data to CDC. CDC funds and assists state and local health departments to collect the information, and the state and local HIV surveillance systems represent valuable additional sources of data pertinent to HIV care.2 The NHSS is a population-based census of all persons diagnosed and reported with HIV infection in the United States, including both those individuals receiving HIV care and those who are not in care.3

Since April 2008, all 50 states and the District of Columbia, as well as American Samoa, Guam, the Northern Mariana Islands, Palau, Puerto Rico, and the U.S. Virgin Islands, have been using the same confidential name-based reporting standards for newly diagnosed cases of HIV. Although the NHSS only includes data from those confidential name-based reporting systems that have been collecting HIV data for at least 4 years in the national aggregate numbers it publishes (CDC, 2010),4 all states and areas report HIV surveillance data to CDC, and the data for each reporting area are included in the annual HIV Surveillance Report. As such, the population in the surveillance system is one of the most nationally representative and provides the largest available sample of diagnosed PLWHA in the United States.

Another advantage of the NHSS is the use of standardized definitions of variables and reporting methods. In terms of data elements of interest to the committee,5 the system includes date of HIV/AIDS diagnosis; information on CD4+ cell count and plasma HIV RNA (viral load) closest to diagnosis; and optional fields for HIV and substance abuse treatment referral, pregnancy status, and antiretroviral therapy (ART) status at the time of reporting. Data gathered also can be used to monitor disparities with regard to race, ethnicity, sex, gender, age, geographic area, and country of birth.

In addition, most jurisdictions report all CD4 count and viral load lab

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2State, territorial, and local HIV surveillance systems may include data from code-based reports initiated prior to name-based reporting and anonymous results that have not been name ascertained and hence are not included in the NHSS. The proportion of these uncounted cases can be calculated precisely by the reporting areas that have made the transition to name-based reporting.

3The national surveillance system is meeting its completeness standard of ≥85 percent for all diagnosed cases being reported to the system (CDC response to IOM request for information, April 4, 2011).

4The 2009 national aggregate data published in 2012 includes data from the 46 states and 5 dependent areas that had implemented confidential name-based reporting by January 2007 (CDC, 2012, Commentary). Two additional states will be represented in the national aggregate data reported next year. The HIV Surveillance Report for 2012, to be issued in 2014, will be the first to include aggregate data from all 50 states (CDC, 2010).

5Although the data systems considered by the committee capture many useful data elements, only those data elements identified by the committee to be of specific interest for tracking the impact of the NHAS and ACA are discussed in the text. Appendix Table 3-4 lists the publicly available data collection instruments for the data systems discussed, which provide a comprehensive picture of the data elements captured by each.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

results,6 which permits the tracking of individuals’ health status over time. In those cases, additional information can be extrapolated or calculated from available data. For example, the time between diagnosis and initial (or second) CD4 and viral load test can serve as a surrogate for the length of time between diagnosis and entry into care, and the number of routine HIV care visits per year may be estimated from the number of HIV-related lab reports per year. One limitation of the NHSS, as noted in the NHAS (ONAP, 2010, p. 18), is the fact that although most jurisdictions report all lab results, such as CD4 and viral load results, not all do. Another limitation is the problem of incomplete or inaccurate reporting by clinicians treating PLWHA and by state and local health departments. Studies have raised questions about the accuracy and completeness of NHSS data. A study comparing self-reported dates of HIV diagnosis with those reported to the NHSS indicates that 56 percent of the date pairs agreed on the year of diagnosis, with another 17 percent differing by 1 year and 19 percent by 3 or more years (Hall et al., 2005). Thirty percent of self-reported dates were earlier than those reported in surveillance data (Hall et al., 2005). Another study comparing date of first diagnosis based on self-report, medical record, and surveillance system data showed 51 percent agreement between self-reported year of diagnosis and the surveillance system and 70 percent agreement between the years reported in medical records and in surveillance (McCoy et al., 2010). Another 21 percent of self-reported dates differed by 1 year, while 23 percent differed by 3 or more years (McCoy et al., 2010). On average the self-reported dates were earlier than those recorded in the surveillance data (McCoy et al., 2010).

According to one study of reporting completeness, 81 percent of HIV diagnoses are reported within 12 months of diagnosis (Hall et al., 2006). This figure corresponds with the observation of McCoy and colleagues that only 81 percent of the cases in their study could be matched to surveillance data (McCoy et al., 2010). Incomplete reporting may be explained by lack of timeliness in reporting, failure to comply with case reporting, or an assumption that previously diagnosed cases already had been reported (McCoy et al., 2010). Structures are in place to improve the accuracy and

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6As of June 15, 2010, 33 of 59 reporting areas (50 states, District of Columbia, 5 U.S. dependent areas, and 3 freely associated states) were reporting all CD4 and viral load test results (see Appendix Table 3-5), including 30 states, District of Columbia, Guam, and Puerto Rico (Personal communication, Amy Lansky, Centers for Disease Control and Prevention, October 6, 2011). One additional state (Kentucky) reported all CD4 results, but only detectable viral load results, and 7 additional states reported all viral load results, but not all CD4 results. More states are moving toward reporting all CD4 and viral load test results. Massachusetts, for example, mandated all CD4 and all HIV viral load results be electronically reported by clinical and commercial laboratories as of January 2012 (Massachusetts Department of Public Health, 2012).

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

timeliness of reporting. For example, increased use of electronic laboratory reporting is expected to increase the completeness and timeliness of HIV surveillance reporting (Overhage et al., 2008).

Despite current gaps in accuracy and reporting, the NHSS is one of the most representative HIV data systems that exists and offers a wealth of information. In terms of the data elements required to assess the core indicators for clinical HIV care, the NHSS, as previously noted, currently captures the individual’s date of diagnosis and the dates and results of the individual’s first and most recent viral load test and the CD4 test at, or closest to, the date that the individual was determined to be HIV-infected or to have AIDS (see Appendix Table 3-2a), as well as the first CD4+ cell count <200 cells/mm3. The ongoing CD4 and viral load test dates available for most reporting areas may be used as a surrogate for dates of first and ongoing visits for routine HIV care in those jurisdictions. These data permit estimation of the indicators for linkage to and continuity of care, regular CD4 and viral load testing, and individuals in care who achieve or maintain a CD4+ cell count of greater than 350 cells/mm3 (see Appendix Table 3-3a).

A revised version of the Adult HIV Confidential Case Report was approved by the Office of Management and Budget (OMB) in June 2011. The form includes a section that asks whether the individual “has ever taken any antiretrovirals (ARVs),” ARV medications taken, and dates ARVs were taken (date begun, date of last use). This information, which is collected “if required by Health Department,” is required for state and local health department that participate in CDC’s HIV Incidence Surveillance (HIS) and Variant, Atypical and Resistant HIV Surveillance (VARHS) activities and is optional for all other surveillance areas (CDC response to IOM request for information, October 20, 2011). When available, the ARV information may permit estimation of the core indicators pertaining to ART initiation and subsequent durable virologic suppression. However, there currently is no mechanism by which the NHSS can routinely capture ARV usage longitudinally. Longitudinal individual-level ART data in conjunction with longitudinal CD4 and viral load test dates and results would more reliably permit calculation of the relevant core indicators. Enhancement of NHSS data in this way would allow its use to evaluate all of the core HIV care indicators for the majority of the population diagnosed with HIV in the United States.7 Information is also captured on pregnancy status at the time the form is completed, which may be used to estimate the additional clinical

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7Since the NHSS captures date of death, it can provide the data necessary to calculate the core indicator pertaining to all cause mortality among PLWHA. However, as discussed in more detail later in this report, the National Vital Statistics System also collects and calculates annual data on HIV mortality.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

care indicator pertaining to proportion of pregnant women with HIV who are receiving ART.

NHSS data also permit calculation of the core HIV care indicators for subpopulations of PLWHA based on age, race and ethnicity,8 sex assigned at birth, current gender identity, geographic distribution, and country of birth. Although CDC does not currently capture information specifically about individuals’ sexual orientation, which relates to the NHAS target and associated indicator pertaining to the proportion of diagnosed gay or bisexual men with undetectable viral load, combining data on sex assigned at birth with data collected on sex of sexual partner(s) (sex with male) can serve as a close proxy.

As is common with disease surveillance in the United States, the HIV surveillance system also does not collect information about income level. Unlike the previous version of the Adult HIV Confidential Case Report form, which included an optional section asking about the individual’s primary source of reimbursement for medical treatment (Medicaid, private insurance or HMO, no coverage, other public funding, clinical trial or government program, unknown), the current form does not collect that information. Collection of such data, especially if the Ryan White HIV/AIDS Program were added to the list of reimbursement source checkboxes provided on the form, would permit the use of NHSS data to estimate the indicators for the subpopulations specifically identified in the NHAS and would help to facilitate the evaluation of data across data systems as discussed in Chapter 6.

Uniform reporting to CDC of ongoing CD4 and viral load test dates and results from all jurisdictions and collection of longitudinal information on ARV usage would permit the use of data from the NHSS to assess all of the core indicators for HIV care identified by the committee. Use of national surveillance system data would permit evaluation of the indicators for the vast majority of the population diagnosed with HIV in the United States, as well as for subpopulations based on race, ethnicity, sex, gender, age, and country of origin. In addition, capturing information on sexual orientation and maintaining current geographic areas of residence for HIV-infected individuals in the system would further enhance the ability of the NHSS to be used to evaluate the impact of the NHAS and health care reform on HIV care in the United States.

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8Like the other federal data systems, NHSS captures data on race and ethnicity as specified by OMB (1977, 1997a,b).

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Medical Monitoring Project

Initiated in 2005 in response to an Institute of Medicine (IOM, 2004) report, the Medical Monitoring Project (MMP) is a CDC-sponsored population-based surveillance system designed to collect comprehensive clinical and behavioral service need, utilization, and outcomes data on a nationally representative sample of adults (.18 years of age) living with HIV/AIDS who are receiving medical care from outpatient facilities in the United States and Puerto Rico (Blair et al., 2011). MMP is the first project since the HIV Cost and Services Utilization Study (Bozzette et al., 1998) almost 15 years ago that is designed to obtain comprehensive information about HIV care from a nationally representative population of PLWHA who are receiving care. MMP employs a probability proportional to size sampling design to obtain cross-sectional probability samples of its target population. A sample of about 400 individuals from each of 26 project areas (approximately 10,400 people) was selected each year for the 2007 and 2008 data collection cycles.9 Data are obtained from individual patient interviews and medical record review.

MMP captures most of the data elements needed to assess all of the indicators identified by the committee (see Appendix Tables 3-2a to 3-2e and 3-3a to 3-3c), including data on supportive services, which makes it an attractive source of data. In terms of demographic data, the interview component of MMP captures self-reported data on race, ethnicity, sex at birth, gender identity (male, female, transgender), and sexual orientation (homosexual, heterosexual, bisexual). In addition to the comprehensiveness of the data currently captured, the nature of the interview component of MMP allows flexibility to modify the questionnaire to capture different data elements that are subsequently determined to be useful. Starting with the 2011 cycle, for example, MMP is capturing data on stigma and discrimination, making it the only data system to do so among those examined by the committee.

An additional strength of MMP is its design to generate results that are nationally representative of the population of HIV-infected adults in care in the United States, which makes it a potentially valuable tool for tracking changes in access to and quality of HIV care in the country. Although MMP only includes HIV-infected individuals who are in care, the sample is not limited to those receiving care through a specific payer (Medicaid, Medicare, Veterans Health Administration [VHA], private or HMO) as is the case with a number of other data systems.

Despite its strengths, MMP also has several limitations. One significant

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9Details of the sampling method are described in the MMP 2009 protocol (CDC, 2009) and summarized in Blair et al. (2011) and on the MMP website (CDC, 2011b).

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

concern about MMP is its low participation rate. For the 2007 data collection cycle, 10,192 individuals were determined to be eligible for participation. The median participation rate was 40 percent, ranging from 3 to 76 percent depending on the project area. Interview data ultimately were reported for 3,643 of the 3,944 participants interviewed; medical record abstraction data were not reported (Blair et al., 2011). As a result of the low participation rate, the data for the 2007 collection cycle may not be nationally or locally representative of HIV-infected adults receiving care in the United States. Steps have been taken to improve participation rates beginning with the 2009 collection cycle, and CDC anticipates that future data will permit nationally representative results (Blair et al., 2011).10 It is not clear, however, that the efforts will completely resolve the issues of nonresponse bias. For example, studies have found that PLWHA who are harder to reach and/or engage for study participation are more likely to be homeless or unstably housed; to be struggling with mental health or drug use problems; to be socially isolated; and to have high rates of missed appointments. Specific efforts to engage such populations are needed to ensure their representation in the study.

A second concern about MMP is the potential for social desirability response bias in the responses to the interview questions. Since many of the the interviews are conducted “in person,” respondents may be reluctant to answer accurately if doing so means providing what they perceive to be less “socially appropriate” responses to sensitive questions (Blair et al., 2011). Providing participants with a means to enter their responses to sensitive questions directly into the computer or on the response form is one way to help counteract social desirability response bias. This approach would avoid the necessity of sharing their responses with the interviewer and could improve the accuracy of the information collected (Carr et al., 1983; Greist et al., 1973; Kobak et al., 1996; Lawrence et al., 2010; Lucas et al., 1977; Metzger et al., 2000; Petrie and Abell, 1994; Waruru et al., 2005; Willig, 2011), although a study of clients at an addiction treatment center found no significant differences in the reliability of information on drug, alcohol, or tobacco use collected through computerized interviews, face-to-face interviews, or self-report formats (Skinner and Allen, 1983).

A third concern is the potential inaccuracy of clinical data (lab values, vaccinations, ART prescription) collected through participant self-report (Blair et al., 2011). Although a problem for reports of findings based on clinical information obtained solely from interviews (e.g., Blair et al. 2011), medical record abstraction is another component of MMP (CDC, 2009, pp. 22-25), which permits comparison with and corroboration of

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10Some interview and medical record abstraction data from MMP’s 2009-2010 cycle have been reported (CDC, 2011d).

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

the self-reported clinical data. It is important that data from the medical record abstraction component of the protocol be available to permit such cross-checking and confirmation of self-reported information. The 2009 MMP protocol specifies that in project areas that have the surveillance authority to abstract medical records of selected patients without their consent, medical record abstraction should be completed for all sampled patients, including those who decline to participate in the interview or who cannot be located for interview (CDC, 2009, p. 25). In project areas with a more narrow definition of surveillance, where record abstraction cannot be completed without patient consent, minimal data can be collected on all sampled patients. The minimum data set contains the same fields as the NHSS case report form, and therefore these data can be collected in all project areas under HIV/AIDS surveillance authority.

Despite its current limitations, the research infrastructure, design, and implementation efforts that are in place make MMP a promising tool for monitoring care among HIV-infected adults receiving care in the United States. The committee supports the current efforts of CDC to improve individual participation and completion rates. Other strategies to increase participation might include providing additional incentives for study participants11 and participating clinics or reducing the time required to complete the full interview by selectively eliminating certain questions.12 In addition, implementation of the “minimum data set” records abstraction could help to provide some data for individuals who decline to participate.

Beginning with the 2012 data collection cycle, medical record abstraction will focus only on the 12 months preceding the interview; earlier clinical data will no longer be captured (Personal communication, Amy Lansky, Centers for Disease Control and Prevention, October 20, 2011). Although limiting medical record abstraction to the preceding 12 months likely will expedite collection of the data, certain data elements required to estimate some HIV care indicators may no longer be captured. For example, data on hepatitis B screening, vaccination, and immunity would not be captured if the relevant testing and immunization took place more than 12 months prior. Another option for reducing the number of questions in the standard interview without undermining the breadth of information provided might be to eliminate (some of) the self-reported clinical data if the same infor-

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11The 2009 MMP protocol specifies that individual participants will receive approximately $40 in cash or cash equivalent for participating in the interview (CDC, 2009, p. 21).

12Currently the MMP protocol offers two interview instruments: the Standard Questionnaire, which is the default and takes approximately 45 minutes to complete, and the Short Questionnaire, which is reserved for individuals who speak neither English nor Spanish or are too sick to respond to the Standard Questionnaire and takes approximately 20 minutes to complete.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

mation already is being harvested through medical record abstraction. In addition, as electronic health records (EHRs) become more prevalent, MMP may be able to increase the scope of medical abstraction while retrieving and processing the data in a timely way. Such enhancements would help to make MMP better able to fulfill its promise as an expanded surveillance system for monitoring HIV care in the United States.

The potential for MMP to provide comprehensive information for tracking improvements in access to and quality of HIV care and supportive services in the United States is great; however, the low completion rate to date and the potential for nonresponse bias raise concerns about the representativeness of the data, especially for the homeless or unstably housed population and those with mental health and/or substance use disorders. Implementation of strategies to improve participation rates, especially among hard-to-reach populations, and to expedite the processing and availability of the data obtained through medical record abstraction would significantly increase the value of the project.

Ryan White HIV/AIDS Program Data

According to the Health Resources and Services Administration (HRSA), approximately 529,000 people currently receive at least one medical, health, or related support service through the Ryan White HIV/AIDS Program each year (HHS, 2011a). The AIDS Drug Assistance Program (ADAP), under Part B of the Ryan White Program, reported 213,764 clients enrolled during FY 2009, including 33,672 new enrollees, and 190,936 clients served (NASTAD, 2011, Table 5). The Ryan White Program is the third-largest federally funded program serving PLWHA (after Medicare and Medicaid) and the largest that serves only PLWHA (KFF, 2009b). Twenty-nine percent ($5.4 billion) of federal spending for HIV care was allocated to the Ryan White Program in FY 2011 (Kates, 2011, p. 1). The majority of Ryan White Program clients are low income, with approximately 70 percent at or below the federal poverty level (FPL) (HRSA, 2010, p. 45, Table 6).

HRSA launched a new reporting scheme in 2009, replacing the Ryan White HIV/AIDS Program Annual Data Report with the Ryan White HIV/AIDS Program Service Report (RSR). The RSR captures individual client-level data annually for individuals who receive one or more Ryan White–funded services (client report), as well as grantee and service provider information (grantee report and service provider report). The RSR client report generates a unique client identifier for every Ryan White HIV/AIDS Program client based on the client’s name, birth date, and other characteristics; the identifier is then encrypted before being sent to HRSA, further protecting the client’s privacy. Use of unique client identifiers not

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

only permits tracking of individual clients across providers, generating more accurate client counts, but also permits the capture of individual-level demographic, clinical, and service utilization data, which can be used to assess quality of care received.13

The client report captures many of the data elements needed to assess the core clinical HIV care indicators identified by the committee (Appendix Tables 3-2a, 3-3a). The client report captures the year of birth (but not the full date); date of death; dates of ambulatory or outpatient HIV care visits; and the dates and results of all CD4 counts and viral load tests within the reporting period. In addition, the client report captures the year, but not the full date, of HIV diagnosis and whether the individual has been prescribed ART at any time within the reporting period, but not the date of ART initiation or subsequent prescriptions. Finally, the client report records the date of the client’s first ambulatory or outpatient care visit with the provider. However, the visit need not be for HIV care, nor is it necessarily the client’s first HIV care visit following diagnosis, which is required to assess the indicator pertaining to linkage to care.

The RSR client report also captures data relevant to the indicators related to mental health, substance abuse, and supportive services (see Appendix Tables 3-2b, 3-3b, 3-3d): screening for both mental health and substance use within the reporting period; number of mental health service visits; number of substance abuse service visits (inpatient and outpatient) in each quarter of the reporting period; housing status (stable permanent, temporary, unstable); and receipt of housing, food, and (medical) transportation services in each quarter of the reporting period (HRSA, 2011). The report does not provide information on referral for mental health or substance abuse services (e.g., whether the services were received within 60 days of referral); direct (e.g., dates) assessment of housing, food, or transportation need; or the proportion of clients who are food insecure or have an unmet need for transportation services, although such information might be inferred from the number of clients who are receiving food or transportation services.

The client report also collects data specific to a number of the additional clinical HIV care indicators (Appendix Tables 3-2c, 3-3c). These data include whether a client has been screened for tuberculosis (TB) during the 12-month reporting period or since being diagnosed with HIV; whether a client was screened for syphilis during the reporting period (excluding those under 18 years of age who are not sexually active); whether a client was screened for hepatitis B and C during the reporting period or since diagnosis

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13Although the Ryan White client-level data will be de-duplicated, the process will identify some false negatives and false positives, as is the case with any identifier based on personal characteristics.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

with HIV; and whether a client has completed the hepatitis B vaccination series. In addition, data are collected on the pregnancy status of HIV-infected female clients, the stage of pregnancy at which they entered prenatal care, and whether they were prescribed ART to prevent maternal-to-child transmission of HIV. Data relevant to the additional clinical HIV care indicators that are not captured by the client report include dates of chlamydia and gonorrhea screenings; dates of influenza and pneumococcal immunizations; and data pertaining to ART drug resistance testing and ART initiation in individuals with HIV nephropathy, hepatitis B or C, or TB.

Although the data elements collected by the client report are not identical to those enumerated for the indicators identified by the committee, they provide information that may serve as a proxy for estimating many of the indicators. In addition, the RSR client report captures demographic data that specify subpopulations within Ryan White HIV/AIDS Program clients including race and ethnicity; gender (male, female, transgender, unknown; and for transgender, male-to-female, female-to-male, unknown); geographic code (first three digits of client zip code); income as a percentage of the FPL; and sources of health insurance.

ADAPs independently report data to HRSA, and ADAP reporting also is undergoing revision. The October 1, 2012 through March 31, 2013, data collection period is the first to capture individual client-level data for the ADAP Data Report (ADR), replacing the ADAP Quarterly Report. Like the RSR, the ADR will employ unique client identifiers using the same algorithm and encryption process as those used for the RSR. The encrypted client identifiers are meant to carry across the reports. In the future, although the reports will remain separate, client-level data from the RSR and the ADR will be merged into a single system, and the two reports will be linked for those clients receiving ADAP and other Ryan White–funded services (Personal communication, Faye Malitz, Health Resources and Services Administration, October 25, 2011).

Appendix Tables 3-2a through 3-2e summarize the data elements pertaining to the committee’s indicators that are captured by the ADAP Quarterly Report and the ADR, including those that are new for the ADR. Appendix Tables 3-3a through 3-3d map the committee’s indicators to the various data elements that are or will be captured by the ADAP reports.14 The ADAP reports do not supplement the data already captured in the RSR in terms of those needed to evaluate the committee’s indicators. However, for the population of ADAP clients who do not receive other Ryan White

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14No data elements from the ADAP Quarterly Report that are pertinent to the committee’s indicators will be dropped in moving to the ADR, although new data elements of interest will be added. The committee refers to “the ADAP reports” jointly when it is unnecessary to distinguish between them.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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services, the ADR in particular can provide data to estimate a few of the core clinical HIV care indicators, such as the proportion of ADAP clients who have received CD4 and/or viral load testing in the past year (Appendix Table 3-3a). The ADR also may be able to provide the data to estimate the indicators pertaining to the proportion of clients with a CD4+ cell count that is less than 500 cells/mm3 who are on ART; the proportion of clients on ART for 12 or more months who have an undetectable viral load; and the proportion of female ADAP clients who are pregnant and on ART. However the data for these indicators are limited to ART drugs that are fully ADAP funded. If a client is not receiving at least one such drug, that person will not be identified as being on ART.

The ADAP reports capture no data pertaining to mental health or substance use screening or services or to the need for or use of supportive services for housing, food, and transportation. Demographic data captured in the ADAP reports are more limited than those captured by the RSR, limited to race and ethnicity, gender (as in RSR), and for the ADAP Quarterly Report, percentage of clients with an annual household income less than 200 percent of the FPL. The ADR includes year of birth and insurance status or type, as well as income as a percentage of the FPL.

As a stand-alone data system, the ADAP reports are of limited usefulness in providing the data needed to estimate the indicators identified by the committee for tracking the provision of HIV care and mental health, substance use, and supportive services in the United States. However, ADAP data may prove useful for assessing waiting time for access to ART drugs and the proportion of people who need, but do not have access to, ART. The committee supports HRSA’s intention to merge the client-level data from the RSR and the ADR into a single system.

Ryan White HIV/AIDS Program data are an important source of information for monitoring access to quality HIV care and supportive services because of the population represented and the importance of the program in providing care and services to many disadvantaged populations. By increasing health insurance options and extending Medicaid coverage to nondisabled individuals who meet the expanded income criteria, implementation of the ACA is expected to reduce the dependency of a portion of current Ryan White HIV/AIDS Program clients on the program to meet their health care service needs, although the Ryan White HIV/AIDS Program likely will continue to serve an important role in providing HIV care to individuals who remain uninsured. Reduction in the use of Ryan White funds for medical care would permit the redirection of funds to other vital Ryan White–funded services. The Ryan White HIV/AIDS Program has an established role in providing a comprehensive array of services beyond medical care, including medical case management and treatment adherence counseling, mental health and substance abuse treatment services, oral care,

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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food assistance, medical transportation, and psychosocial support (IOM, 2011, p. 20). Increased emphasis on such services through continued funding of the Ryan White HIV/AIDS Program and decreased demand for medical care among clients would continue to advance the goals of the NHAS in important ways, for example, by supporting PLWHA “who have challenges meeting their basic needs, such as housing” (ONAP, 2010, p. 21). As one of the few data systems examined by the committee that capture data on housing, food, and medical transportation need, an increase in Ryan White funding available for such supportive services would make it an even more valuable source of data on those services.

Although the population of PLWHA receiving services through the Ryan White HIV/AIDS Program is a large and important one, it is not nationally representative of PLWHA, and use of Ryan White data to estimate the indicators will only permit tracking of the indicators for that group. Another difficulty with Ryan White HIV/AIDS Program data is that data pertaining to medical and supportive services received are reported only when the services were funded with Ryan White dollars. Such services include mental health and substance abuse treatment visits and housing, food, and transportation services. An organization might receive funding from a number of different sources, and if a client were to receive some services funded, at least in part, through the Ryan White HIV/AIDS Program and other services funded exclusively by another source, only the former would be reported to HRSA. Ryan White–funded services vary widely among and within states, depending on how state and local jurisdictions tailor services to meet the needs of local communities (Rawlings and Hopson, 2009). There are persistent dollar-per-case federal allocations to states (Martin and Keenan, 2011), which are associated with the size and scope of ADAP drug formularies (Martin and Barry, 2011). If other sources of state and local funding are used to provide these additional services, they will not appear on the client’s record. To obtain a comprehensive picture of access to needed services within the Ryan White HIV/AIDS client population, it would be helpful to have information on all pertinent services received by clients regardless of funding source, as is the case for clinical data. The clinical information reported by providers who receive Ryan White HIV/AIDS Program funding includes all of the data requested for each Ryan White HIV/AIDS Program client, regardless of how the service was paid for and who delivered it. Thus, all of a given client’s outpatient or ambulatory care visit dates, CD4 and viral load counts, and the like within the reporting period are included.

Along with MMP, the RSR is one of two data systems to provide information on the need for and utilization of supportive services for housing, food, and transportation, as well as HIV medical care and mental health

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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and substance use services.15 The data’s usefulness is limited by the reporting only of those supportive services that are funded through the Ryan White HIV/AIDS Program. Just as all pertinent clinical data are reported by Ryan White–funded providers for clients regardless of payment source, reporting of complete data for supportive service utilization would provide more robust information for tracking the impact of the NHAS and health care reform on the provision of these services. Absent reporting of all supportive service utilization, an indication of whether clients had received any non-Ryan White-funded services would allow analyses of Ryan White HIV/AIDS Program data to be stratified accordingly.

Medicaid Statistical Information System

Medicaid is the largest safety-net health insurance program in the United States, providing health and long-term care coverage to more than 59 million low-income and disabled beneficiaries (KFF, 2011a). Although PLWHA represent less than 1 percent of the total Medicaid population, in FY 2007 Medicaid provided coverage for 47 percent of PLWHA estimated to be receiving regular medical care: 212,892 Medicaid beneficiaries were HIV infected (Kates, 2011, p. 1). Medicaid is financed jointly by the federal and state governments and represents the largest expenditure on health care coverage for PLWHA when federal and state funds are combined. Together, federal and state Medicaid expenditures totaled $9.3 billion in FY 2011, accounting for 51 percent of federal spending for HIV care (Kates, 2011, p. 1). Medicare accounts for another $5.4 billion (29 percent) of federal funding for HIV care (Kates, 2011, p. 1). Approximately 29 percent of Medicaid beneficiaries with HIV were dually eligible for Medicare in FY 2007 (Kates, 2011, p. 1).

The Medicaid Statistical Information System (MSIS) is the claims processing system for Medicaid, which captures utilization data and management information pertaining to medical care and services provided to Medicaid recipients. MSIS includes the full population of people with HIV/AIDS enrolled in Medicaid in the United States,16 and, given Medicaid’s prominent role in HIV care (covering 47 percent of PLWHA estimated to be in care), it not only captures a significant share of PLWHA but also is a critical source of care and coverage that should be assessed. Currently,

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15Housing Opportunities for Persons with AIDS (HOPWA) is a federal program under the U.S. Department of Housing and Urban Development (HUD) that provides short- and long-term housing assistance to PLWHA and their families (HUD, 2011b). HOPWA data, discussed later in the chapter, provide important information on housing needs and services for PLWHA, but are focused primarily on housing.

16It does not include information on individuals who are eligible for, but not enrolled in, Medicaid.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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to qualify for Medicaid individuals must be low income and be “categorically eligible.” Most Medicaid beneficiaries with HIV (74 percent) qualify through the disability pathway, meaning their disease is sufficiently advanced to preclude them from working (Kates, 2011, p. 4). The anticipated expansion of Medicaid under the ACA will remove the categorical eligibility requirement and extend eligibility to most people under the age of 65 who have incomes less than 133 percent of the FPL (Kates, 2011, p. 4). The resulting increase in Medicaid’s role in covering care for PLWHA makes MSIS a particularly important source of data for tracking the impact of the ACA on HIV care.

States are required to report Medicaid beneficiary and claims data quarterly to the Centers for Medicare and Medicaid Services (CMS) through the Medical Management Information System (MMIS).17 These data, which include demographic and monthly enrollment data for each person covered by Medicaid in the quarter (eligible files) and adjudicated claims data (paid claims files), are captured in MSIS. Claims files are categorized by inpatient, long-term care, prescription drug, and noninstitutional services and include data on types and dates of services, providers, costs and types of reimbursement, and epidemiological variables (CMS, 2011c).

MSIS data are available in two forms: MSIS files and Medicaid Analytic eXtract (MAX) files. MSIS files are organized quarterly for the federal fiscal year (October–September) and by transaction or claims adjudication date. They cover all enrollment transactions, including retroactive enrollment and corrections, as well as all interim claims records, including originals, voids, credits, debits, and the like. MAX files contain data extracted from the MSIS files and formatted to facilitate research and public policy needs. They are organized chronologically by calendar year, based on date of service, and MSIS claims records (initial, interim, voids, and adjustments) are combined or consolidated to generate final records for specific services covered by Medicaid as accurately as possible (CCW, 2011c; CMS, 2011a,d). MAX files include a person summary file, as well as inpatient hospital, long-term care, prescription drug, and other services files.18

MAX files are available to approved academic researchers and certain government agencies through the CMS Chronic Condition Data Warehouse (CCW). MAX files currently are available for 1999 through 2008, although 2008 data are not yet available for all states (ResDAC, 2011a).19 MSIS files

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17CMS plans to move to monthly collection of data within 2 years (CMS response to IOM request for information, April 8, 2011).

18More detailed descriptions of MSIS and MAX files, and the differences between them, are available from CMS (2011d). See also RESDAC (2011b), CCW (2011b), and CMS (2010).

19Data are currently missing for Hawaii, Missouri, North Dakota, Pennsylvania, Utah, Wisconsin, and the District of Columbia, although these data were expected to be available on or about October 31, 2011 (CMS, 2011a).

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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are available through FY 2009 (48 states) and for 22 states for FY 2010 (CMS, 2011b). Although most states complete their reporting within a year, not all do, resulting in about a 2-year lag time for MSIS data files. The lag time is somewhat longer (2.5-3 years) for MAX data files because the raw MSIS data must be extracted and consolidated (CCW, 2011c). A built-in lag of at least 13 to 14 months is needed to ensure that claims for most services delivered in a given calendar year are captured, and another 9 to 10 months are needed to validate and process the data (ResDAC, 2011b).20

Advantages of MSIS as a source of data for HIV care include the large number of HIV-infected individuals represented (although enrollees with HIV are identifiable only if they have a diagnosis for HIV entered in the system); strong representation of “vulnerable populations,” including racial and ethnic minorities; regular collection of data over time (currently quarterly, moving to monthly within 2 years [CMS response to IOM request for information, April 8, 2011]), linkage of data to unique personal identifiers, and an existing data processing and data retrieval structure. In addition, diagnostic and treatment information is reported by providers, which may reduce inaccuracies inherent in patient self-report, although nonclinical factors can affect provider reporting also. For example, changes in disease recognition, treatment, and prescription patterns, as well as billing or reimbursement considerations, may have an impact on provider reporting (Crystal et al., 2007). Inaccurate reporting (errors, coding variation, designation) is another nonclinical factor that can affect the accuracy of the data available from MSIS or MAX. MSIS and MAX data include eligibility and claims data and limited demographic data. As is the case with all claims databases, information is available to chart “quality of care” based solely on medical service and medication utilization. Dates of service, diagnosis and procedure codes, and provider codes are available, but core outcome measures such as CD4 and viral load test results are not. Some negative outcome indicators would be available, such as treatment for an opportunistic infection or mortality, based on date of death. Assessment for mental health treatment needs or medical comorbidities would be indicated only if a diagnosis code appears in the case file to justify treatment or medication. Appendix Tables 3-2a through 3-2e summarize which data elements of interest to the committee are captured in MSIS.

One challenge of using MSIS or MAX data is identification of the population of PLWHA who are Medicaid beneficiaries. Variations in diagnostic and other service coding may adversely affect the usefulness of any particular group of codes for accurately identifying the Medicaid population with a given condition. Therefore, use of a combination of diagnosis

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20Although 22 to 24 months has been reported as the minimum lag time for MAX data (RESDAC, 2011b), it appears that 30 to 36 months may be more realistic.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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codes (for HIV/AIDS), common procedure codes (CD4 counts; HIV RNA tests), and prescription drug codes (ARVs) is likely the best way to identify the maximum number of PLWHA among Medicaid recipients with the greatest positive predictive value (see Crystal et al., 2007; Koroukian et al., 2003). Difficulties other than those related to coding also limit the ability to identify the full population of PLWHA within Medicaid. The fluctuating eligibility of some beneficiaries causes those individuals to move in and out of coverage during the course of a year, meaning any medical care they receive in the period during which they are not covered is not captured by Medicaid claims data. Dual eligibility with Medicare also causes claims covered by Medicare not to be captured in Medicaid data. Each of these situations makes it probable that MSIS or MAX data on encounters will not provide a complete accounting of medical services received by individuals in the group (Koroukian et al., 2003). Not only may some Medicaid recipients with HIV not be identified at all, but a number of others within these groups will have incomplete encounter data in MSIS, resulting in an underestimation of the indicators for the population of Medicaid recipients (Crystal et al., 2007).

Similar to the cases in which Ryan White HIV/AIDS Program data include only Ryan White–funded services, even if the MSIS data were complete and accurate, state variation in covered services beyond a set of “mandatory” services required to receive matching federal funds and service payment structure (fee-for-service versus prepaid plans) would mean those data still would not provide a complete accounting of service utilization by individual recipients. For example, MSIS may include data pertaining to a given type of service for some beneficiaries (those residing in a state in which the service is covered) but not capture data on the provision of the same type of service for Medicaid beneficiaries residing in a state where the service is not covered. In addition, states may place limits on the number of occurrences (prescriptions, inpatient days, provider visits) that Medicaid will cover. In both types of case, Medicaid claims data will not provide a complete picture of service utilization by individual beneficiaries.

In other cases, MSIS data may not be complete or accurate. Fee-for-service plans generate fairly complete utilization data because reimbursement depends on filing a claim for each covered service. However, in FY 2007, 71 percent of Medicaid beneficiaries with HIV received some covered services through managed care plans (Kates, 2011). Although states are required to report utilization for beneficiaries in prepaid plans (HMOs, preferred health plans), the accuracy and completeness of these data are suspect (CCW, 2011c; Crystal et al., 2007). Both situations (variations in Medicaid coverage, incomplete or inaccurate Medicaid data) may result in incomplete service utilization data being available from MSIS on specific individuals. Identification of the most common service providers for

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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individuals with variable Medicaid eligibility or of services not covered by Medicaid (e.g., Ryan White HIV/AIDS Program) would permit use of data from these additional sources to gain a more complete measure of the full set of services received by these individuals. Likewise, combined Medicare and Medicaid data for individuals dually eligible for both programs also would provide a more complete picture of service usage. As discussed in Chapter 6, although combining data from multiple data systems to generate a more complete measure of service utilization for the purpose of estimating the recommended indicators is a theoretical ideal, doing so in practice poses numerous statistical challenges.

Demographic data of interest are limited to date of birth, date of death, gender (male, female), race and ethnicity, and zip code. MSIS also collects limited information on private payer status. Income (as a percentage of the FPL) is an optional field, although information about income level could be inferred based on eligibility criteria. Also, data are collected on whether the beneficiary received Temporary Assistance for Needy Families benefits during the month. MSIS links data to unique individual identifiers (either MSIS generated or Social Security number, depending on the state), so that information may be tracked across time for individuals, permitting evaluation of their longitudinal care experiences to the extent permitted by claims data. The demographic data collected would permit assessment of indicators for racial and ethnic subgroups of interest, as well as subgroups based on location of residence and payer status. Since data on sexual orientation are not collected, MSIS data do not permit estimation of the indicators for the NHAS-targeted subgroup of gay and bisexual men, although separate assessments could be made for men and women with data based on sex. With respect to the core indicators of HIV care, MSIS could be expected to provide the data needed to assess the indicators pertaining to continuity of care and regular CD4 and viral load testing, based on claims submitted for office visits with HIV listed as one of the diagnosis codes and claims submitted for CD4 and viral load tests, all of which capture dates of service (see Appendix Table 3-3a). However, any services received by an individual that were not reported to CMS would not be included in MSIS, resulting in gaps in the information available. MSIS captures date of death and so could provide data to calculate the mortality rate within its population of PLWHA.

MSIS captures neither the date of HIV diagnosis nor the date of first visit for HIV care; thus it cannot be used to assess the linkage-to-care indicator. Also, since MSIS does not capture clinical data, such as the results of CD4 counts and viral load tests, it cannot independently provide the information needed to assess the remaining core indicators of clinical HIV care, even though it collects data on the prescription and (re)fill dates for ART drugs, when claims are submitted.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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MSIS captures data pertaining to screening and visits for mental health and substance use services covered by Medicaid, but it does not specifically capture the dates of (hence, the time between) diagnosis or referral and first visit for services. With regard to supportive services, MSIS collects data on the provision of social work or case management services, but specific information pertaining to housing, food, and transportation needs is not captured (see Appendix Tables 3-2b, 3-3b).

For the additional indicators (see Appendix Tables 3-2c, 3-3c), MSIS could provide data to assess the clinical HIV care indicators relating to TB, sexually transmitted infections (STIs), and hepatitis B and C screenings, along with influenza, pneumococcal pneumonia, and hepatitis B immunizations, although clinical information about whether the TB test results were interpreted or hepatitis B immunity was documented would not be available. Data would also be available to assess the indicators pertaining to drug resistance testing and the proportion of HIV-infected pregnant women on ART, although pregnancy status would have to be extrapolated from related diagnostic or service codes. Data to assess indicators relating to timely diagnosis of HIV infection and those involving clinical markers for ART initiation would not be readily available.

Despite the importance of data from the Medicaid population for tracking the impact of the NHAS and the ACA on HIV care, MSIS and MAX data have some limitations. As previously noted, the lag time from service utilization to reporting completion (especially for MAX data) may be problematic for time-sensitive policy evaluation. In addition, Medicaid data alone may not provide a complete accounting of service utilization by beneficiaries who receive services from multiple funding sources, and strategies must be employed to help correct for that additional encounter data. Stephen Crystal and colleagues (2007) list some “best practices” for working with Medicaid data. Development of methods for combining data from or analyzing data across additional relevant data systems (e.g., Medicare, Ryan White HIV/AIDS Program) might provide more complete information on service utilization for individuals receiving services through two or more of the programs. One such effort is the database of linked Medicaid and Medicare data developed by CMS in 2009, which contains service utilization and expenditures data for 9 million dually eligible beneficiaries (CHCS, 2010). CCW assigns a unique beneficiary identification number for the MAX and Medicare records of dually eligible beneficiaries to permit tracking and analysis of data across programs (CCW, 2011c, p. 4).

Chronic Condition Data Warehouse

Although not representing as large a patient population as Medicaid, Medicare accounted for 29 percent of federal spending on HIV in FY

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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2011 (Kates, 2011), the largest source of federal spending on HIV care.21 Medicare is a federal program providing health care coverage to disabled individuals and those age 65 and older. Approximately 100,000 Medicare beneficiaries are HIV-infected, representing about 20 percent of HIV-infected individuals estimated to be receiving care in the United States (KFF, 2009a). The majority of PLWHA currently receiving Medicare qualified through the disability pathway. With the evolution of HIV into a chronic condition, many PLWHA are living longer and increasingly are expected to qualify for Medicare on the basis of age, resulting in an increase in the number Medicare beneficiaries with HIV. Given Medicare’s Part D prescription drug coverage and the increasing number of Medicare-eligible PLWHA, Medicare plays an important role in HIV care coverage.

The CCW contains fee-for-service22 claims data for 100 percent of Medicare beneficiaries from 2005 to 200923 and Part D drug event data from 2006 to 2009 (CCW, 2011a, About). As such, it includes fee-for-service utilization data for all PLWHA who are enrolled in the Medicare program. To expedite delivery and maximize cost efficiency, data sets are available for predetermined cohorts representing 21 chronic conditions. Although HIV/AIDS is not presently one of the predefined cohorts, it currently is under consideration for addition to the list of flagged conditions (CCW, 2011a, Chronic Conditions).

Medicare uses a unique beneficiary identification number and collects the basic demographic data of interest: date of birth, date of death, OMB-defined race and ethnicity, gender (male, female), and zip code. The Medicare Current Beneficiary Survey (MCBS) of a representative national sample of Medicare beneficiaries is used to generate two files (Access to Care; Cost and Use) each year. The Access to Care file “contains summaries of use and expenditures for the year from Medicare files along with survey data on insurance coverage, health status and functioning, access to care, information needs, satisfaction with care, and income” (CCW, 2011b, p. 10). Although MCBS data are not automatically linked to Medicare beneficiary identification numbers, information is available upon request to permit MCBS data to be merged with other CCW data at the beneficiary level. Medicare also requires assessments for beneficiaries receiving care in nursing facilities, inpatient rehabilitation facilities, and home care. These assessments provide data on certain aspects of beneficiaries’ health status, as well as other relevant information (e.g., the safety and sanitary condition of the individual’s

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21Federal spending on Medicare is greater than that on Medicaid (if the state share is not included) and the Ryan White HIV/AIDS Program (KFF, 2011b).

22Most services for Medicare recipients in managed care are not captured in the CCW.

23The CCW also contains data on a random 5 percent sample of Medicare beneficiaries for 1999 forward.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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home for those receiving home care) and likely will increase in importance as the population of PLWHA ages and individuals with HIV enter home and institutional nursing care in greater numbers.

As a source of claims data, Medicare is similar to Medicaid in terms of the data available to assess the core indicators of HIV care. It should be able to inform indicators related to continuity of care, regular CD4 and viral load testing, and mortality rate, but it does not contain the information necessary to evaluate the linkage-to-care indicator or the clinical data needed to assess the other core HIV care indicators. ART drug prescription and (re)fill data are available for Medicare Part D beneficiaries. The availability of Medicare data to assess the additional indicators for HIV care is similar to that of MSIS data as well.

Although Medicare does not have data on screening for mental health disorders or substance use, it does capture service utilization data on the diagnosis of and covered treatment for these conditions, but as with Medicaid, the data do not specifically permit calculation of the time between treatment referral and receipt of services. Medicare does not collect data on housing, food, or transportation needs, although questions pertaining to housing adequacy are included in the assessment for home health beneficiaries (OASIS).

As previously noted, efforts to link Medicare and Medicaid data for dually eligible beneficiaries will provide a more complete picture of service utilization for that group of individuals. In addition, inclusion of HIV/AIDS in the list of predetermined chronic condition cohorts for which CCW data sets are available should expedite delivery of these data for research and policy use.

North American AIDS Cohort Collaboration on Research and Design

The North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD) captures data from 22 single and multisite clinical and classical epidemiologic HIV cohorts, which represent most of the HIV/AIDS cohort studies in North America, including the CFAR Network of Integrated Clinical Systems (CNICS) and the HIV Research Network (HIVRN) discussed in the following sections. Although NA-ACCORD includes data from CNICS and HIVRN, not all of the data elements captured by those systems are represented in NA-ACCORD.

NA-ACCORD collects data on more than 100,000 HIV-infected adults from more than 60 academic research and hospital- and community-based clinical sites throughout the United States (44 states and the District of Columbia) (Kitahata, 2011; NA-ACCORD, 2011; NA-ACCORD response to IOM request for information, March 30, 2011). NA-ACCORD is de-

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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signed to be widely representative of HIV care in the United States,24 and the population of PLWHA represented is similar to that reported by the CDC in terms of age and sex, but it includes somewhat fewer minorities25 (Kitahata, 2011; NA-ACCORD response to IOM request for information, March 30, 2011).

NA-ACCORD data pertaining to the core clinical HIV care indicators include date of diagnosis (although these data are not complete); date of first visit at the clinical site and whether the individual was previously seen at another site (but not always the date of first-ever visit for HIV care); dates of routine HIV care visits; CD4 and viral load test dates and results; dates that individual ARVs were started or stopped; year of birth; and mortality information (date and cause of death) (Appendix Tables 3-2a, 3-3a). For the additional indicators of clinical HIV care, NA-ACCORD also includes dates of ART drug resistance testing; diagnoses of AIDS-defining conditions; diagnoses of and/or laboratory results relevant to renal disease (nephropathy), hepatitis C, and hepatitis B; dates of hepatitis C and hepatitis B screening; and dates of TB testing (Quantiferon-TB tests). As of 2012, NA-ACCORD collects information on pregnancy status. NA-ACCORD does not currently collect dates of screening for chlamydia, gonorrhea, and syphilis or dates of vaccination or immunization for hepatitis B, influenza, or pneumococcal pneumonia (see Appendix Tables 3-2c, 3-3c).

Information on diagnosis or referral for mental health disorders and substance abuse is included in NA-ACCORD, but not data on screening for those disorders or on first visit for mental health or substance abuse treatment, although it will capture visits for psychiatry, psychology, and counseling, beginning in 2012. NA-ACCORD does not include data pertaining to housing stability, food security, or access to transportation but could add such data to the extent they are collected by social workers in the clinical practice setting (Appendix Tables 3-2b, 3-3b).

Demographic information available in NA-ACCORD includes age, sex, race and ethnicity, and the first three digits of zip code, as well as metropolitan statistical area (MSA), and, as of 2012, country of birth. Data on

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24Since urban areas are heavily represented among the cohorts, NA-ACCORD may not be representative of the care experience of PLWHA in rural areas.

25A comparison of 2007 data for NA-ACCORD and the population of PLWHA indicates that NA-ACCORD had a lower proportion of non-Hispanic blacks (40 percent versus 46 percent) and Latinos (14 percent versus 20 percent), as well as a higher proportion of non-Hispanic whites (41 percent versus 32 percent) (Kitahata, 2011). Older (2005) data reported for the NHSS (33 states and U.S. dependent areas with confidential name-based reporting) and NA-ACCORD for HIV transmission risk factors suggest that, at the time, NA-ACCORD had a lower proportion of men who have sex with men (33 percent versus 44 percent) and a higher proportion of injection drug users (27 percent versus 20 percent) and individuals infected through heterosexual contact or other means (40 percent versus 30 percent). (See CDC, 2007, Table 8; Gange et al., 2007, Table 3.)

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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sexual orientation, gender identity, income, and insurance status are not collected. (See Appendix Table 3-2d.)

Data collected by NA-ACCORD can be used to estimate all of the core indicators of clinical HIV care. The data system is less useful for estimating the additional clinical care indicators and much less so for indicators pertaining to mental health, substance abuse, and supportive services. A strength of NA-ACCORD is that new data elements can be added relatively easily if they are collected by the participating cohorts.

CFAR Network of Integrated Clinical Systems

The CFAR Network of Integrated Clinical Systems comprises a network of eight Centers for AIDS Research (CFAR) sites26 that have implemented point-of-care electronic data collection systems. CNICS data are collected prospectively through these systems on PLWHA in care at the site and, therefore, characterize the rapidly changing course of HIV disease management. The CNICS cohort includes more than 23,000 individuals and represents a diverse population of patients with regard to sex, race, ethnicity, age, risk factor for HIV transmission, and geographic distribution, although the CFAR sites are located in urban areas and the data may not be representative of PLWHA in rural areas (CNICS, 2011, CNICS sites; Kitahata, 2011).

CNICS currently maintains data on 10 unique domains: (1) disease diagnoses; (2) laboratory data (viral load, CD4 count, viral hepatitis, hematologic, kidney, and chemistries or metabolic markers); (3) medication data; (4) demographics (sex, race and ethnicity, age, and risk factor for HIV transmission); (5) health care utilization (initial patient enrollment, primary care visits, and hospitalizations); (6) vital status (death date, source, and cause of death); (7) patient-reported outcomes27; (8) antiretroviral drug resistance; (9) biological specimens; and (10) census block data (CNICS, 2011, Data elements).

According to the project website, an important distinction between

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26These are Case Western Reserve University; University of Alabama at Birmingham; University of California, San Francisco; University of Washington; University of California, San Diego; Fenway Community Health Center of Harvard University; University of North Carolina; and Johns Hopkins University. Although the Johns Hopkins University site is no longer CFAR-funded, it has continued to collaborate with other CNICS sites.

27Most sites collect patient-reported outcomes data from consenting patients using touch-screen tablets or PCs that are connected to a wireless network. Data are captured on depression and anxiety; adherence; smoking, alcohol, drug use; HIV transmission risk behaviors; symptom burden; physical activity level; body morphology; and quality of life. As of August 2010, there were approximately 8,000 completed assessments in the central database (CNICS, 2011, Data elements).

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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CNICS and other cohorts is the ability to provide peer-reviewed open access to data for research from a system that prospectively collects comprehensive patient data including validated outcomes, longitudinal resistance data, and PROs (CNICS, 2011).

CNICS includes much of the data needed to calculate the core clinical HIV care indicators (Appendix Tables 3-2a, 3-3a), including dates of first and ongoing visits for HIV care, CD4 and viral load test dates and results, and dates of starting and stopping specific ARVs. Information on date of diagnosis is collected by CNICS, but these data are not available for some individuals. For the additional clinical HIV care indicators (Appendix Tables 3-2c, 3-3c), CNICS collects data on diagnosis of AIDS-defining conditions; hepatitis B and C; chlamydia, gonorrhea, and syphilis screening; ART drug resistance testing; and diagnosis of renal disease. Data also are collected on TB testing using QuantiFERON-TB tests. As of 2012, data on pregnancy status is collected, and collection of immunization information for hepatitis B, influenza, and pneumococcal pneumonia is proposed. If all these data are collected, CNICS will capture the data needed to estimate all of the core and additional indicators for clinical HIV care.

CNICS also collects certain data on mental health and substance abuse disorders, including dates of screening and diagnosis or referral. Although CNICS does not specifically capture the date of first visits for mental health treatment services, it does capture visits for psychiatry, psychology, and counseling. Since it also captures date of screening, a proximate visit for services would suggest date of first visit, but it would not be flagged as such. CNICS captures whether an individual received substance abuse treatment in the past year, but not specific dates of service. CNICS does not currently include data on housing, food, and transportation needs assessment or status, but data on housing stability (stable or permanent, temporary, unstable, and homelessness) are collected in the clinical practice setting and could be added to CNICS (CNICS response to IOM request for information, April 11, 2011).

Demographic data captured in CNICS include age, sex, race, and ethnicity. Data on sexual orientation and gender identity are not currently collected. CNICS collects MSA of residence and is adding the three initial numbers of individuals’ zip codes, which provide state and at least county of residence, as permitted by the Health Insurance Portability and Accountability Act. Country of birth is collected beginning in 2012. Insurance status is collected, and income data are collected and could be added to CNICS. PROs provide an opportunity to collect qualitative data on satisfaction with provider care and on stigma or discrimination, as well as other information of interest, including food security and transportation needs.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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HIV Research Network

The HIV Research Network compiles data electronically from health records and through manual medical record review in order to obtain, analyze, and disseminate current information on the delivery of services to PLWHA. HIVRN captures these data longitudinally to assess trends in areas such as accessibility, quality, utilization, safety, and costs of HIV-related health care services. HIVRN is primarily supported by the Agency for Healthcare Research and Quality with additional support from other agencies of the U.S. Department of Health and Human Services (HHS).

HIVRN represents a consortium of 16 academic and community-based sites that provide primary and subspecialty HIV care in 13 cities throughout the United States, with 8 in the eastern United States, 1 in the Midwest, 3 in the South, and 4 in the West (HIVRN, 2011). Data are collected annually on the clinical and demographic characteristics of approximately 21,000 adults, adolescents, and children receiving HIV care at the participating sites (HIVRN response to IOM request for information, March 30, 2011). (Five of the sixteen sites are devoted to pediatric care.) The data from each site are sent to the data coordination center at the Johns Hopkins School of Medicine, where they are consolidated into a single uniform database.

HIVRN data can be used to estimate all of the core clinical HIV care indicators identified by the committee. In addition, data for estimating the core indicators for mental health and substance abuse are available for a subset of the participating sites. HIVRN does not collect data on the dates of screening for mental health or substance abuse disorders, nor does it collect any data pertinent to the committee’s core or additional indicators for housing, food security, or unmet need for transportation. As with NA-ACCORD and CNICS, HIVRN data are collected from urban areas and may not be representative of PLWHA in rural areas.

Clinical Case Registry: HIV

The Veterans Health Administration within the Department of Veterans Affairs is the largest provider of HIV care in the United States, serving more than 24,000 veterans with HIV in 2010 (VA, 2011). The Clinical Case Registry (CCR): HIV is an administrative and clinical database containing population-based data on HIV-infected individuals who receive care through the VHA.28 Local reporting allows clinicians with access to the database to monitor clinical outcomes and resource utilization. The national database permits quality of care, as well as outcomes and utiliza-

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28A second CCR collects data on veterans with hepatitis C who receive care in the VHA system.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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tion, monitoring. Data on all veterans with a confirmed diagnosis of HIV/AIDS in VHA care during the calendar year are included in the database. The sample is limited to those veterans who receive care within the VHA system and is older and predominantly male, compared with the overall population of PLWHA in the United States (VHA response to IOM request for information, April 11, 2011).

The VHA has a sophisticated EHR system that captures utilization and outcomes data. Data needed to calculate all of the core clinical HIV care indicators and most of the additional clinical care indicators are available from the EHR if the services are performed within the VHA system (Appendix Tables 3-2a, 3-2c, 3-3a, 3-3c). Date of diagnosis, CD4 count at diagnosis, and date of first visit for HIV care are all available for individuals diagnosed and treated within the VHA, but for those who transfer into the system following diagnosis, data on linkage to care and stage of disease at diagnosis are not available. Information on prescriptions and refills written by VHA providers is available as are dispensing data for prescriptions (re)filled through the VHA pharmacy system.

Although prenatal care is covered by the VHA, prenatal care services are provided outside the system by community providers. Although the VHA EHR does not capture data from external providers, the information pertaining to ART prescription for pregnant women would be available for prescriptions filled through the VHA pharmacy system.

Data pertaining to screening for mental health disorders and substance use are not captured in the VHA data system (VHA response to IOM request for information, April 11, 2011), but it does include data on diagnosis of or referral for mental health and substance abuse disorders, as well as date of first visit for treatment services if they occur in the VHA. Data pertinent to the supportive services indicators are not collected, although some data pertaining to social work or case management are captured. (Appendix Tables 3-2b, 3-3b). Demographic data collected include age, sex, race, ethnicity, and address. Data on gender identity, sexual orientation, income, insurance status, and country of birth are not collected. (See Appendix Tables 3-2d, 3-2e.)

As an EHR, the VHA data system contains comprehensive clinical data on test and treatment services provided within the system, including prescription and pharmacy dispensing data, although information on services provided outside the system is not reliably captured.29 As an integrated health care system, the VHA is well poised to respond to challenges raised by the NHAS, as demonstrated by its recent efforts to implement routine

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29A uniform notation in the EHR indicating whether a patient reports having received health care services outside of the VHA system could facilitate research on health care services provided by the VHA.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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HIV testing. Although the population of PLWHA served by the VHA is disproportionately male and older compared to the national population of PLWHA, recent collaborative efforts between the VHA and Kaiser Permanente (KP) (discussed in the following section) may be the first step in addressing concerns about representativeness.

Kaiser Permanente

Kaiser Permanente is one of the largest not-for-profit health plans in the United States, providing coverage to more than 8.7 million members in nine states and the District of Columbia (KP, 2011). Health outcome and utilization data are collected on all members through EHRs and databases. The second-largest private provider of HIV care in the United States in 2006, with more than 16,000 HIV-infected individuals in care, KP data represent a diverse population of individuals with private insurance in California, Hawaii, and selected metropolitan areas, including Baltimore, Maryland; Washington, DC; and Atlanta, Georgia. Analyses have shown that KP is representative of the HIV-infected population in California (KP response to IOM request for information, March 30, 2011), a state with more than 6.5 million KP members (KP, 2011), and as the largest provider of HIV care in Hawaii, KP is representative of the population there as well (KP response to IOM request for information, March 30, 2011).

KP has a sophisticated EHR system that facilitates the capture and retrieval of detailed clinical data. A major benefit to a robust EHR system is the availability of data on both service utilization and clinical outcomes. KP captures all of the data elements necessary to assess the core indicators of clinical HIV care, although the date of HIV diagnosis is only captured for individuals diagnosed within the KP system (Appendix Tables 3-2a, 3-3a). Thus, the linkage-to-care indicator can be calculated reliably only for those in the system at the time of diagnosis. KP also captures the data needed to assess the additional indicators for clinical HIV care (Appendix Tables 3-2c, 3-3c). Data on the prescription of ART drugs are available, as are most pharmacy (re)fill data. No data are available on prescriptions (re) filled at pharmacies outside of the KP system.

KP also records data on screening for mental health disorders and substance abuse, although the screenings are performed as indicated and not according to a predetermined schedule. Data on referral for services for mental health disorders and substance abuse are included in individuals’ EHRs, as are data on receipt of treatment services that are provided within the KP system. Data relevant to supportive services indicators are not routinely collected within the KP system.

As an integrated health care system with a comprehensive EHR system, KP, like the VHA, captures comprehensive clinical test and treatment

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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data for services provided within the system. Although the population of PLWHA served by KP is not nationally representative, it is representative of the privately insured HIV-infected population in areas of the United States with access to Kaiser (Hawaii; California; Oregon; Mid-Atlantic region, including the District of Columbia; Atlanta, Georgia).

In December 2009, KP and the VHA launched a pilot project in San Diego, California, for electronically sharing EHR files of individuals who receive care from both systems with patient permission (KP, 2009). Now part of the Nationwide Health Information Network Exchange project (NwHIN Exchange, 2011), this type of data sharing not only should improve patient care but also could permit the capture of similar types of data from a larger and more diverse population than those represented by the individual participating systems.

National Vital Statistics System

Most of the data systems reviewed by the committee collect date of death. In particular, the NHSS would serve as the most nationally representative source of data for estimating the committee’s recommended mortality indicator: all-cause mortality rate among PLWHA. As indicated in Chapter 2, the committee selected all-cause mortality for the indicator because of the inherent difficulties in determining and recording in every instance whether deaths among PLWHA were related to the disease or another cause. Mortality rate due to HIV nevertheless may be a useful measure for some purposes. In such cases, the National Vital Statistics System (NVSS) is the best source of data for estimating mortality related to HIV infection. Although some of the data systems examined by the committee, such as NA-ACCORD, record information on cause of death, the NVSS regularly calculates HIV mortality. NVSS operates under the auspices of CDC’s National Center for Health Statistics, which collects vital statistics data through contracts with the registration systems in jurisdictions that are legally responsible for recording vital events, such as births and deaths (NVSS, 2011a). Mortality data from the NVSS provide uniform, nationwide demographic, geographic, and cause-of-death information for individuals who die in the United States (NVSS, 2011b). Standard forms (e.g., death certificate) and model procedures are developed and recommended for nationwide use to promote the collection of uniform national data. The death certificate requires a single immediate (final) cause of death and allows for as many as three underlying causes of death to be listed sequentially (CDC, 2011c). Although reporting errors of various types may occur for cause of death, CDC provides extensive information on writing cause-of-death statements for death certificates (NVSS, 2011c). Preliminary HIV mortality data currently are available for 2009 (Kochanek et al., 2011).

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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ADDITIONAL DATA SYSTEMS FOR MONITORING HIV CARE

The committee identified three additional systems that provide data to help evaluate the impact of the NHAS and the ACA on HIV care and access to supportive services for PLWHA in the United States. The Indian Health Service (IHS) and the Federal Bureau of Prisons (BOP) have data systems that capture health care data for two small but important subpopulations of HIV-infected individuals: American Indians and Alaska Natives (AI/ANs) and federal prisoners. The Housing Opportunities for Persons with AIDS (HOPWA) program collects data pertinent to the program’s funding of assistance for housing and other supportive services for its beneficiaries.

Resource and Patient Management System

Nationally, AI/ANs represent less than 1 percent of PLWHA (between 3,039 and 3,083 individuals in 2009) (CDC, 2012, Commentary, Table 15a). Yet, AI/ANs are disproportionately burdened by the epidemic in several ways. The rate of HIV diagnoses among AI/ANs was 9.7 (per 100,000) in 2010, compared with 6.5 for Asians and 7.3 for whites (CDC, 2012, Table 1a).30 Compared with other racial and ethnic groups, AI/ANs also have one of the shortest timelines from AIDS diagnosis to death (CDC, 2012, Commentary, Table 14a; Hall et al., 2005). Impoverishment and conditions such as alcoholism and diabetes that occur at higher rates among AI/ANs (Chartier and Caetano, 2010; IHS, 2008) may complicate care and adherence to treatment.31 The IHS is the federal agency responsible for providing comprehensive health care services to approximately 2.0 million AI/ANs representing 566 federally recognized tribes (IHS, 2012). Most IHS facilities are primary care clinics. Two IHS-funded hospitals together treat the majority of HIV patients in the lower 48 states (Personal communication, Lisa Neel, Indian Health Service, October 13, 2011). Combined with an additional two sites, these facilities account for 61 percent of the IHS HIV/AIDS case load (Personal communication, Lisa Neel, Indian Health Service, October 13, 2011). Although some IHS clinics provide limited HIV care services, most refer their HIV clients to outside providers for HIV care (GAO, 2007; IHS response to IOM request for information, March 28, 2011). As of June 2011, there were 289 HIV/AIDS patients on record at federal IHS health care service sites, of which 224 were “active,” having received CD4 and viral load testing within the preceding 12 months. Patients receiving care in tribally operated and urban Indian health care programs are not included in

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30Black or African Americans and Native Hawaiian and other Pacific Islanders had higher rates of diagnosis (CDC, 2012, Table1a).

31In addition, an estimated 25 percent of AI/ANs with HIV infection are undiagnosed (CDC, 2011a).

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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these numbers due to administrative constraints (Personal communication, Lisa Neel, Indian Health Service, February 29, 2012).

The IHS uses an electronic record system called the Resource and Patient Management System (RPMS) to manage clinical, administrative, and financial information on patients and resources and improve the quality of care provided at federal, tribal, and urban IHS facilities throughout the United States (Cullen, 2006). Data are entered into RPMS by providers during patient visits.32 An optional automated module within RPMS called the HIV Management System (HMS) may be used by HIV care providers and case managers in the IHS system to capture data related to HIV/AIDS and to assist nonspecialist providers with decision making through the use of clinical reminders, provider guidelines, and quality-of-care audit reports. HMS captures HIV-specific information such as date of HIV diagnosis, CDC classifications, and ART status. Lab, radiology, and pharmacy data are available through linkage with RPMS. HMS also may be used to report HIV/AIDS cases to public health authorities through a state surveillance form and report (Cullen, 2006). HMS was first implemented in 2006, and personnel at 12 IHS facilities had been trained in how to use the system by October 2007 (GAO, 2007). In 2009, it was integrated into RPMS (IHS, 2011a, Home, Tech Support), but HMS usage is not mandatory (IHS, 2011d). Although 283 IHS facilities have downloaded HMS as part of the RPMS update, only the two large hospitals that treat the majority of HIV-infected patients are known to use the system and contribute to its ongoing development (Personal communication, Lisa Neel, Indian Health Service, October 13, 2011).

Another component of the RPMS, called the Clinical Reporting System (CRS), is used for national, local, and area monitoring of clinical performance measures. The CRS draws from local RPMS databases to create printed or electronic reports of clinical performance measures, including HIV screening and HIV quality of care, as well as a number of other conditions (e.g., STI, depression, and alcohol screening) that may be relevant for monitoring HIV care (see IHS, 2011c). According to 2011 guidance on the CRS, HIV screening information is reported nationally (IHS, 2011b,c). Reported information includes data on HIV screening among pregnant women and among patients age 13 to 64 with no recorded HIV diagnosis prior to the report period, broken down by gender and age groups, as well as the percentage of patients with documented HIV screening refusals (IHS, 2011b,c). In addition, information is reported on the percentages of patients with positive, negative, or indeterminate test results and on the

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32Although the IHS is a federal agency, tribal data require special permission to access, since the data belong to the tribe and not to the federal government (IHS response to IOM request for information, March 28, 2011).

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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number of HIV tests given to patients during the report period where the patient was not diagnosed with HIV any time prior to the screening (IHS, 2011b). HIV screening is also incorporated into a syphilis, gonorrhea, chlamydia, and HIV screening measure where diagnosis of one of these STIs prompts screening for the other three (IHS, 2011b).

CRS also captures HIV quality-of-care data for the user population of patients age 13 and older with at least two direct care visits (i.e., visits within the IHS system) during the report period with HIV diagnosis and one HIV visit in the last 6 months (IHS, 2011c). These measures are not reported nationally, however. The quality-of-care measures assessed are (1) the percentage of patients who received the CD4 test only (without HIV viral load) during the report period; (2) the percentage of patients who received HIV viral load only (without CD4) during the report period; (3) the percentage of patients who received both CD4 and HIV viral load tests during the report period; and (4) total numerators 1, 2, and 3 (IHS, 2011c). The first collection period for these variables was July 2010–June 2011 (Personal communication, Lisa Neel, Indian Health Service, October 13, 2011). IHS recently added “newly diagnosed HIV” to CRS, but the measure has not yet been validated (Personal communication, Lisa Neel, Indian Health Service, October 13, 2011).

As with other clinically based EHR systems (e.g., KP, VHA), the IHS collects all of the data needed to calculate the core clinical HIV care indicators for services provided within the IHS (Appendix Tables 3-2a, 3-3a), and the HMS attempts to include historical data about tests and services provided outside of IHS facilities. Similarly, the IHS captures the data pertinent to the additional clinical HIV care indicators (Appendix Tables 3-2c, 3-3c). Even if certain data (e.g., date of influenza vaccination) are not currently captured in the HMS, they may apply to quality measures for other subpopulations (e.g., individuals ages 50 and older, individuals with diabetes) (IHS, 2011c). In addition, data would be captured at the patient level and could be applied to HIV-specific indicators in the future.

Data for calculating the mental health and substance abuse indicators also are captured by the IHS (Appendix Tables 3-2b, 3-3b, 3-3d). Information pertaining to the need for and provision of supportive services may be recorded in the provider narrative section of the EHR. Demographic data collected include age, sex, race, ethnicity, and locality of residence. Data on gender identity and sexual orientation are not routinely collected but might be recorded in the provider narrative section of the EHR.

IHS captures the data necessary for estimating most of the indicators identified by the committee, which could be used to track improvements in HIV care and access within the population of HIV-infected individuals receiving care in IHS facilities. The limited number of IHS facilities providing comprehensive HIV care can affect the size of the HIV-infected population

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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represented in the data system. Facilities that transition from federal to tribal management no longer automatically report data to IHS. In addition, some tribal facilities have moved from IHS to private-vendor EHRs, making data sets incompatible.

Bureau of Prisons Electronic Medical Record

When both state and federal prisons are considered, 21,987 inmates (1.5 percent of total inmates) were HIV infected or had confirmed AIDS as of the end of 2008. Of those inmates, 1,538 were federal prisoners (Maruschak, 2010).

The BOP, which is responsible for ensuring access to health care services for the almost 217,000 individuals incarcerated in federal correctional institutions throughout the United States (BOP, 2011), uses the Bureau of Prisons Electronic Medical Record (BEMR), a point-of-care direct entry web-based system record, to collect health information on inmates housed at 116 federal correctional institutions (BOP response to IOM request for information, April 14, 2011). The BEMR includes a fully integrated pharmacy capability (computerized order entry through prescription administration records, BEMRx) as well as a dental module (DOJ, 2011; Price, 2011). The BEMR tracks CD4 count and viral load for prisoners with HIV/AIDS. Other information contained in the BEMR that may be useful for tracking HIV/AIDS care received by prisoners includes demographic, prescription drug, substance use, and mental health data. The BOP is in the process of enhancing the BEMR by programming key HIV data elements for the extraction and analysis of HIV data that currently are available only in individuals’ records (BOP response to IOM request for information, April 14, 2011).

Due to the much larger number of HIV-infected inmates in state prisons, it would be necessary to track HIV care data from the state inmate population as well in order to gain a more complete picture of HIV care within the U.S. corrections system. Gathering and integrating data from the individual state systems poses a significant challenge, however. A 2007 survey of state electronic health initiatives found that although 22 of 42 states responding had implemented some sort of health information technology use in their state prison systems, only 3 states reported the use of EHRs and/or electronic medical records (Smith et al., 2008). Kentucky had implemented an EHR system across all of its state-operated correctional facilities. Virginia had planned implementation of an EHR system for its correctional facilities, and Washington State was exploring the feasibility of a single, integrated EHR for all of its correctional institutions, including state prisons, city and county jails, and juvenile corrections facilities (Smith et al., 2008).

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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Integrating EHRs across all types of correctional institutions would provide a rich source of data for tracking the provision of HIV care in the incarcerated population. For individuals already diagnosed with HIV, linkage to and maintaining continuity of care and treatment adherence upon release is a significant challenge. Development of methods for capturing data on the provision of transitional services and associated outcomes for HIV-infected prisoners upon release would be important in this regard (Rich et al., 2011).

Housing Opportunities for Persons with AIDS

The HOPWA program, managed by the U.S. Department of Housing and Urban Development’s (HUD’s) Office of HIV/AIDS Housing, provides funds for housing assistance and other supportive services. The additional supportive services most relevant to the indicators identified by the committee include meals and nutritional services, transportation services, mental health services, and alcohol and drug abuse services, as well as approved health, medical, and intensive care services (HOPWA, 2011a,b). HOPWA programs provide assistance to low-income households with one or more PLWHA along with other members of the household. By the end of FY 2010, HOPWA had provided resources for housing assistance to 60,669 unduplicated households (HOPWA response to IOM request for information, April 4, 2011). The population served by HOPWA is generally representative of low-income PLWHA (HOPWA response to IOM request for information, April 4, 2011).

HOPWA grantees report aggregated data on program performance outcome measures related to maintenance of housing stability, improved access to care and support, and reduced risk of homelessness for low-income persons and their families living with HIV/AIDS. HOPWA Competitive Program grantees submit an Annual Progress Report (APR) and Formula Program grantees submit a Consolidated Annual Performance Evaluation Report (CAPER) measuring performance outcomes.

APR and CAPER (HOPWA, 2011a,b) report information on the number of households with an unmet need for housing assistance,33as well as the type of subsidy assistance needed. They also report on the number of households served by HOPWA and other funding sources that provide housing assistance and support to PLWHA and their families and the number of households that received other supportive services through HOPWA funds (e.g., meals or nutritional services, transportation, mental health

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33These data are for “the number of HOPWA-eligible households that require HOPWA housing subsidy assistance, but are not served by any HOPWA-funded housing subsidy assistance in [the] service area” (HOPWA, 2011b, p. 8).

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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services, alcohol and drug abuse services). Aggregate data are reported on the number of PLWHA who qualified their household to receive HOPWA housing assistance, their prior living situation, the number of other PLWHA who reside with the HOPWA-eligible individuals, and the number of persons not diagnosed with HIV who reside with the eligible individuals. The reports also record the number of HOPWA-eligible individuals and other beneficiaries by race and ethnicity, as well as by sex (male, female) and gender (transgender male to female, female to male) within given age ranges. Additional information reported includes number of households that demonstrated “a housing plan for maintaining or establishing stable on-going [sic] housing”; contact with a case manager or benefits counselor as specified in the client’s individual service plan; contact with a primary health care provider as specified in the client’s individual service plan; access to and maintenance of medical insurance or assistance; and sources of income. The reports also include the number of households receiving assistance by percentage of area median income.

In addition to the aggregate data reported by HOPWA grantees, HUD developed the Homeless Management Information System (HMIS) to store longitudinal standardized individual-level data on persons receiving housing assistance and homeless prevention services through Continuum of Care programs. Program-level data on homeless service usage is reported as well. Aggregate HMIS data provides information about the size, characteristics, and needs of the homeless population at the local, state, and national levels. Although HMIS is not an HIV-specific data system, one of the client-level universal data elements it captures is “disabling condition,” which includes AIDS and AIDS-related conditions.

HUD requires the collection in HMIS of a minimum set of data elements from all individuals receiving homeless assistance and prevention services. These data are required to generate unduplicated estimates of the number and basic demographic characteristics of individuals accessing services and patterns of service use. These “universal data elements” include, among others, name, date of birth, race, ethnicity, gender (male, female; transgender male to female, female to male), presence of a disabling condition, residence prior to program entry, zip code of last permanent address, and housing status (HUD, 2010, pp. 40-63). Additional “program-specific” data elements are variously required from specified homeless assistance programs, including those funded through HOPWA. The program-specific data elements include the amounts and sources of income, if any, in the preceding 30 days; receipt of noncash benefits (e.g., Medicare, Medicaid, Supplemental Nutrition Assistance Program); and information on physical and developmental disability, chronic health conditions, HIV/AIDS, mental health, substance abuse, domestic violence, and destination upon program exit (HUD, 2010, pp. 64ff.). Optional program-specific data elements, not

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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required for APR reporting, include employment status, education, general health status, and pregnancy status (HUD, 2010, pp. 93ff.).

The data from HOPWA’s APR and CAPER and those captured in HMIS provide important information about access to housing and other supportive services for PLWHA, including an assessment of unmet housing needs for HOPWA-eligible households (i.e., those with income below 80 percent of the area median income and documented HIV/AIDS status) (HUD, 2011a). The unmet needs assessment is limited, however, to those individuals identified as being HOPWA-eligible and may not represent the full scope of need for housing assistance among PLWHA. In terms of access to other supportive services (e.g., nutrition or food, transportation), the data are limited to households receiving HOPWA-funded services and do not reflect need or access to services among other PLWHA.

The collection of longitudinal individual-level data in HMIS permits assessment of patterns of housing service usage and outcomes over time. In addition, a number of the client-level data elements captured may allow for linkage or cross-matching to additional information in other pertinent data systems (e.g., MSIS, CCW, Ryan White HIV/AIDS Program).

SIMILAR DATA COLLECTION EFFORTS

Several additional data collection efforts are under way that will provide useful information for assessing the impact of the NHAS and ACA on HIV care, including CDC’s Enhanced Comprehensive HIV Prevention Planning Project, HHS’s 12 Cities Project, and the Nationwide Health Information Network Exchange.

Enhanced Comprehensive HIV Prevention Planning Project

Launched in September 2010 in response to the NHAS, the ECHPP Project is a 3-year demonstration project funded by the CDC’s Division of HIV/AIDS Prevention. The program targets the 12 MSAs that have the highest AIDS prevalence, cumulatively accounting for 44 percent of cases in the United States (DHAP, 2011).34 Following the NHAS, the overarching goals of the project are to maximize the impact of HIV prevention strategies in these geographic areas, reduce the incidence of HIV infections, improve the quality of HIV care, and reduce HIV health disparities.

The 12 ECHPP grantees are evenly divided between state or territorial health departments and directly funded local health departments. During

_________________

34The 12 MSAs are Atlanta, Georgia; Baltimore, Maryland; Chicago, Illinois; Dallas, Texas; District of Columbia; Houston, Texas; Los Angeles, California; Miami, Florida; New York City; Philadelphia, Pennsylvania; San Juan, Puerto Rico; San Francisco, California.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

the first year of the project, each grantee was required to conduct a local situational analysis, taking account of available resources, epidemiologic profiles, priority areas, and cost and cost-effectiveness data for specific interventions and strategies. Based on these analyses, the grantees created a set of goals and strategies that would best aid in the accomplishment of NHAS goals. These enhanced prevention plans, which have been approved by CDC, include interventions and public health strategies designed to prevent new HIV infections and to promote HIV care and treatment. By the end of 2011, the jurisdictions had begun implementing their plans and had submitted funding applications for the second and third years of the project.

Although prevention of new infections is the primary emphasis of ECHPP, seven of its nine required prevention strategies for PLWHA address treatment concerns such as linkage to care, retention or reengagement in care, provision of ART consistent with current guidelines, adherence to antiretroviral medications, STI screening, prevention of perinatal transmission, and linkage to other medical and social services (DHAP, 2011). ECHPP has a comprehensive evaluation plan that incorporates process, outcome, and impact indicators to assess progress in these prevention and treatment areas that will be collected in the 12 MSAs, as well as supplemental data from a subset of the cities (Fisher and Hoyte, 2011).

12 Cities Project

Created by HHS to work in conjunction with CDC’s ECHPP initiative, the 12 Cities Project is a demonstration project designed to promote prevention and treatment of HIV in the 12 cities (MSAs) disproportionately affected by the epidemic through cross-agency collaboration and coordination with state and local health departments and other organizations (HHS, 2011b). Ultimately the lessons learned through the 12 Cities Project will help to improve HIV care in other jurisdictions. The project expands upon the foundation laid by ECHPP, engaging additional federal partners and increasing focus on HIV care and treatment. Whereas ECHPP’s emphasis is on local plans to improve prevention and care in the 12 jurisdictions, the 12 Cities Project emphasizes better coordination of services and funding of federal efforts to improve HIV prevention and care within the jurisdictions and the development of a common set of measures (indicators), in conjunction with streamlining reporting requirements, to evaluate the efforts with respect to the goals of the NHAS.

Motivated by the need to develop common metrics for tracking program outcomes for the 12 Cities Project, HHS undertook a broader effort to develop a streamlined set of cross-agency, core indicators that can be used to monitor the prevention, treatment, and care services of all federally

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

funded programs providing HIV/AIDS services. HHS identified the need for indicators in seven domains: HIV+ diagnosis, early HIV diagnosis, initial linkage to care, sustained engagement in care, initiation of ART, viral load suppression, and housing (Valdiserri and Forsyth, 2011; Personal communication, Andrew Forsyth, Department of Health and Human Services, January 24, 2012). The committee has recommended indicators in each of these areas. Although the jurisdictions included in the 12 Cities Project represent a large percentage of the U.S. population of PLWHA, use of a common set of core indicators across all federally funded HIV/AIDS programs nationwide will generate a more complete picture of HIV care in the United States.

Nationwide Health Information Network Exchange

Developed under the auspices of the Office of the National Coordinator for Health Information Technology, the Nationwide Health Information Network (NwHIN) Exchange is a public-private partnership designed to promote the exchange of health information from patient health records (ONC, 2011). Federal agencies participating in NwHIN Exchange include CDC, Department of Veterans Affairs, and Department of Defense. Nonfederal entities include KP, various hospitals, health information organizations, and state health information exchanges.

Health Care Cost Institute

Another type of data sharing partnership is the Health Care Cost Institute (HCCI), launched in September 2011. The HCCI is an independent, nonprofit entity whose goal is to create a comprehensive database of health care cost and service utilization data to promote and support research on the drivers of escalating health care costs and utilization. HCCI will make available de-identified claims records from four of the largest private health insurers in the United States (Aetna, Humana, Kaiser Permanente, United-Healthcare), as well as Medicare Advantage data from each of those plans (HCCI, 2011). Currently the HCCI database contains more than 5 billion medical claim records from over 5,000 hospitals and 1 million service providers from 2000 through the present (Merrill, 2011). Eventually HHCI plans to add data from additional private insurers, as well as public payers such as Medicaid (Merrill, 2011). This type of cooperative arrangement among private insurers and between the private insurance industry and the public serves as another example of the type of data sharing enterprise that would help to expand the pool of data available to estimate the indicators beyond those available from any individual data system.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

CONCLUSIONS AND RECOMMENDATIONS

•  Currently data are being collected by a number of public and private data systems, some specific to HIV and others not, each of which has limitations. These data systems are collecting relevant information that can serve as a collective platform for evaluating access to continuous and high-quality care in all populations of PLWHA. The committee identified 12 data systems in particular that collect data of use for estimating the core indicators to monitor progress toward meeting the goals of the NHAS and ACA:

National HIV Surveillance System

Medical Monitoring Project

Ryan White Services Report

Ryan White AIDS Drug Assistance Program Reports

Medicaid Statistical Information System

Chronic Condition Data Warehouse

North American AIDS Cohort Collaboration on Research and Design

CFAR Network of Integrated Clinical Systems

HIV Research Network

Clinical Case Registry: HIV

Kaiser Permanente

National Vital Statistics System

    Two additional data systems provide information of use in tracking the impact of the initiatives on care for two small but important subpopulations of HIV-infected individuals (AI/ANs; federal prisoners), and a third provides information relevant to housing assistance and other supportive services for PLWHA:

Resource and Patient Management System

Bureau of Prisons Electronic Medical Record

Housing Opportunities for Persons with AIDS

•  The committee’s review of federal data systems relevant to HIV care showed they capture a wealth of data that can be used to

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

estimate the indicators identified by the committee for monitoring the impact of the NHAS and the ACA in improving HIV/AIDS care in the United States. Each data system has limitations, however. Few contain all of the data elements needed to estimate the indicators, especially those pertaining to mental health, substance abuse, and supportive services. In addition, most of the data systems are not fully representative of the population of PLWHA in the United States. In many cases (e.g., Ryan White HIV/AIDS Program, MSIS, CCW, VHA), the population represented in the data system is defined by program eligibility and cannot be expanded. Similarly, the purposes for which the data systems were designed preclude expansion of the data elements they collect to include all of those needed to estimate all of the indicators identified by the committee. Furthermore, such expansion would entail significant increases in cost and reporting burden. The committee concluded, however, that more modest changes in individual data systems could improve the usefulness of their data for tracking changes in HIV care and access to supportive services for people living with HIV. For example, a given data system might add one or more data elements or modify an existing data element to allow the system to provide data for estimating a subgroup of the indicators identified by the committee, such as those pertaining to supportive services (housing, food security, transportation), or to simplify identification of data representing HIV-infected individuals (e.g., flagging HIV/AIDS as a chronic condition in the CCW). In cases where the population represented in a data system is not constrained by the program it serves (e.g., MMP), steps might be taken either to make the population more representative of the national population of people living with HIV or to include groups (e.g., homeless) who are less apt to be represented in other data systems.

      Recommendation 3-1. The Department of Health and Human Services, the Department of Veterans Affairs, the Department of Housing and Urban Development, and other relevant federal agencies should review and, to the extent practicable, modify the federal data systems identified by the committee to better enable them to be used for monitoring progress toward achieving the goals of the National HIV/AIDS Strategy.

•  Uniform longitudinal reporting of CD4 and viral load test dates and results from all jurisdictions and data on the initiation and ongoing prescription or dispensing of antiretroviral therapy would facilitate the use of data from the NHSS to assess all of the core

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

indicators for clinical HIV care identified by the committee. In addition, collection of data on sexual orientation, sources of coverage for medical treatment, and maintaining current geographic area of residence for individuals in the NHSS would facilitate use of national surveillance system data for evaluation of indicators for specific subpopulations identified in the NHAS.

Recommendation 3-2. The Centers for Disease Control and Prevention should take steps to enhance the National HIV Surveillance System including

  • issuing guidelines or criteria for National HIV Surveillance System reporting to include all CD4 and viral load test results
  • capturing longitudinal data pertaining to the initiation and ongoing prescription or dispensing of antiretroviral therapy for individuals diagnosed with HIV (e.g., through pharmacy-based reporting)
  • obtaining information on sexual orientation and sources of coverage for medical treatment (including, but not limited to, Medicaid, Medicare, Ryan White HIV/AIDS Program, other public funding, private insurance or health maintenance organization, no coverage) and obtaining and employing current geographic marker of residence (e.g., current address, zip code, partial zip code, census block) for individuals in the National HIV Surveillance System

•  The committee’s review of data systems relevant to HIV care showed that clinically based EHR systems (e.g., VHA, KP, IHS, BOP) capture all, or most, of the data elements needed to estimate the clinical HIV care indicators identified by the committee. They also generally capture at least some of the information needed to estimate the indicators pertaining to mental health and substance abuse, but they do not routinely capture data needed to estimate the indicators pertaining to supportive services. Another limitation of provider-based systems is that individually they represent only one segment of the population of PLWHA in the United States (e.g., veterans, KP enrollees, AI/ANs, federal prisoners). Other data systems represent larger proportions of PLWHA nationally (e.g., NHSS, MSIS) and may contain information on mental health, substance abuse, and supportive services (e.g., Ryan White HIV/AIDS Program, MSIS), but they contain limited or no clinical data. The NwHIN Exchange is an example of a partnership between public

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

and private entities to exchange health information for a variety of purposes. It could serve as a model for or a foundation upon which to build a broader data sharing partnership among public and private data systems both to permit better estimation of the indicators identified by the committee and to return information to private health care systems and providers for the purpose of improving health care for individuals with HIV. Building upon existing data sharing partnerships would help to reduce the costs associated with implementation of such partnerships for the exchange of information relevant to the provision of HIV care.

      Recommendation 3-3. The Department of Health and Human Services, the Department of Veterans Affairs, the Indian Health Service, the Federal Bureau of Prisons, and other relevant federal agencies should use existing data from private data systems, including data from electronic health records, to monitor the impact of the National HIV/AIDS Strategy and the Patient Protection and Affordable Care Act on improving HIV care. Federal agencies also should share data pertaining to HIV care with private health care systems and providers to improve the quality of care for individuals with HIV. Methods might include the development of a data sharing partnership between public and private data systems that include data pertaining to HIV care.

 

REFERENCES

Blair, J. M., A. D. McNaghten, E. L. Frazier, J. Skarbinski, P. Huang, and J. D. Heffelfinger. 2011. Clinical and behavioral characteristics of adults receiving medical care for HIV infection—Medical Monitoring Project, United States, 2007. MMWR Surveillance Summaries 60(11):1-20.

BOP (Federal Bureau of Prisons). 2011. Weekly Population Report. http://www.bop.gov/locations/weekly_report.jsp (accessed December 22, 2011).

Bozzette, S. A., S. H. Berry, N. Duan, M. R. Frankel, A. A. Leibowitz, D. Lefkowitz, C. A. Emmons, J. W. Senterfitt, M. L. Berk, S. C. Morton, and M. F. Shapiro. 1998. The care of HIV-infected adults in the United States. HIV Cost and Services Utilization Study Consortium. New England Journal of Medicine 339(26):1897-1904.

Carr, A. C., A. Ghosh, and R. J. Ancill. 1983. Can a computer take a psychiatric history? Psychological Medicine 13(1):151-158.

CCW (Chronic Condition Data Warehouse). 2011a. Chronic Condition Data Warehouse. http://www.ccwdata.org/index.htm (accessed March 6, 2012).

CCW. 2011b. Chronic Condition Data Warehouse User Guide. Version 1.8. http://www.ccwdata.org/cs/groups/public/documents/document/ccw_userguide.pdf (accessed December 21, 2011).

CCW. 2011c. Medicaid Analytic Extract Files (MAX) User Guide. Version 1.1. http://www.ccwdata.org/cs/groups/public/documents/document/ccw_max_user_guide.pdf (accessed February 2, 2012).

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

CDC (Centers for Disease Control and Prevention). 2007. Cases of HIV infection and AIDS in the United States and dependent areas, 2005. HIV/AIDS Surveillance Report 17, revised edition, June. http://www.cdc.gov/hiv/surveillance/resources/reports/2005report/#3 (accessed January 18, 2012).

CDC. 2009. Medical Monitoring Project 2009 Protocol. Atlanta, GA: Centers for Disease Control and Prevention. http://www.cdc.gov/hiv/topics/treatment/mmp/pdf/MMP2009Protocol.pdf (accessed October 21, 2011).

CDC. 2010. Summary of Changes to the National HIV Surveillance Report. National Center for HIV/AIDS, Hepatitis, STD, and TB Prevention. http://www.cdc.gov/hiv/topics/surveillance/resources/factsheets/pdf/summary_changes.pdf (accessed October 20, 2011).

CDC. 2011a. HIV surveillance—United States, 1981-2008. Morbidity and Mortality Weekly Report 60(21):689-693.

CDC. 2011b. Medical Monitoring Project (MMP). http://www.cdc.gov/hiv/topics/treatment/mmp/index.htm (accessed October 21, 2011).

CDC. 2011c. U.S. Standard Certificate of Death. http://www.cdc.gov/nchs/data/dvs/DEATH11-03final-ACC.pdf (accessed November 27, 2011).

CDC. 2011d. Vital signs: HIV prevention through care and treatment—United States. Morbidity and Mortality Weekly Report 60(47):1618-1623.

CDC. 2012. Diagnoses of HIV infection and AIDS in the United States and dependent areas, 2010. HIV Surveillance Report. Volume 22. http://www.cdc.gov/hiv/surveillance/resources/reports/2010report/index.htm (accessed March 21, 2012).

Chartier, K., and R. Caetano. 2010. Ethnicity and health disparities in alcohol research. Alcohol Research & Health 33(1-2):152-160.

CHCS (Center for Health Care Strategies, Inc.). 2010. Integrating Medicare and Medicaid Data to Support Improved Care for Dual Eligibles. http://www.chcs.org/usr_doc/Integrating_Medicare_and_Medicaid_Data_for_Duals.pdf (accessed January 24, 2012).

CMS (Centers for Medicare and Medicaid Services). 2010. Medicaid and CHIP Statistical Information System (MSIS): File Specifications and Data Dictionary. Release 3.1. http://www.cms.gov/MSIS/Downloads/msisdd2010.pdf (accessed December 21, 2011).

CMS. 2011a. Medicaid Analytic Extract (MAX) General Information. http://www.cms.gov/MedicaidDataSourcesGenInfo/07_MAXGeneralInformation.asp (accessed October 26, 2011).

CMS. 2011b. Medicaid Statistical Information System (MSIS) State Summary Datamart. http://msis.cms.hhs.gov/(accessed December 21, 2011).

CMS. 2011c. Overview: Medicaid Statistical Information System (MSIS). http://www.cms.gov/msis/ (accessed January 24, 2012).

CMS. 2011d. What Are the Types of Records That Are Contained in Each of the Medicaid Analytic Extract (MAX) Files? How Do the Records in These Files Differ from the Records in the Medicaid Statistical Information System (MSIS) Files? http://questions.cms.hhs.gov/app/answers/detail/a_id/9230/kw/Medicaid%20Analytic%20Extract (accessed December 22, 2011).

CNICS (CFAR Network of Integrated Clinical Systems). 2011. CNICS. http://www.uab.edu/cnics/ (accessed December 21, 2011).

Crystal, S., A. Akincigil, S. Bilder, and J. T. Walkup. 2007. Studying prescription drug use and outcomes with Medicaid claims data: Strengths, limitations, and strategies. Medical Care 45(10 Suppl 2):S58-65.

Cullen, T. 2006. HIV Management System: Software Application. Indian Health Service, Office of Information Technology. http://healthit.hhs.gov/portal/server.pt/document/954931/2006cullen_051111comp_pdf (accessed December 22, 2011).

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

DHAP (Division of HIV/AIDS Prevention). 2011. Enhanced Comprehensive HIV Prevention Planning (ECHPP) Project. http://www.cdc.gov/hiv/nhas/echpp/pdf/echpp_factsheet.pdf (accessed December 27, 2011).

DOJ (Department of Justice). 2011. Federal Prison System. FY 2012 Performance Budget. http://www.justice.gov/jmd/2012justification/pdf/fy12-bop-se-justification.pdf (accessed December 22, 2011).

Fisher, H. H., and T. Hoyte. 2011. Using HIV Surveillance Data to Inform the ECHPP Evaluation. PowerPoint presentation at the 2011 National HIV Prevention Conference, August 14-17, Atlanta, GA. http://www.slideshare.net/CDCNPIN/using-hiv-surveillance-data-to-inform-the-echpp-evaluation (accessed December 22, 2011).

Gange, S. J., M. M. Kitahata, M. S. Saag, D. R. Bangsberg, R. J. Bosch, J. T. Brooks, L. Calzavara, S. G. Deeks, J. J. Eron, K. A. Gebo, M. J. Gill, D. W. Haas, R. S. Hogg, M. A. Horberg, L. P. Jacobson, A. C. Justice, G. D. Kirk, M. B. Klein, J. N. Martin, R. G. McKaig, B. Rodriguez, S. B. Rourke, T. R. Sterling, A. M. Freeman, and R. D. Moorey. 2007. Cohort Profile: The North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD). International Journal of Epidemiology 36:294-301.

GAO (U.S. Government Accountability Office). 2007. Indian Health Service: HIV/AIDS Prevention and Treatment Services for American Indians and Alaskan Natives: Report to Congressional Requesters. http://www.gao.gov/new.items/d0890.pdf (accessed December 22, 2011).

Greist, J. H., T. P. Laughren, D. H. Gustafson, F. F. Stauss, G. L. Rowse, and J. A. Chiles. 1973. A computer interview for suicide-risk prediction. American Journal of Psychiatry 130(12):1327-1332.

Hall, H. I., K. McDavid, Q. Ling, and A. Sloggett. 2005. Survival after diagnosis of AIDS, United States. Annals of Epidemiology 15(8):652.

Hall, H. I., R. Song, J. E. Gerstle 3rd, and L. M. Lee, HIV/AIDS Reporting System Evaluation Group. 2006. Assessing the completeness of reporting of human immunodeficiency virus diagnoses in 2002-2003: Capture-recapture methods. American Journal of Epidemiology 164(4):391-397.

HCCI (Health Care Cost Institute). 2011. About HCCI. http://healthcostinstitute.org/about (accessed November 27, 2011).

HHS (U.S. Department of Health and Human Services). 2011a. Statement by Mary K. Wakefield, Administrator, Health Resources and Services Administration, before the Committee on Energy, the Subcommittee on Health, United States House of Representatives: Health Resources and Services Administration on Ryan White AIDS Reauthorization Bill. http://www.hhs.gov/asl/testify/2009/09/t20090909a.html (accessed August 9, 2011).

HHS. 2011b. 12 Cities Project. http://blog.aids.gov/downloads/NHAS-HHS-12.pdf (accessed January 24, 2012).

HIVRN (HIV Research Network). 2011. HIVRN: Contacts. http://cds.johnshopkins.edu/hivrn/index.cfm?do=sens.content&page=contacts.html (accessed December 21, 2011).

HOPWA (Housing Opportunities for Persons with AIDS). 2011a. Annual Progress Report (APR): Measuring Performance Outcomes. http://www.hudhre.info/documents/APR_HOPWA.docx (accessed December 1, 2011).

HOPWA. 2011b. Consolidated Annual Performance Evaluation Report (CAPER): Measuring Performance Outcomes. http://portal.hud.gov/hudportal/documents/huddoc?id=hopwa_caper_10312014.doc (accessed December 8, 2011).

HRSA (Health Resources and Services Administration). 2010. Going the Distance: The Ryan White HIV/AIDS Program. http://hab.hrsa.gov/data/files/2010progressrpt.pdf (accessed December 14, 2011).

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

HRSA. 2011. 2010 Annual Ryan White HIV/AIDS Program Services Report (RSR) Instruction. U.S. Department of Health and Human Services. http://hab.hrsa.gov/manageyourgrant/files/rsrinstructionmanual2010.pdf (accessed August 9, 2011).

HUD (U.S. Department of Housing and Urban Development). 2010. Homeless Management Information System (HMIS) Data Standards, Revised Notice. Office of Community Planning and Development, March. http://www.hudhre.info/documents/FinalHMISDataStandards_March2010.pdf (accessed December 9, 2011).

HUD. 2011a. Administering HOPWA Housing Assistance: Determining Beneficiary Eligibility. Office of HIV/AIDS Housing. http://portal.hud.gov/hudportal/documents/huddoc?id=DOC_12082.pdf (accessed December 9, 2011).

HUD. 2011b. HIV/AIDS Housing. http://portal.hud.gov/hudportal/HUD?src=/program_offices/comm_planning/aidshousing (accessed October 26, 2011).

IHS (Indian Health Service). 2008. Diabetes in American Indians and Alaska Natives. Fact Sheet. Department of Health and Human Services. http://www.ihs.gov/MedicalPrograms/Diabetes/index.cfm?module=resourcesFactSheets_AIANs08 (accessed August 25, 2011). IHS. 2011a. iCare. http://www.ihs.gov/cio/ca/icare/(accessed December 22, 2011).

IHS. 2011b. IHS Clinical Reporting System (BGP): National GPRA Developmental Report Performance Measure List and Definitions. Version 12.0, December. Albuquerque, NM: Office of Information Technology, Division of Information Resource Management. http://www.ihs.gov/CIO/CRS/documents/crsv12/GPRA%20Dev%20Measures%20V12.pdf (accessed January 25, 2012).

IHS. 2011c. IHS Clinical Reporting System (BGP): Select Measures (Local) Report Performance Measure List and Definitions. Version 12.0, December. Albuquerque, NM: Office of Information Technology, Division of Information Resource Management. http://www.ihs.gov/cio/crs/documents/crsv12/SelectedMeasuresV12.pdf (accessed January 25, 2012).

IHS. 2011d. The IHS HIV/AIDS Program: Frequently Asked Questions. http://www.ihs.gov/medicalprograms/hivaids/index.cfm?module=faq (accessed December 22, 2011).

IHS. 2012. IHS Fact Sheets: IHS Year 2012 Profile. http://www.ihs.gov/PublicAffairs/IHSBrochure/Profile.asp (accessed February 29, 2012).

IOM (Institute of Medicine). 2004. Measuring What Matters: Allocation, Planning and Quality Assessment for the Ryan White CARE Act. Washington, DC: The National Academies Press.

IOM. 2011. HIV Screening and Access to Care: Health Care System Capacity for Increased HIV Testing and Provision of Care. Washington, DC: The National Academies Press.

Kates, J. 2011. Medicaid and HIV: A National Analysis. Washington, DC: Henry J. Kaiser Family Foundation. http://www.kff.org/hivaids/upload/8218.pdf (accessed January 11, 2012).

KFF (Kaiser Family Foundation). 2009a. Medicare and HIV. HIV/AIDS Policy Fact Sheet. February. http://www.kff.org/hivaids/upload/7171_04.pdf (accessed December 19, 2011).

KFF. 2009b. The Ryan White Program. HIV/AIDS Policy Fact Sheet. February. http://www.kff.org/hivaids/upload/7582_05.pdf (accessed December 19, 2011).

KFF. 2011a. Medicaid and CHIP—Kaiser State Health Facts. http://www.statehealthfacts.org/comparecat.jsp?cat=4 (accessed December 14, 2011).

KFF. 2011b. U.S. federal funding for HIV/AIDS: The President’s FY 2012 budget request. HIV/AIDS Policy Fact Sheet. October. http://www.kff.org/hivaids/upload/7029-07.pdf (accessed December 21, 2011).

Kitahata, M. 2011. IOM Review of Data Systems Monitoring HIV Care in the U.S.: CNICS and NA-ACCORD. PowerPoint presentation before the committee, Washington, DC, April 28.

Kobak, K. A., J. H. Greist, J. W. Jefferson, and D. J. Katzelnick. 1996. Computer-administered clinical rating scales: A review. Psychopharmacology 127(4):291-301.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Kochanek, K. D., J. Xu, S. L. Murphy, A. M. Miniño, and H. Kung. 2011. Deaths: Preliminary data for 2009. National Vital Statistics Reports 59(4):1-51.

Koroukian, S. M., G. S. Cooper, and A. A. Rimm. 2003. Ability of Medicaid claims data to identify incident cases of breast cancer in the Ohio Medicaid population. Health Services Research 38(3):947-960.

KP (Kaiser Permanente). 2009. VA and Kaiser Permanente Invite Veterans to Participate in Health Record Pilot Program. Press release, November 25. http://xnet.kp.org/newscenter/pressreleases/nat/2009/112509vapilot.html (accessed December 21, 2011).

KP. 2011. Our Plans. http://www.kpchoicesolution.com/HealthPlans.aspx (accessed December 21, 2011).

Lawrence, S. T., J. H. Willig, H. M. Crane, J. Ye, I. Aban, W. Lober, C. R. Nevin, D. S. Batey, M. J. Mugavero, C. McCullumsmith, C. Wright, M. Kitahata, J. L. Raper, M. S. Saag, and J. E. Schumacher. 2010. Routine, self-administered, touch-screen, computer-based suicidal ideation assessment linked to automated response team notification in an HIV primary care setting. Clinical Infectious Diseases 50(8):1165-1173.

Lucas, R. W., P. J. Mullin, C. B. Luna, and D. C. McInroy. 1977. Psychiatrists and a computer as interrogators of patients with alcohol-related illnesses: A comparison. British Journal of Psychiatry 131(2):160-167.

Martin, E. G., and C. L. Barry. 2011. The adoption of mental health drugs on state AIDS Drug Assistance Program formularies. American Journal of Public Health 101(6):1103-1109.

Martin, E. G., and P. S. Keenan. 2011. Sticky dollars: Inertia in the evolution of federal allocations for HIV care through the Ryan White Program. Publius: The Journal of Federalism 41(1):101-125.

Maruschak, L. M. 2010. HIV in Prisons, 2007-2008. U.S. Department of Justice. http://bjs.ojp.usdoj.gov/content/pub/pdf/hivp08.pdf (accessed December 6, 2011).

Massachusetts Department of Public Health. 2012. Letter to clinical laboratories. (February 28).

McCoy, S. I., B. Jones, P. A. Leone, S. Napravnik, E. B. Quinlivan, J. J. Eron, and W. C. Miller.2010. Variability of the date of HIV diagnosis: A comparison of self-report, medical record, and HIV/AIDS surveillance data. Annals of Epidemiology 20(10):734-742.

Merrill, M. 2011. Healthcare Cost Institute to provide data from four private sector insurers. Health IT News. http://healthcareitnews.com/news/healthcare-cost-institute-provide-data-four-private-sector-insurers (accessed November 27, 2011).

Metzger, D. S., B. Koblin, C. Turner, H. Navaline, F. Valenti, S. Holte, M. Gross, A. Sheon, H. Miller, P. Cooley, and G. R. Seage III, for the HIVNET Vaccine Preparedness Study Protocol Team. 2000. Randomized controlled trial of audio computer-assisted self-interviewing: Utility and acceptability in longitudinal studies. American Journal of Epidemiology 152(2): 99-106.

NA-ACCORD (North American AIDS Cohort Collaboration on Research and Design). 2011. North American AIDS Cohort Collaboration on Research and Design: Cohorts. http://statepiaps.jhsph.edu/naaccord/Cohorts/index.html (accessed December 21, 2011).

NASTAD (National Alliance of State and Territorial AIDS Directors). 2011. National ADAP Monitoring Project Annual Report. http://www.nastad.org/Docs/020035_2011%20NASTAD%20National%20ADAP%20Monitoring%20Project%20Annual%20Report.pdf (accessed December 6, 2011).

NVSS (National Vital Statistics System). 2011a. National Vital Statistics System. http://www.cdc.gov/nchs/nvss.htm (accessed December 21, 2011).

NVSS. 2011b. National Vital Statistics System: Mortality Data. http://www.cdc.gov/nchs/deaths.htm (accessed December 21, 2011).

NVSS. 2011c. Writing Cause-of-Death Statements. http://www.cdc.gov/nchs/nvss/writing_cod_statements.htm (accessed November 27, 2011).

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

NwHIN (Nationwide Health Information Network) Exchange. 2011. Nationwide Health Information Network Exchange. http://healthit.hhs.gov/portal/server.pt?open=512&objID=1407&parentname=CommunityPage&parentid=8&mode=2&in_hi_userid=11113&cached=true (accessed December 21, 2011).

OMB (Office of Management and Budget). 1977. Statistical Policy Directive No. 15, Race and Ethnic Standards for Federal Statistics and Administrative Reporting. http://wonder.cdc.gov/wonder/help/populations/bridged-race/Directive15.html (accessed August 11, 2011).

OMB. 1997a. Recommendations from the Interagency Committee for the Review of the Racial and Ethnic Standards to the Office of Management and Budget concerning changes to the standards for the classification of federal data on race and ethnicity. Federal Register (3110-01):36873-36946.

OMB. 1997b. Revisions to the standards for the classification of federal data on race and ethnicity. Federal Register 62:58781-58790.

ONAP (Office of National AIDS Policy). 2010. National HIV/AIDS Strategy for the United States. http://www.whitehouse.gov/sites/default/files/uploads/NHAS.pdf (accessed July 14, 2011).

ONC (Office of the National Coordinator for Health Information Technology). 2011. Nationwide Health Information Network Exchange. http://healthit.hhs.gov/portal/server.pt/community/healthit_hhs_gov__nhin_exchange/1407 (accessed November 27, 2011).

Overhage, J. M., S. Grannis, and C. J. McDonald. 2008. A comparison of the completeness and timeliness of automated electronic laboratory reporting and spontaneous reporting of notifiable conditions. American Journal of Public Health 98(2):344-350.

Petrie, K., and W. Abell. 1994. Responses of parasuicides to a computerized interview. Computers in Human Behavior 10(4):415-418.

Price, L. G. 2011. The Federal Bureau of Prisons Electronic Medical Record (BEMR): From Sojourn to Odyssey. PowerPoint presentation at the 2011 USPHS Scientific and Training Symposium/New Orleans, Louisiana. http://www.phscofevents.org/agenda/ag_glanceDetail.cfm?sg_id=58 (accessed December 22, 2011).

Rawlings, M. K., and D. P. Hopson. 2009. The impact of HIV policies and politics on communities of color. In HIV/AIDS in U.S. Communities of Color, edited by V. Stone, B. Ojikutu, M. K. Rawlings, and K. Y. Smith. Dordrecht: Springer. Pp. 261-282.

ResDAC (Research Data Assistance Center). 2011a. Availability of Research Identifiable Data, Limited Data Sets, and Non Identifiable Files. http://www.resdac.org/tools/TBs/TN_015_CMS%20Data%20Availability_508%20.pdf (accessed December 22, 2011).

ResDAC. 2011b. Medicaid FAQs Draft. http://www.resdac.org/medicaid/FAQs-draft-08172006.doc (accessed October 31, 2011).

Rich, J. D., D. A. Wohl, C. G. Beckwith, A. C. Spaulding, N. E. Lepp, J. Baillargeon, S. Gardner, A. Avery, F. L. Altice, and S. Springer, Centers for AIDS Research—Collaboration on HIV in Corrections (CFAR-CHIC) Working Group. 2011. HIV-related research in correctional populations: Now is the time. Current HIV/AIDS Reports 8(4):288-296.

Skinner, H. A., and B. A. Allen. 1983. Does the computer make a difference? Computerized versus face-to-face versus self-report assessment of alcohol, drug, and tobacco use. Journal of Consulting and Clinical Psychology 51(2):267-275.

Smith, V. K., K. Gifford, S. Kramer, J. Dalton, P. MacTaggart, and M. Lim Warner. 2008. State E-Health Activities in 2007: Findings from a State Survey. http://www.commonwealthfund.org/usr_doc/1104_Smith_state_e-hlt_activities_2007_findings_st.pdf (accessed August 31, 2011).

VA (Department of Veterans Affairs). 2011. Center for Quality Management in Public Health: HIV Infected Veterans in VHA Care by State—2010. http://www.publichealth.va.gov/quality/reports/hiv-in-care-by-state-2010.asp (accessed December 21, 2011).

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Valdiserri, R., and A. Forsyth. 2011. DHHS/OHAP Consultation on HIV/AIDS Core Indicators, Data Streamlining, and Federal Reporting Requirements. Washington, DC, September 19.

Waruru, A. K., R. Nduti, and T. Tylleskär. 2005. Audio computer-assisted self-interviewing (ACASI) may avert socially desirable responses about infant feeding in the context of HIV. BMC Medical Informatics and Decision Making 5(August):24 (7 pages).

Willig, J. 2011. Data at the HIV-Research and Informatics Service Center (RISC). PowerPoint presentation before the committee, San Francisco, CA, July 8.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

APPENDIX TABLE 3-1 follows on next page

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

APPENDIX TABLE 3-1 Summary of Data Systems for Monitoring HIV Care Identified by the Committee


Design Population Covered Source of Data Number How Representative

National HIV Surveillance System (Centers for Disease Control and Prevention)

• Public health surveillance, state-mediated mandatory reporting by all • All persons diagnosed with HIV/ AIDS • Clinician reports of diagnosis • 808,090 (803,771)a —2009 data for 46 states and 5 U.S. dependent areas with confidential name-based reporting • Wide coverage of diagnosed PLWHA jurisdictions

• Longitudinal from time of diagnosis

• Lab reports of CD4 counts and viral load

• Includes PLWHA out of care

• State health department reporting


aEstimated number following statistical adjustment for reporting delays and missing risk-factor information, but not for incomplete reporting (http://www.cdc.gov/hiv/surveillance/resources/reports/2010report/pdf/2010_HIV_Surveillance_Report_vol_22.pdf#Page=52, accessed March 21, 2012).

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Strengths Limitations Potential Enhancements ACA Implications




• Population-based census

• Includes individuals not in care

• Not limited to one type of payer

• Definitions of variables and reporting methods standardized

• Trend data routinely available

• Many highest priority indicators can be calculated

• Can be used to monitor disparities re: gender, race/ ethnicity, region

• Possible to link with other data systems maintained at local level (e.g., Ryan White Services Report; Homeless Management Information System)

• Clinical data elements limited to CD4 and viral load tests, with optional fields for ART and pregnancy status

• Not all jurisdictions report lab results longitudinally

• Inability to track individuals across reporting areas

• Inaccurate/incomplete reporting

• Not yet complete for jurisdictions without mature name-based reporting

• Addition of payer information

• Addition of employment status, income, sexual orientation

• Addition of ART status (whether receiving)

• Work with states to extend reporting of all CD4 and viral load lab results to all jurisdictions

• Number may increase and become more comprehensive as more individuals with HIV/AIDS are identified with increased access to health care coverage


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Design Population Covered Source of Data Number How Representative

Medical Monitoring Project (Centers for Disease Control and Prevention)

• Multistage probability proportional to size sampling design • Adults (≥18 years) diagnosed with HIV/ AIDS and receiving outpatient care • Self-reported behavioral and selected clinical data • 3,643 HIV-infected adults (2007 cycle) • Repeated cross-sectional probability samples of adult PLWHA receiving outpatient medical care in United States and Puerto Rico

• Repeated cross-sectional probability sample

• Medical record abstraction

• 4,217 HIV-infected adults (2009 cycle)b


bThe 2009 collection cycle data were weighted to estimate nationally representative percentages of HIV-infected adults receiving medical care in the United States.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Strengths Limitations Potential Enhancements ACA Implications




• Most indicators can be calculated

• Includes data on supportive services

• 2009 data cycle weighted to estimate nationally representative percentages of adult PLWHA in care

• Not limited to patients receiving care through a specific payer

• Low individual participation rate in 2007 cycle

• 2007 data unweighted

• Possibility of social desirability response bias for in-person interviews

• Some clinical information (e.g., date of HIV diagnosis and date of first entry into care) is self-reported

• Stratification by certain characteristics produced numbers too small for reliable interpretation

• Only includes individuals who are in care

• Take steps to improve participation rates and make sample more nationally representative particularly among hard to reach populations such as homeless

• Create a mechanism to allow supplemental questions to be added as needed to capture salient data (e.g., with specific ACA implementation issues and how they might affect patients)

• Sample may be expected to reflect greater number of PLWHA not previously in care, as number of persons in care increases


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Design Population Covered Source of Data Number How Representative

Ryan White Services Report (Health Resources and Services Administration)

• HRSA/HAB mandatory reporting for Ryan White HIV/AIDS Program grantees and contracted service providers • HIV-infected individuals receiving at least one Ryan White service • Ryan White grantees and contracted service providers • >500,000 HIV-infected individuals

• Representative of clients receiving Ryan White funded services

• Not representative of national population of PLWHA in the United States

• Grantee Report: summary of RW' providers in the jurisdiction and services they offer

• Service Provider Report: basic information about the organization; lists service provider contracts for reporting period
• Client Report: client-level demographic information; HIV clinical information; HIV medical, health care, and support services received

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Strengths Limitations Potential Enhancements ACA Implications




• Most indicators (or a proxy) can be calculated • Grantees/providers are not required to report client service data for services not paid for by the Ryan White HIV/AIDS Program (may result in client-level data gaps) [Full clinical data are reported regardless of funding source] • Report all client service data regardless of funding source • Anticipated shift in clientele and services

• Includes data on supportive services, such as need for and use of housing, food, transportation services for people served by Ryan White HIV/AIDS Program

• Difficult to compare data across jurisdictions due to interstate variation in programs

• Reduced dependency on program to meet health service needs

• Grantee data can be used to monitor changes at service system level

• Redirection of funds to other vital services (e.g., housing, case management)


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Design Population Covered Source of Data Number How Representative

Ryan White AIDS Drug Assistance Program (ADAP) Reports (Health Resources and Services Administration)

ADAP Quarterly Report

• HRSA/HAB mandatory reporting for ADAP grantees and contracted entities • Aggregate data on ADAP clients enrolled/ served • ADAP grantees and contracted entities such as Pharmacy Benefits Management organizations • 213,764 ADAP clients enrolled (FY2009) • ADAP clients are HIV-positive, low income, and uninsured or underinsured
• ADAP Quarterly Data Report (aggregate data) • 190,963 ADAP clients served (FY2009)

ADAP Data Report (NOTE: First data collection period is April 1-September 30, 2012)

• Proposed HRSA/HAB mandatory reporting for ADAP grantees and contracted enlities • Client-level data on ADAP clients enrolled/ served (proposed) • ADAP grantees and contracted entities such as Pharmacy Benefits Management organizations • 213,764 ADAP clients enrolled (FY2009) • ADAP clients are HIV-infected, low income, and uninsured or underinsured

• 190,963 ADAP clients served (FY2009)

• A IMF Data Report (proposed) (client-level data)

• Demographic variables may be self-reported
• Clinical data must be from lab report, clinical documentation, or HIV surveillance program

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Strengths Limitations Potential Enhancements ACA Implications





• Data are aggregate
• Contains only limited data, mostly demographic
• Scheduled to be replaced by ADAP Data Report beginning with April 1-September 30, 2012, collection period


• Client-level data • Provides information only on medications that are fully funded by ADAP • Capture dispensing information for all ADAP formulary drugs regardless of funding source

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Design Population Covered Source of Data Number How Representative

Medicaid Statistical Information System (Centers for Medicare & Medicaid Services)

• Health care claims and eligibility • HIV-diagnosed individuals enrolled in Medicaid • Claims and eligibility data reported by states • 212,892 HIV-infected individuals (FY2007) • Representative of PLWHA enrolled in Medicaid (estimated 47 percent of PLWHA in care)
• Eligible file • Enrollees most likely to be black males over the age of 19
• Inpatient claims • 74 percent qualify for Medicaid as disabled (therefore not currently representative of non-disabled population of PLWHA)

• Long-term care claims

• Other claims
• Prescription drug claims

  Claim types:
• Fee-for-service
• Capitated payments
• Encounter claims
• Service-tracking claims (some states)

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Strengths Limitations Potential Enhancements ACA Implications




• Represents largest single source of care coverage for PLWHA: Medicaid enrollees account for 47 percent of PLWHA estimated to be in regular care • Utilization data only: No clinical outcome data • Anticipated increase in enrollment with increased eligibility provisions in ACA: magnitude likely to vary greatly across states

• No data on housing, food, transportation services

• Challenging to identify HIV-positive Medicaid recipients
Incomplete data on services for beneficiaries in managed care
• Diagnostic and service information dependent on codes entered on claims potentially resulting in incomplete data
• Variations in Medicaid eligibility resulting in enrollment lapses

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Design Population Covered Source of Data Number How Representative

Chronic Condition Data Warehouse (Centers for Medicare & Medicaid Services)

• Health care claims • HIV-diagnosed individuals enrolled in Medicare • Claims data submitted by health care providers • Approximately 100,000 HIV-infected individuals • Approximately 20 percent of PLWHA estimated to be receiving care in the United States
• PLWHA who are disabled or age 65 or older
• 29 percent of HIV-infected Medicaid enrollees are dually eligible for Medicare
Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Strengths Limitations Potential Enhancements ACA Implications




• Represents approximately 20 percent of PLWHA in care • Primarily fee-forservice utilization data • Designate HIV/AIDS as one of the predefined chronic condition cohorts • Potentially more claims for Medicare Part D
• Number expected to increase with aging population of PLWHA • Limited data on services for beneficiaries in managed care • Eventual elimination of Part D “donut hole”

• Limited/no clinical outcome data or data on supportive services

• May provide better information on drug coverage than other systems (with Part D enrollees)

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Design Population Covered Source of Data Number How Representative

North American AIDS Cohort Collaboration on Research and Design

• Clinical cohorts collect data in the course of routine medical practice at each of the contributing clinical sites

• Classical epidemio-logic HIV interval cohorts collect data at visits scheduled every 6 months

• HIV-infected adults at 60+ clinical and academic research sites in the United States and Canada

• Electronic data provided by contributing clinical and interval cohorts

• Clinical cohorts collect data from electronic health records, interview question-naires, chart review, and other data collection systems

• Interval cohorts collect data from structured interview, question-naires, and other data collection systems

• Approximately 100,000 HIV-infected individuals

• Demographics (including age, sex, and transmission risk group) are similar to those reported by the CDC for the United States, but with somewhat fewer minorities; includes individuals from all but three U.S. states, but not all areas of each state represented


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Strengths Limitations Potential Enhancements ACA Implications




• Represents about 20 percent of PLWHA in care • Data are private/ proprietary, but may be available upon submission of proposal for research/policy use • No change anticipated

• New data elements can be added if they are collected by individual cohorts

• No common protocol for timing and standardization of data elements across sites
• Limited data on supportive services
• PLWHA receiving care primarily in academic medical centers may show-little change in already high standard of care in response to ACA or NHAS implementation

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Design Population Covered Source of Data Number How Representative

CFAR Network of Integrated Clinical Systems

• Clinical cohorts • Individuals receiving HIV care at 8 selected CFAR sites across the United Statesc • Electronic health records • 23,197 HIV-infected adults • Representative of PLWHA in the geographic regions of the selected CFAR sites

• Electronic patient-reported outcomes using standardized questionnaire

• Chart review and other data collection systems

HIV Research Network

• Clinical cohorts • Adults, children, and adolescents in care at hospital and community-based outpatient clinics throughout the United States • Data supplied electronically and through medical record review • Approximately 21,000 HIV-infected patients in care • Demographics (including age, sex, race/ ethnicity, and transmission risk group) are similar to those reported by the CDC

• Longitudinal record while in care at a participating site


cUniversity of Alabama at Birmingham (UAB); University of California at San Francisco (UCSF); University of Washington (UW); Case Western Reserve University (CWRU), Cleveland, OH; Lifespan/Tufts/Brown University CFAR (Fenway), Boston, MA/Providence RI; the University of California, San Diego (UCSD); the University of North Carolina at Chapel Hill (UNC), and Johns Hopkins University (JHU), Baltimore, MD.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Strengths Limitations Potential Enhancements ACA Implications




• Much of the data needed to calculate indicators, except for supportive services • Data are private/ proprietary, but may be available upon submission of proposal for research/policy use • No change anticipated
• New data elements, such as housing stability, can be added if they are collected in the clinical practice setting • Population not nationally representative of PLWHA in the United States
• Patient reported outcome questionnaire could be used to ask about basic needs, stigma, discrimination




• Much of the data needed to calculate indicators, except for supportive services • Data are private/ proprietary, but may be available upon submission of proposal for research use
• New data elements, such as housing stability, can be added if they are collected in the clinical practice setting

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Design Population Covered Source of Data Number How Representative

Clinical Case Registry: HIV (Department of Veterans Affairs)

• Longitudinal record while in care in system • HIV-diagnosed veterans receiving care in Veterans Health Administration (VHA) facilities • Electronic health records • 23,463 HIV-infected individuals (2008) • Population is predominantly male and older compared to all PLWHA in the United States

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Strengths Limitations Potential Enhancements ACA Implications




• Outcome and utilization data • Population not nationally representative of PLWHA in the United States • No change anticipated

• Largest provider of HIV care in the United States

• Only captures data within VHA system
• No data on supportive services or mental health/ substance abuse screening

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Design Population Covered Source of Data Number How Representative

Kaiser Permanente

• Longitudinal record while in care in system • HIV-diagnosed individuals enrolled in Kaiser • Electronic health records • > 19,000 HIV-infected individuals (2009); regional variation +/-200 to >6,600 • Largest private provider of HIV care (2010)
• HIV registry of 17,000+ (2010)

• Representative of the insured HIV-positive population in the U.S. areas with Kaiser access (Hawaii, California, Oregon, Mid-Atlantic region, Atlanta, GA)

• Majority Caucasian MSM
• Greater percentage of Latinos on West Coast and greater percentage of blacks on East Coast
• 12% female, but greater percentage on East Coast

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Strengths Limitations Potential Enhancements ACA Implications




• Outcome and utilization data
• Represents one of the largest groups of privately insured PLWHA in the United States
• Data are private/proprietary • Possible increase in enrol lees as more people with low/ moderate incomes (133-400% of federal poverty level) gain access to private insurance

• Only captures data within Kaiser system
• No data on supportive services
• Younger and marginally employed individuals may not remain in system due to insurance status

• Possible increase in private insurance enrollees with elimination of preexisting condition clauses

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Design Population Covered Source of Data Number How Representative

Resource and Patient Management System (Indian Health Service [IHS])

• Longitudinal record while in care in system • American Indians/Alaska Natives receiving HIV care within IHS • Electronic health records • A minority of the estimated 2,385 HIV-positive American Indian/ Alaska Native individuals (2008) receive HIV care in IHS facilities • American Indian/ Alaska Native individuals account for <1 percent of PLWHA

• Not representative of national (or native) population of PLWHA


Bureau of Prisons Electronic Medical Record

• Longitudinal record while in care in system • Federal prisoners diagnosed with HIV/ AIDS • Electronic health records • 1,538 HIV-infected individuals (December 31, 2008) • Not representative of national population of PLWHA

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Strengths Limitations Potential Enhancements ACA Implications




• Utilization and outcome data • Very small subpopulation of PLWHA (even within native population) • No change anticipated

• Optional HIV-specific module in electronic health record system

• Data from tribal facilities require special permission to access

• Important subpopulation

• Data on supportive services are not routinely captured




• Developing capability to extract HIV data that currently are only available at individual level • Very small subpopulation of PLWHA (even among incarcerated population in the United States) • No change anticipated
• Important subpopulation

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Design Population Covered Source of Data Number How Representative

Housing Opportunities for Persons with AIDS (Department of Housing and Urban Development)

• HUU-mandated reporring for Housing Opportunities for Person with AIDS (HOPWA) Competitive Program and Formula Program grantees • Aggregate data on HOPWA beneficiaries and households served and unmet need for housing based on HOPWA-eligible households not served by HOPWA-funded assistance in service area • HOPWA grantees: information on program accomplishments in maintaining housing stability, improving access to care, and reducing risk of homelessness • 60,669 unduplicated households (by end of FY2010) • Generally representative of low-income PLWHA
• Competitive Program grantees file Annual Progress Report
• Formula Program grantees file Consolidated Annual Performance Evaluation Report
Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

Strengths Limitations Potential Enhancements ACA Implications




• Includes data on unmet need for housing among HOPWA-eligible households not receiving HOPWA housing assistance • Data are aggregated
• Includes data on supportive services, such as housing, food or nutrition, and transportation, as well as mental health and substance abuse services funded through HOPWA

• Supportive services information limited to HOPWA-tunded services

• Grantee data can be used to monitor changes at service system level

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

APPENDIX TABLE 3-2a Data Elements for Core Clinical HIV Care Indicators


Date of HIV diagnosis [or first evidence of HIV infection) Date of first visit for HIV care [or date of first/second CD4/viral load test] CD4 count at diagnosis/first visit for HIV care Dates of routine HIV-care visits


National HIV Surveillance System Yes Yes (CD4/VL) Yes Yes (CD4/VL test dates: most reporting areas)


Medical Monitoring Project Yes Yes Yes Yes


Ryan White Services Report No Yes (at present RW provider agency) No Yes


Ryan White ADAP Reports No No No No


Medicaid Statistical Information System No No No Yes


Medicare Chronic Condition Data Warehouse No No No Yes


North American AIDS Cohort Collaboration on Research and Design Yes, hut data are not complete Yes Yes Yes


CFAR Network of Integrated Clinical Systems Yes, but data are not complete Yes Yes Yes


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Dates of CD4 counts CD4 counts Dates of viral load tests Viral load results ART prescription/ dispensing dates Date of death


Yes (most reporting areas) Yes (most reporting areas) Yes (most reporting areas) Yes (most reporting areas) Whether ever taken ARV, ARV taken, and dates taken (not required in all areas) Yes


Yes Yes Yes Yes Yes Yes (during surveillance period)


Yes Yes Yes Yes Whether prescribed within 12-month reporting period Yes


Yes (most recent in past 12 months) Yes (most recent in past 12 months) Yes (most recent in past 12 months) Yes (most recent in past 12 months) Yes (in reporting period: only fully ADAP-funded drugs) No


Yes No Yes No Yes Yes


Yes No Yes No Yes Yes


Yes Yes Yes Yes Yes (dates of starting and stopping individual drugs) Yes


Yes Yes Yes Yes Yes (dates of starting and stopping individual drugs) Yes


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Date of HIV diagnosis [or first evidence of HIV infection) Date of first visit for HIV care [or date of first/second CD4/viral load test] CD4 count at diagnosis/first visit for HIV care Dates of routine HIV-care visits


HIV Research Network Yes (> 60% of patients) Yes Yes Yes


Clinical Case Registry: HIV (VHA) Yes (in VHA) Yes (in VHA) Yes (in VHA) Yes


Kaiser Permanente (KP) Yes (at KP) Yes (at KP) Yes (at KP) Yes


Indian Health Service HIS Yes Yes Yes Yes (in IHS)


Federal Bureau of Prisons Yes (if during incarceration) Yes (if during incarceration) Yes (not discrete data in EHR) Yes (while incarcerated)


Housing Opportunities for Persons with AIDS No No No Households that had contact with primary provider as specified in client’s plan


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Dates of CD4 counts CD4 counts Dates of viral load tests Viral load results ART prescription/ dispensing dates Date of death


Yes Yes Yes Yes Yes Yes


Yes Yes Yes Yes Yes Yes


Yes Yes Yes Yes Yes Yes


Yes (in IHS) Yes (in IHS) Yes (in IHS) Yes (in IHS) Yes (in IHS) Yes


Yes (while incarcerated) Yes Yes (while incarcerated) Yes Yes Yes (if during incarceration, separate database)


No No No No No No


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

APPENDIX TABLE 3-2b Data Elements for Core Mental Health, Substance Abuse, and Supportive Services Indicators


Date of mental health diagnosis or referral Date of first visit for mental health services Date of substance use diagnosis or referral


National HIV Surveillance System No No No


Medical Monitoring Project Whether diagnosed/ referred in 12-month surveillance period, but not date/prior diagnosis Whether received services in 12-month surveillance period, but not date Whether diagnosed/ referred in 12-month surveillance period, but not date


Ryan White Services Report No Number of visits in 12-month reporting period, but not date No


Ryan White ADAP Reports No No No


Medicaid Statistical Information System No Visits, but not first visit specifically No


Medicare Chronic Condition Data Warehouse Yes (in past 12 months) First visit covered by Medicare Yes (in past 12 months)


North American AIDS Cohort Collaboration on Research and Design Yes 2012, will collect visits, but not first visit specifically Yes


CFAR Network of Integrated Clinical Systems Yes Visits, but not first visit specifically Yes


!IIY Research Network Yes (for a subset of sites) Yes (for a subset of sites) Yes (for a subset of sites)


Clinical Case Registry: HIV (VHA) Yes Yes (in VHA) Yes


Kaiser Permanente (kp) Yes Yes (at KP) Yes


Indian Health Service (IHS) Yes Yes (in IHS) Yes


Federal Bureau of Prisons Yes (while incarcerated) Yes (while incarcerated) Yes (while incarcerated)


Housing Opportunities for Persons with AIDS (HOPWA) No Whether received HOPWA-funded services No


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Date of first visit for substance abuse services Housing status Food security status Transportation status


No No No No


Whether received services in 12-month surveillance period, but not date Yes Yes Yes


Number of visits in 12-month reporting period, but not date Yes, also whether received RW-funded services Whether received RW-funded services Whether received RW-funded services


No No No No


Visits, but not first visit specifically No No No


First visit covered by Medicare No No No


No No No No


Whether received services in past year No No No


Yes (for a subset of sites) No No No


Yes (in VHA) No No No


Yes (at KP) No No No


Yes (in IHS) Variable (provider narrative) Variable (provider narrative) Variable (provider narrative)


Yes (while incarcerated) N/A N/A N/A


Yes, also whether received HOPWA-funded services Whether received HOPWA-funded services Whether received HOPWA-funded services Whether received HOPWA-funded services


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

APPENDIX TABLE 3-2c Data Elements for Additional Clinical HIV Care Indicators


Diagnosis of AIDS or AIDS-defining illness Dates and results of TB tests Dates of chlamydia, gonorrhea, and syphilis screening Date of hepatitis B screening or date of documented immunity Dates of hepatitis C tests


National HIV Surveillance System Yes (optional) No No No No


Medical Monitoring Project Yes Yes Yes Yes (2007-2011 cycles only)* Yes (2007-2011 cycles only)*


Ryan White Services Report Yes Yes Yes (syphilis within 12-month reporting period) Whether screened within 12-month reporting period Whether screened within 12-month reporting period


Ryan White ADAP Reports HIV/AIDS status at end of reporting period No No No No


Medicaid Statistical Information System Yes Test dates Yes Yes (screening) Yes


Medicare Chronic Condition Data Warehouse No Test dates Yes Yes (screening) Yes


*Starting with the 2012 data collection cycle, medical record abstraction focuses on the 12 months preceding the interview. Earlier clinical data is no longer captured.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Date of influenza immunization Date of pneumococcal immunization Date of hepatitis B vaccination/date of documented immunity Dates of ART resistance testing Date of ART initiation ART prescription/dispensing dates Diagnosis/test results for HIV nephropathy, hepatitis B, TB


No No No Yes (optional) Yes (self-report, not required in all areas) Whether ever taken ARV, ARV taken, and dates taken (not required in all areas) No


Yes Yes Yes (2007-2011 cycles only)* Yes (during surveillance period) Yes Yes Yes


No No Whether vaccination series is completed No No Whether prescribed within 12-month reporting period No


No No No No Proposed (in reporting period: only fully ADAP- funded drugs) Proposed (in reporting period: only fully ADAP-funded drugs) No


Yes Yes Yes (vaccination) Yes No Yes Diagnosis captured if claim filed with appropriate ICD-9 codes


Yes Yes Yes (vaccination) Yes No Yes No


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Diagnosis of AIDS or AIDS-defining illness Dates and results of TB tests Dates of chlamydia, gonorrhea, and syphilis screening Date of hepatitis B screening or date of documented immunity Dates of hepatitis C tests


North American AIDS Cohort Collaboration on Research and Design Yes Yes No Yes Yes


CHAR Network of Integrated Clinical Systems Yes Yes Yes Yes Yes


HIV Research Network Yes For a subset of sites Yes Yes Yes


Clinical Case Registry: HIV (VHA) Yes Yes Yes Yes Yes


Kaiser Permanente (KP) Yes Yes Yes Yes Yes


Indian Health Sen-ice (IHS) Yes Yes Yes Yes Yes


Federal Bureau of Prisons Yes (if during incarceration) Yes Yes Yes Yes (may not be in EHR)


Housing Opportunities for Persons with AIDS No No No No No


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Date of influenza immunization Date of pneumococcal immunization Date of hepatitis B vaccination/ date of documented immunity Dates of ART resistance testing Date of ART initiation ART prescription/ dispensing dates Diagnosis/ test results for HIV nephropathy, hepatitis B, TB


No No No Yes Yes Yes, dates of starting and stopping individual drugs Yes


Proposed for 2012 Proposed for 2012 Proposed for 2012 Yes Yes Yes, dates of starting and stopping individual drugs Yes


For a subset of sites For a subset of sites For a subset of sites For a subset of sites Yes Yes For a subset of sites


Yes Yes Yes Yes Yes (in VHA) Yes Yes


Yes Yes Yes Yes Yes (at KP) Yes Yes


Yes Yes Yes Yes Yes Yes (in IHS) Yes


Yes Yes Yes Yes (if during incarceration) Yes (if during incarceration) Yes Yes


No No No No No No


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Pregnancy status


National HIV Surveillance System Yes
Medical Monitoring Project Yes
Ryan White Services Report Yes
Ryan White ADAP Reports Yes
Medicaid Statistical Information System Not specifically, but may be extrapolated from related diagnosis/service codes
Medicare Chronic Condition Data Warehouse No
North American AIDS Cohort Collaboration on Research and Design Yes (as of 2012)
CFAR Network of Integrated Clinical Systems Yes (as of 2012)
HIV Research Network No
Clinical Case Registry: HIV (VHA) Yes
Kaiser Permanente Yes
Indian Health Service Yes
Federal Bureau of Prisons Yes (via ICD-9 codes)
Housing Opportunities for Persons with AIDS No


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

APPENDIX TABLE 3-2d follows on next page

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

APPENDIX TABLE 3-2d Data Elements for Additional Mental Health, Substance Abuse, and Supportive Services Indicators


Date of mental health screening Date of screening for substance abuse Dates of housing needs assessment Dates of food security assessment Dates of transportation needs assessment


National HIV Surveillance System No No No No No


Medical Monitoring Project Yes Yes Whether received/ needed services, but not date Whether received/ needed services, but not date Whether received/ needed services, but not date


Ryan White Whether screened within 12-month reporting period, but not date Whether screened within 12-month reporting period, but not date No No No


Ryan White ADAP Reports No No No No No


Medicaid Statistical Information System Yes Yes No No No


Medicare Chronic Condition Data Warehouse No No No No No


North American AIDS Cohort Collaboration on Research and Design No No No No No


CHAR Network of Integrated Clinical Systems Yes Yes No No No


HIV Research Network No No No No No


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Date of mental health screening Date of screening for substance abuse Dates of housing needs assessment Dates of food security assessment Dates of transportation needs assessment


Clinical Case Registry: HIV (VHA) No No No No No


Kaiser Permanente Yes Yes No No No


Indian Health Service Yes Yes No No No


Federal Bureau of Prisons Yes Yes N/A N/A N/A


Housing Opportunities for Persons with AIDS (HOPWA) No No Number of HOPWA-eligible households with unmet need for housing assistance No No


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

APPENDIX TABLE 3-2e Data Elements to Estimate Indicators for Subpopulations


Race Ethnicity Sex (M/F)


National HIV Surveillance System Yes Yes Yes (sex at birth)


Medical Monitoring Project Yes Yes Yes


Ryan White Services Report Yes Yes Yes (male/female under gender)


Ryan White ADAP Reports Yes Yes Yes (male/female under gender)


Medicaid Statistical Information System Yes Yes Yes


Medicare Chronic Condition Data Warehouse Yes Yes Yes


North American AIDS Cohort Collaboration on Research and Design Yes Yes Yes


CFAR Network of Integrated Clinical Systems Yes Yes Yes


HIV Research Network Yes Yes Yes


Clinical Case Registry: HIV (VHA) Yes Yes Yes


Kaiser Permanente Yes Yes Yes


Indian Health Service Yes Yes Yes


Federal Bureau of Prisons Yes Yes (in separate database) Yes


Housing Opportunities for Persons with AIDS Yes Yes Yes


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Gender identity Sexual orientation Date of birth Zip code/ other geographic marker Country of birth


Current gender identity (optional) No (but captures sexual history) Yes Yes (at diagnosis of HIV and AIDS) Yes (optional)


Yes Yes Yes Yes (optional field for local use only) Yes


Yes Yes Yes (year) Yes (first 3 digits) No


Yes No Yes (year) No No


No No Yes Yes No


No No Yes Yes No


No No Yes Yes (first 3 digits) Yes (as of 2012)


No Sex of patient and current partner collected semiannually Yes Yes (first 3 digits) Yes (as of 2012)


Yes (transgender persons who self-identify) Yes Yes No No


No No Yes Yes No


No Yes (but data are not complete) Yes Yes No


No No Yes Yes No


No No Yes N/A Yes (in separate database)


Yes No No Yes No


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

APPENDIX TABLE 3-2f Additional Data Elements for Monitoring HIV Care


Stigma Discrimination Emergency department/inpatient use Sexual risk behaviors


National HIV Surveillance System No No No Yes


Medical Monitoring Project 2011 cycle 2011 cycle Yes Yes


Ryan White Services Report No No No Yes


Ryan White ADAP Reports No No No No


Medicaid Statistical Information System No No Yes No


Medicare Chronic Condition Data Warehouse No No Yes No


North American AIDS Cohort Collaboration on Research and Design No No Yes (as of 2012) No


CHAR Network of Integrated Clinical Systems No No Yes Yes


HIV Research Network No No Yes Yes


Clinical Case Registry: HIV (VHA) No No Yes Variable


Kaiser Permanente (KP) No No Yes Yes


Indian Health Service No No No No


Federal Bureau of Prisons No No No Yes (not as a discrete data element)


Housing Opportunities for Persons with AIDS No No No No


*KP Northwest is the only provider of dental services in the KP system. Only dental services provided within the system are captured.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Partner HIV status Access to dental care Income Employment status Insurance status/type


Yes (only for persons reporting heterosexual risk) No No No Yes (optional)


Yes Yes Yes No Yes


No Yes (RW-funded) Percent of federal poverty level (FPL) No Yes


No No Percent of FPL Current: percent of clients (200% FPL No Yes


No Yes No No Yes


No No No No Yes (only Medicare and Medicaid)


No No No No Yes (as of 2012)


Yes (current partner status semiannually) No No No Yes


No No No No Yes


No Yes (in VHA) No No No


No At KP Northwest (Oregon) only* No Yes Yes


No No No No No


No Yes N/A N/A N/A


No No Yes Yes Yes


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

APPENDIX TABLE 3-3a Data Systems Mapped to Core Clinical HIV Care Indicators


Proportion with CD4+ cell count >200 and without a clinical diagnosis of AIDS Proportion linked to care for HIV within 3 months of diagnosis Proportion in continuous care (2 or more visits in preceding 12 months at least 3 months apart) Proportion who received 2 or more CD4 tests in past 12 months


National HIV Surveillance System Yes (most reporting areas) Yes Most reporting areas: proxy using CD4/VL test dates Yes (most reporting areas)


Medical Monitoring Project Yes Yes Yes Yes


Ryan White Services Report No No Yes Yes


Ryan White ADAP Reports No No No Yes (most recent date)


Medicaid Statistical Information System No No Yes Yes


Medicare Chronic Condition Data Warehouse No No Yes Yes


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Proportion who received 2 or more viral load tests in past 12 months Proportion in continuous care for 12 or more months and with CD4+ cell count ≥350 Proportion with a CD4+ cell count <500 who are not on ART Proportion on ART for 12 or more months who have an undetectable viral load (VL) All-cause mortality rate


Yes (most reporting areas) Possible using CD4 test dates as proxy, but not all jurisdictions report all results No/Variable (minimal data on ART status; variable jurisdictional reporting of CD4 counts) No (no longitudinal data on ART status; variable jurisdictional reporting of VL results) Yes


Yes Yes Yes Yes Yes (during surveillance period)


Yes Yes Yes (within 12-month reporting period) Possible: depends on availability of longitudinal data on ART status Yes


Yes (most recent date) No Possible for future, but only for fully ADAP-funded ARVs Possible for future, but only for fully ADAP-funded ARVs No


Yes No (no CD4 results) No (no CD4 results) No (no VL results) Yes


Yes No (no CD4 results) No (no CD4 results) No (no VL results) Yes


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Proportion with CD4+ cell count >200 and without a clinical diagnosis of AIDS Proportion linked to care for HIV within 3 months of diagnosis Proportion in continuous care (2 or more visits in preceding 12 months at least 3 months apart) Proportion who received 2 or more CD4 tests in past 12 months


North American AIDS Cohort Collaboration on Research and Design Yes Yes (but date- of-diagnosis data are not complete) Yes Yes


CFAR Network of Integrated Clinical Systems Yes Yes (but date- of-diagnosis data are not complete) Yes Yes


HIV Research Network Yes Yes Yes Yes


Clinical Case Registry: HIV (VHA) Yes (diagnosed in VHA) Yes (in VHA) Yes Yes


Kaiser Permanente (KP) Yes (diagnosed at KP) Yes (at KP) Yes Yes


Indian Health Service (IHS) Yes (in IHS) Yes Yes (in IHS) Yes (in IHS)


Federal Bureau of Prisons Yes (if diagnosed while incarcerated Yes (if diagnosed during incarceration) Yes Yes


Housing Opportunities for Persons with AIDS No No Proportion following client-specific schedule for contact with provider No


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Proportion who received 2 or more viral load tests in past 12 months Proportion in continuous care for 12 or more months and with CD4+ cell count ≥350 Proportion with a CD4+ cell count <500 who are not on ART Proportion on ART for 12 or more months who have an undetectable viral load (VL) All-cause mortality rate


Yes Yes Yes Yes Yes


Yes Yes Yes Yes Yes


Yes Yes Yes Yes Yes


Yes Yes Yes Yes Yes


Yes Yes Yes Yes Yes


Yes (in IHS) Yes (in IHS) Yes (in IHS) Yes (in IHS) Yes


Yes Yes (if incarcerated during that period) Yes Yes Yes (in separate database for those who die while incarcerated)


No No No No No


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

APPENDIX TABLE 3-3b Data Systems Mapped to Core Mental Health, Substance Abuse, and Supportive Services Indicators


Proportion with mental health disorder referred for mental health services who receive these services within 60 days Proportion with substance use disorder referred for substance abuse services who receive these services within 60 days


National HIV Surveillance System No No


Medical Monitoring Project No (no dates for diagnosis/ referral or services) No (no dates for diagnosis/ referral or services)


Ryan White Services Report No No


Ryan White ADAP Reports No No


Medicaid Statistical Information System No No


Medicare Chronic Condition Data Warehouse Yes, if first visit covered by Medicare Yes, if first visit covered by Medicare


North American AIDS Cohort Collaboration on Research and Design Possible, if a service date is proximate to referral date No


CHAR Network of Integrated Clinical Systems Possible, if a service date is proximate to referral date No


HIV Research Network Yes (for a subset of sites) Yes (for a subset of sites)


Clinical Case Registry: HIV (VHA) Yes (in VHA) Yes (in VHA)


Kaiser Permanente (KP) Yes (at KP) Yes (at KP)


Indian Health Service (IHS) Yes (in IHS) Yes (in IHS)


Federal Bureau of Prisons Yes (while incarcerated) Yes (while incarcerated)


Housing Opportunities for Persons with AIDS No No


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Proportion who were homeless or temporarily or unstably housed at least once in the preceding 12 months Proportion who experienced food or nutrition insecurity at least once in the preceding 12 months Proportion who had an unmet need for transportation services at least once in the preceding 12 months


No No No


Yes Yes Yes


Yes, also whether received RW-funded services Whether received RW-funded services Whether received RW-funded services


No No No


No No No


No No No


No No No


No No No


No No No


No No No


No No No


Variable (incomplete data) Variable (incomplete data) Variable (incomplete data)


N/A N/A N/A


Yes No No


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

APPENDIX TABLE 3-3c Data Systems Mapped to Additional Clinical HIV Care Indicators


Proportion screened for TB since diagnosis and results interpreted Proportion screened for chlamydia, gonorrhea, and syphilis Proportion screened for hepatitis B since diagnosis Proportion screened for hepatitis C Proportion immunized for influenza


National HIV Surveillance System No No No No No


Medical Monitoring Project Yes Yes Yes (2007-2011 cycles only)* Yes (2007-2011 cycles only)* Yes


Ryan White Services Report Yes (but lacks diagnosis date) Syphilis within 12-month reporting period Yes (within 12-month reporting period) Yes (within 12-month reporting period) No


Ryan White ADAP Reports No No No No No


Medicaid Statistical Information System Yes (but lacks diagnosis date; TB test results) Yes Yes (but lacks diagnosis date) Yes Yes


Medicare Chronic Condition Data Warehouse Yes (but lacks diagnosis date; TB test results) Yes Yes (but lacks diagnosis date) Yes Yes


*Starting with the 2012 data collection cycle, medical record abstraction will focus on the 12 months preceding the interview. Earlier clinical data will no longer be captured.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Proportion immunized for pneumococcal pneumonia since diagnosis Proportion immunized for hepatitis B (if needed) Proportion who receive drug resistance testing prior to ART initiation Proportion with HIV-associated nephropathy, hepatitis B (when treatment is indicated) or active TB who are not on ART Proportion HIV-infected pregnant women who are not on ART


No No No No Yes (when pregnancy and ART status captured)


Yes (during surveillance period) Yes (2007-2011 cycles only)* Yes (during surveillance period) Yes Yes


No Whether vaccination series is completed No No Yes (ART prescribed in last 12 months)


No No No No Data only for fully ADAPfunded drugs


Yes (but lacks diagnosis date) Yes Yes (if covered and identifiable by code; lacks ART initiation date) Yes (if claims filed with proper diagnosis code/s) Yes (if pregnancy captured by relevant diagnostic code/s)


Yes (but lacks diagnosis date) Yes Yes (but lacks ART initiation date) No No


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Proportion screened for TB since diagnosis and results interpreted Proportion screened for chlamydia, gonorrhea, and syphilis Proportion screened for hepatitis B since diagnosis Proportion screened for hepatitis C Proportion immunized for influenza


North American AIDS Cohort Collaboration on Research and Design Yes No Yes (date-of-diagnosis data incomplete) Yes No


CHAR Network of Integrated Clinical Systems Yes Yes Yes (date-of-diagnosis data incomplete) Yes Proposed for 2012


HIV Research Network Yes (for a subset of sites) Yes Yes Yes Yes (for a subset of sites)


Clinical Case Registry: HIV (VHA) Yes (in VHA) Yes Yes Yes Yes


Kaiser Permanente (KP) Yes (at KP) Yes Yes Yes Yes


Indian Health Service (IHS) Yes (in IHS) Yes Yes Yes Yes


Federal Bureau of Prisons Yes Yes Yes Yes (although data may not be available in EHR) Yes


Housing Opportunities for Persons with AIDS No No No No No


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Proportion immunized for pneumococcal pneumonia since diagnosis Proportion immunized for hepatitis B (if needed) Proportion who receive drug resistance testing prior to ART initiation Proportion with HIV-associated nephropathy, hepatitis B (when treatment is indicated) or active TB who are not on ART Proportion HIV-infected pregnant women who are not on ART


No No Yes Yes Yes (as of 2012)


Proposed for 2012 (date-of-diagnosis data incomplete) Proposed for 2012 Yes Yes Yes (as of 2012)


Yes (for a subset of sites) Yes (for a subset of sites) Yes (for a subset of sites) Yes (for a subset of sites) Mo


Yes Yes Yes Yes Yes


Yes Yes Yes Yes Yes


Yes Yes Yes Yes Yes


Yes Yes Yes (may not be available) Yes (would require record abstraction and verification) Yes


No No No No No


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×

APPENDIX TABLE 3-3d Data Systems Mapped to Additional Mental Health, Substance Abuse, and Supportive Services Indicators


Proportion screened for mental health disorders at least once in the past 12 months Proportion screened for substance use disorders at least once in the past 12 months Proportion assessed for need for housing at least once in the past 12 months Proportion assessed for need for food or nutrition at least once in the past 12 months Proportion assessed for need for transportation at least once in the past 12 months


National HIV Surveillance System No No No No No


Medical Monitoring Project Yes Yes No (whether received/ needed services, but not date) No (whether received/ needed services, but not date) No (whether received/ needed services, but not date)


Ryan White Services Report Yes Yes No No No


Ryan White ADAP Reports No No No No No


Medicaid Statistical Information System Yes Yes No No No


Medicare Chronic Condition Data Warehouse No No No No No


North American AIDS Cohort Collaboration on Research and Design No No No No No


CHAR Network of Integrated Clinical Systems Yes Yes No No No


HIV Research Network No No No No No


Clinical Case Registry: HIV (VHA) No No No No No


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
×


Proportion screened for mental health disorders at least once in the past 12 months Proportion screened for substance use disorders at least once in the past 12 months Proportion assessed for need for housing at least once in the past 12 months Proportion assessed for need for food or nutrition at least once in the past 12 months Proportion assessed for need for transportation at least once in the past 12 months


Kaiser Permanente Yes Yes Mo No No


Indian Health Service Yes Yes Mo No No


Federal Bureau of Prisons Yes Yes N/A N/A N/A


Housing Opportunities for Persons with AIDS No No Yes No No


Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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APPENDIX TABLE 3-4 Publicly Available Data Collection Instruments and Information


Data System Collection Instrument/s

National HIV Surveillance System 1. Adult HIV/AIDS Confidential Case Report
Medical Monitoring Project 1. 2010 Medical History Form*
2. 2010 Surveillance Period Inpatient Form*
3. 2010 Surveillance Period Summary Form*
4. 2010 Surveillance Period Visit Form*
5. 2010 Standard Questionnaire*
6. 2011 Medical Monitoring Project Response Cards
Ryan White AIDS Drug Assistance Program (ADAP) Reports 1. AIDS Drug Assistance Program (ADAP) Data Report—Final Client-Level Data Variables (Effective October 1,2012)
2. ADAP Data Report; Grantee Report: Summary of Changes to the Grantee:Level Variables
3. ADAP—Quarterly Data Report (Phasing out this year)
Ryan White Services Report 1. Data Elements for Client-Level Data Export (Effective for the 2010 Annual RSR)
Medicaid Statistical Information System 1. Medicaid Analytic eXtract Files (MAX) User Guide
2. Medicaid and CHIP Statistical Information System (MSIS): File Specifications and Data Dictionary
Medicare Chronic Condition Data Warehouse 1. Chronic Condition Data Warehouse User Guide
2. Summary Statistics
3. Data Dictionaries
4. Chronic Conditions
5. Analytic Guidance
CHAR Network of Integrated Clinical Systems 1. CN1CS Data Elements
Indian Health Service 1. HIS Clinical Reporting System (BGP): Selected Measures (Local) Report Performance Measure List and Definitions
Federal Bureau of Prisons 1. Management of HIV: Federal Bureau of Prisons Clinical Practice Guidelines—May 2011
Housing Opportunities for Persons with AIDS 1. Annual Progress Report (APR): Measuring Performance Outcomes
2. Consolidated Annual Performance Evaluation Report (CAPF1R): Measuring Performance Outcomes
3. Homeless Management Information System (HMIS) Data Standards, Revised Notice—March 2010

*Link to 2009 version of MMP data collection materials.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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Link/s

1. http://www.cdc.gov/hiv/topics/treatment/MMP/pdf/MMP_2009_MRA_MHF_v400_OMB_Race_Jan5_2009.pdf
2. http://www.cdc.gov/hiv/topics/treatment/MMP/pdf/MMP_2009_MRA_SPIF_v400_Jan5_2009.pdf
3. http://www.cdc.gov/hiv/topics/treatment/MMP/pdf/MMP_2009_MRA_SPSF_v400_Jan5_2009.pdf
4. http://www.cdc.gov/hiv/topics/treatment/MMP/pdf/MMP_2009_MRA_SPVF_v400_Jan5_2009.pdf
5. http://www.cdc.gov/hiv/topics/treatment/MMP/pdf/2009MMPStandardEnglish.pdf
6. http://www.cdc.gov/hiv/topics/treatment/mmp/pdf/2011_english_response_cards.pdf
1. http://hab.hrsa.gov/manageyourgrant/files/habadrclientlevelvariables.pdf
2. http://hab.hrsa.gov/manageyourgrant/files/adrgranteeleveldatavariablesfinal.pdf
3. http://hab.hrsa.gov/manageyourgrant/adap/adapformfeb08.pdf
1. http://hab.hrsa.gov/manageyourgrant/files/clientleveldatafields.pdf
1. http://www.ccwdata.org/cs/groups/public/documents/document/ccw_max_user_guide.pdf
2. http://www.cms.gov/msis/downloads/msisdd2010.pdf
1. http://www.ccwdata.org/cs/groups/public/documents/document/ccw_userguide.pdf
2. http://www.ccwdata.org/summary-statistics/index.htm
3. http://www.ccwdata.org/data-dictionaries/index.htm
4. http://www.ccwdata.org/chronic-conditions/index.htm
5. http://www.ccwdata.org/analytic-guidance/index.htm
1. http://www.uab.edu/cnics/data-core/cnics-data-elements
1. http://www.ihs.gov/cio/crs/documents/crsv11/SelectedMeasuresV11_1.pdf
1. http://www.bop.gov/news/PDFs/mgmt_hiv.pdf
1. http://www.hudhre.info/documents/APR_HOPWA.docx
2. http://portal.hud.gov/hudportal/documents/huddoc?id=hopwa_caper_10312014.doc
3. http://www.hudhre.info/documents/FinalHMISDataStandards_March2010.pdf
Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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APPENDIX TABLE 3-5 CD4 and Viral Load Reporting by HIV Surveillance Reporting Area (as of June 15, 2010)


CD4 count (cdh/µL)


Reportable Level All Values Reportable Level <200


Alaska, Arkansas, California, Delaware, Florida, Georgia, Hawaii, Illinois, Indiana, Iowa, Kentucky, Louisiana, Maine, Maryland, Massachusetts,* Michigan, Minnesota, Mississippi, Missouri, Nebraska, New Hampshire, New York, North Dakota, Oregon, South Carolina, South Dakota, Texas, Utah, Virginia, Washington, West Virginia, Wyoming Alabama, Arizona, Connecticut, Idaho, New Jersey, New Mexico, North Carolina, Ohio, Pennsylvania, Rhode Island, Tennessee, Vermont, Wisconsin
District of Columbia
Guam, Puerto Rico U.S. Virgin Islands


Viral Load


Reportable Level Any Result Reportable Level Detectable


Alaska, Arkansas, California, Colorado, Connecticut, Delaware, Horida, Georgia, Hawaii, Illinois, Indiana, Iowa, Louisiana, Maine, Maryland, Massachusetts*, Michigan, Minnesota, Mississippi, Missouri, Nebraska, New Hampshire, New Jersey, New Mexico, New York, North Dakota, Oklahoma, Oregon, South Carolina, South Dakota, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, Wyoming Arizona, Idaho, Kansas, Kentucky, Montana, Nevada, North Carolina, Ohio, Pennsylvania, Rhode island, Tennessee
District of Columbia
Guam, Puerto Rico U.S. Virgin Islands


*As of January 2012.

SOURCES: Personal Communication, Amy Lansky, Centers for Disease Control and Prevention, October 6, 2011; Massachusetts Department of Public Health, 2012.

Suggested Citation:"3 Sources of Data on HIV Care to Assess Indicators of HIV Care and Access to Supportive Services." Institute of Medicine. 2012. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: The National Academies Press. doi: 10.17226/13225.
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Reportable Level
<500
No Reporting


Colorado, Kansas, Nevada, Oklahoma Montana

American Samoa; Marshall Islands;
Micronesia, FS; N. Mariana Islands; Palau



No Reporting


Alabama

American Samoa; Marshall Islands;
Micronesia, FS; N. Mariana Islands; Palau


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The number of people living with HIV/AIDS (PLWHA) in the United States is growing each year largely due both to advances in treatment that allow HIV-infected individuals to live longer and healthier lives and due to a steady number of new HIV infections each year. The U.S. Centers for Disease Control and Prevention (CDC) estimates that there were 1.2 million people living with HIV infection in the United States at the end of 2008, the most recent year for which national prevalence data are available. Each year, approximately 16,000 individuals die from AIDS despite overall improvements in survival, and 50,000 individuals become newly infected with HIV. In 2011, the CDC estimated that about three in four people living with diagnosed HIV infection are linked to care within 3 to 4 months of diagnosis and that only half are retained in ongoing care.

In the context of the continuing challenges posed by HIV, the White House Office of National AIDS Policy (ONAP) released a National HIV/AIDS Strategy (NHAS) for the United States in July 2010. The primary goals of the NHAS are to: reduce HIV incidence; increase access to care and optimize health outcomes; and reduce HIV-related health disparities.

Monitoring HIV Care in the United States addresses existing gaps in the collection, analysis, and integration of data on the care and treatment experiences of PLWHA. This report identifies critical data and indicators related to continuous HIV care and access to supportive services, assesses the impact of the NHAS and the ACA on improvements in HIV care, and identifies public and private data systems that capture the data needed to estimate these indicators. In addition, this report addresses a series of specific questions related to the collection, analysis, and dissemination of such data.

Monitoring HIV Care in the United States is the first of two reports to be prepared by this study. In a forthcoming report, also requested by ONAP, the committee will address the broad question of how to obtain national estimates that characterize the health care of people living with HIV in the United States. The second report will include discussion of challenges and best practices from previous large scale and nationally representative studies of PLWHA as well as other populations.

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