Clinical Data as the Basic Staple of Health Learning Creating and Protecting a Public Good: Workshop Summary (2010) / Chapter Skim
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2 U.S. Healthcare Data Today: Current State of Play
2 U.S. Healthcare Data Today: Current State of Play
Pages 69-108
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From page 69... ...
Through examples of healthcare data used to manage and drive improvements in care and for healthcare marketing, this chapter explores important aspects of healthcare data in the United States -- examines what drives the collection of these data and the accessibility of these data for new clinical insights; reflects on how well these data are used and key barriers to wider use; and focuses attention on how clinical data from all sources -- both public and private -- could be made more widely useful to monitor clinical effectiveness. As reviewed in this chapter, data are collected on socioeconomic, environmental, biomedical, and genetic factors; individual health status and health behaviors; biomedical and genetic factors, as well as on resource use, outcomes, financing, and expenditures.
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From page 70... ...
, Simon Cohn offers an overview of current major activities in healthcare data collection and database capacity development, including those related to administrative and claims data, quality indicators, health status and outcomes data, clinical research data, industry-sponsored pre- and postmarket studies, regulatory studies, registries, and emerging datasets. To help frame the discussion, Cohn presents a taxonomy for health data, then reflects on key issues and barriers to address as we move to a learning health system.
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From page 71... ...
Cohn, M.D., M.P.H. Chair, National Committee on Vital and Health Statistics Associate Executie Director, The Permanente Federation, Kaiser Permanente This section aims to provide a brief overview of major current activities in healthcare data development and collection -- including administrative and claims data, quality indicators, health status and outcomes data, clinical research data, industry-sponsored pre- and postmarket studies, regulatory studies, registries, and emerging datasets.
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From page 72... ...
that was requested by the Department of Health and Human Services (HHS) to further investigate and consider "secondary uses" of electronically collected and transmitted healthcare data as we move into the world of the Nationwide Health Information Network (NHIN)
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From page 73... ...
In the context of this discussion of more traditional health and healthcare data, as well as of issues and barriers, it is important to recognize how much information we do not routinely collect, or if we do, we do not normally integrate it into our vision of health and health improvement. This NCVHS work was an important input to subsequent efforts to develop simpler, more approachable health and healthcare conceptual frameworks internationally.
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From page 74... ...
FIGURE 2-1 Influences on the population's health.
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From page 75... ...
. This useful tool frames thinking about the data needed for a learning healthcare system as well as the development of sound health policy.
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From page 76... ...
BOX 2-1 Taxonomy Used by HHS Data Crucial for Health Data and Statistics Planning • Demographics and Socioeconomic Data -- ge, sex, race, ethnicity, education, and related demographic/ A socioeconomic variables • Health Status Data -- ndividual health status, including morbidity, disability, diagnoses, I problems, complaints, and signs and symptoms as well as behav ioral and health risk factor data • Health Resources Data -- apacity and characteristics of the provider, plan, or health C system • Healthcare Utilization Data -- ature and characteristics of the medical care visits, encounter, N discharge, stay, or other use of healthcare services. Includes time, data, duration, tests, procedures, treatment, prescriptions, and other elements of the health encounter • Healthcare Financing and Expenditure Data -- osts, prices, charges, payments, insurance status, and source of C payment • Healthcare Outcomes -- utcomes of prior or current prevention, treatment, counseling, or O other interventions on future health status over time in a cyclical, longitudinal process • Other Factors -- enes and proteins, environmental exposures G SOURCE: Adapted from HHS Data Council (2007)
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From page 77... ...
The inability to connect data that may include risk factors, medical history, and interventions in a comprehensive way is a fundamental flaw in moving forward. The hopeful news is that the vision of the NHIN is intended to help consolidate the data, but we are rife with fragmentation of health and healthcare data at this point.
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From page 78... ...
Certainly, the work of the ONC and HHS toward the vision and instantiation of the NHIN needs our support. Various initiatives that are also under way to help consolidate healthcare data for important purposes such as quality measurement deserve ongoing support and encouragement.
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Clinically rich data, all standardized and interoperable, will provide a fertile environment for the learning health system, but many of these terminologies will be stretched to their limits. Unforeseen problems will need to be remedied.
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From page 80... ...
Enhanced Protections for Secondary Uses of Health Data A transformation in health and health care is being enabled by health information technology (HIT) : electronically available health data are no longer just claims data, but include more clinically rich data and can be linked more readily with other databases.
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From page 81... ...
To guide the development of recommendations and maintain consistency with other NCVHS work, the committee developed guiding principles for evaluating each recommendation. These principles include precepts that healthcare data protections should: maintain or strengthen an individual's health information privacy; enable improvements in the health of Americans and the healthcare delivery system of the nation; facilitate appropriate uses of electronic health information; increase the clarity and understanding of laws and regulations pertaining to privacy and the security of health information; and build on existing legislation and regulations whenever they are appropriate and do not result in undue administrative burden.
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From page 82... ...
The NCVHS has long supported more inclusive federal privacy legislation to cover all organizations that have access to personal health data. At a minimum, expanding HIPAA coverage to new entities that are holding personal health information (PHI)
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From page 83... ...
claims data as a BQI pilot; • Capture and aggregation of electronic clinical data in a quality data warehouse with the Massachusetts eHealth Collaborative; and • Aggregation of health plan HEDIS data. MHQP aggregates HEDIS data already calculated by health plans (numerators and denominators for individual physicians)
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From page 84... ...
how the different medical groups within those networks perform; (3) how practice sites within the medical groups per Physician Network D HEDIS 2003 Commercial Products Chlamydia Screening in Women Ages 16-20 Physician Network D Description of Measure: The percentage of women, ages 16 to 20, who were Trend MHQP MA Statewide Rate members of one of the five par ticipating health plans, had claims-based evidence of National 90th Percentile sexual activity and received a test for Chlamydia during the measurement year.
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From page 85... ...
Aggregation of Commercial Health Plan Claims Data and Medicare FFS Claims In 2006 MHQP was one of six organizations across the country to be designated as a Better Quality Information to Improve Care for Medicare Beneficiaries pilot. BQI is a CMS initiative to combine public and private information to measure and report on physician performance.
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. Reprinted with the permission of the Massachusetts Health Quality Partners.
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From page 87... ...
Each BQI pilot health delivery market brings many unique characteristics. For example, the Indiana Health Information Exchange has access to a rich clinical data source because of the work the Regenstrief Institute has accomplished over the years, and the Wisconsin Collaborative for Health Care Quality does not use health plan claims data, but rather uses source data provided from the large physician groups.
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From page 88... ...
Capturing clinical data and deriving quality measures from the EHRs and HIEs has been quite challenging. The technical specifications for measure creation have been based historically on data elements available in claims data, not electronic clinical data.
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From page 89... ...
They have influenced decisions to accelerate implementation of electronic health record systems, and decisions about how standardized individual EHR systems should be within a physician organization given budget considerations. Physician organizations are also using MHQP's private reports within their organizations to focus improvement efforts and to reward individual physician performance.
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From page 90... ...
Opportunities to Create More Meaningful Quality Measures The best way for MHQP to create more meaningful quality measures is to be able to capture clinical outcome data from EHRs and other electronic data sources. Experts in the HIT world are beginning to pay attention to the need to capture healthcare quality information for measurement purposes, and on the national level, the health information community and the quality community are beginning to work with a broad-based set of stakeholders to define how HIT can effectively support quality improvement.
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. Data based on clinical care come from electronic health records, clinic-based administrative datasets, and government payer datasets.
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. Despite concern that administrative databases inherently yield biased estimates, some investigators have found that predictions based on administrative data closely approximate those based on rigorously obtained clinical data (Krumholz et al., 2006)
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Patients who underwent coronary artery bypass grafting (CABG) had better outcomes than those who had stenting.
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aspects of common cardiovascular diseases. The Framingham Heart Study cohort is the basis for one of the most commonly accepted means of global risk assessment of patients at risk for coronary heart disease (Executive summary, 2001)
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that has been used, for example, to generate robust prediction models for outcomes of patients hospitalized for acute myocardial infarction or decompensated heart failure (Krumholz et al., 2006)
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, whereas others are only available to personnel working at specific clinical sites or for specific sponsors. Obserational Data Nearly all data derived from electronic health records and public or private registries are observational, that is, not based on randomized experiments.
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. Data Access In 1989, Claude L'Enfant, then NHLBI director, sent a memo to division directors, calling attention to a policy for widespread data release of Institute-supported, multicenter clinical trials and epidemiological studies (Figure 2-8)
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From page 98... ...
. In one program, the Personal Genome Project, an "open consent" model is being proposed by which adults volunteer to give DNA samples along with health information with the understanding that their data will be widely available and that there are no guarantees of anonymity, confidentiality, and privacy (Lunshof et al., 2008)
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From page 99... ...
and requires results for many clinical trials, whether publicly funded or publicly noted, to be made publicly available. Summary and Closing Thoughts For many decades, researchers and clinicians have taken advantage of many sources of rich clinical and population-based data to generate new insights, stimulate major research programs, and develop robust clinical guidelines.
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From page 100... ...
Much of the information about patient/consumer attitudes comes from this source. The administrative data include retail store sales data, patient eligibility and medical claims data, and a growing availability of short- and long-term disability claims data as well as health risk appraisal data.
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From page 101... ...
The administrative data assets are often used in retrospective database studies to examine the cost effectiveness of interventions in the general population (outside the context of clinical trials, where both providers and patients are strongly encouraged to be on their best behavior)
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From page 102... ...
Marketing data analyses draw on a rich abundance of administrative data that offer both advantages and shortfalls. Retail store sales data, for example, can include information on pharmaceutical use; available quickly, such data can sometimes identify the prescribing physician.
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From page 103... ...
At a perhaps more strategic level, claims data can offer insights for evaluating unmet medical needs, understanding the cost of acquiring a drug in a broader context, pricing new products, gaining favorable formulary position, and convincing prescribers about the value of a drug. The development of healthcare marketing data is also informed by the FDA's encouragement of peer review.
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From page 104... ...
The best of what are currently available are labresult data linked to claims. Health plans are in the best position to acquire data from national labs.
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2006. Systematic Review: Impact of Health Information Technology on Quality, Effi ciency, and Costs of Medical Care.
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From page 106... ...
2006. How common are electronic health records in the United States?
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From page 107... ...
2007. Enhanced protections for uses of health data: A stewardship framework for "secondary uses" of electronically collected and transmitted health data.
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From page 108... ...
2007. Toward a national framework for the secondary use of health data: An american medical informatics association white paper.
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