Summary

INTRODUCTION AND OVERVIEW

Because of their potential to enable the development of new knowledge and to guide the development of best practices from the growing sum of individual clinical experiences, clinical data represent the resource most central to healthcare progress (Arrow et al., 2009; Detmer, 2003). Whether captured during product development activities such as clinical research trials and studies, or as a part of the care delivery process, these data are fundamental to the delivery of timely, appropriate care of value to individual patients—and essential to building a system that continually learns from and improves upon care delivered. The opportunities for learning from practice are substantial, from improved understanding of the effects of different treatments and therapies in specific patient subpopulations, to developing and refining practices to streamline or tailor care processes for complex patients, to the development of a delivery system that can advance the evidence base on novel diagnostic and therapeutic techniques (Hrynaszkiewicz and Altman, 2009; Nass et al., 2009; NRC, 2009; Safran, 2007). Furthermore, U.S. per capita healthcare costs are now nearly double that of comparable nations (Health care spending in the United States and OECD countries, 2007), and broader access and use of existing and future clinical data may be a key opportunity to better understand and address system-wide factors—such as waste and inefficiencies—that contribute to rising healthcare expenditures.

Clinical data now reside in many often unconnected and inaccessible repositories, making linkage, analysis, and interpretation of these data



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 1
Summary INTRODUCTION AND OVERVIEW Because of their potential to enable the development of new knowledge and to guide the development of best practices from the growing sum of individual clinical experiences, clinical data represent the resource most central to healthcare progress (Arrow et al., 2009; Detmer, 2003). Whether captured during product development activities such as clinical research trials and studies, or as a part of the care delivery process, these data are fundamental to the delivery of timely, appropriate care of value to indi- vidual patients—and essential to building a system that continually learns from and improves upon care delivered. The opportunities for learning from practice are substantial, from improved understanding of the effects of different treatments and therapies in specific patient subpopulations, to developing and refining practices to streamline or tailor care processes for complex patients, to the development of a delivery system that can advance the evidence base on novel diagnostic and therapeutic techniques (Hrynaszkiewicz and Altman, 2009; Nass et al., 2009; NRC, 2009; Safran, 2007). Furthermore, U.S. per capita healthcare costs are now nearly double that of comparable nations (Health care spending in the United States and OECD countries, 2007), and broader access and use of existing and future clinical data may be a key opportunity to better understand and address system-wide factors—such as waste and inefficiencies—that contribute to rising healthcare expenditures. Clinical data now reside in many often unconnected and inaccessible repositories, making linkage, analysis, and interpretation of these data 

OCR for page 1
2 CLINICAL DATA AS THE BASIC STAPLE OF HEALTH LEARNING challenging on an individual or population level. The increase in poten- tially interoperable electronic and personal health datasets—integrated with laboratory values, diagnostic images, and patient demographic information and preferences—and development of approaches to link and network these data offer even greater opportunity to create and use rich data resources to help transform healthcare delivery and improve the public’s health. Concerns about privacy of health data, as well as the treatment of medical data—even those generated with public funds—as proprietary goods pose additional challenges to data use (Blumenthal, 2006; Nass et al., 2009, edi- tors, Nature 2005, Ness, 2007; Piwowar et al., 2008). The utility of clinical data as a transformative agent in the U.S. health- care system was the focus of the February 2008 Institute of Medicine (IOM) workshop, Clinical Data as the Basic Staple of Health Learning: Creating and Protecting a Public Good. Issues motivating discussion include the potential for clinical data as a resource for continuous learning and key component of an efficient healthcare system; the opportunities presented by vastly larger and potentially interoperable data resources—particularly those developed with public funds; the challenges and barriers to more appropriate use of these resources (e.g., related to the fragmentation of data, proprietary nature of data, and privacy concerns); the lag of public policy development and public awareness of and attention to these issues; and the need to address key issues, including the extent to which data con- stitute a public good (Box S-1). During the 2-day workshop, participants representing a variety of healthcare perspectives, reviewed current use of data for benchmarking and generating new clinical and operational insights, and discussed a sampling of innovative efforts to aggregate data for greater insights. In evaluating the current marketplace for care data, participants presented opportunities to increase access to and sharing of health information as private and public goods, while devoting particular attention to legal and social aspects of privacy and security of healthcare data. The workshop addressed multiple health-sector perspectives in the identification of specific policy areas for developing strategies and next-generation health data systems. Engaging the public in the advances necessary to develop a learning health system was viewed as a particularly important area for further discussion. The IOM Roundtable and the Clinical Data Utility Convened by the IOM in 2006, the Roundtable on Value & Science- Driven Health Care (formerly the Roundtable on Evidence-Based Medicine) serves as a mechanism for bringing stakeholders from multiple sectors together to evaluate means through which improving the generation and application of evidence will accelerate progress toward an efficient, effective

OCR for page 1
 SUMMARY BOX S-1 Issues Motivating Discussion 1. iscovering what works best in medical care—including for whom and D under what circumstances—requires that clinical data be carefully nurtured as a resource for continuous learning. 2. ransformational opportunities are presented by evolving large and T potentially interoperable clinical and administrative datasets. 3. linical data are recorded and held in multiple activities and many C institutions, including medical records, administrative and claims r ecords, and research studies. 4. ublic policy and public awareness lag behind the technical, organiza- P tional, and legal capacity for reliable safeguarding of individual privacy and data security in mining clinical data for new knowledge. 5. significant challenge to progress resides in the barriers and restric- A tions that derive from the treatment of medical care data as a propri- etary commodity by the organizations involved. 6. ven clinical research and medical care data developed with public E funds are often not available for broader analysis and insights. 7. roader access and use of healthcare data for new insights requires B not only fostering data system reliability and interoperability but also addressing the matter of individual data ownership and the extent to which data central to progress in health and health care should con- stitute a public good. U.S. medical care system. These stakeholders span the realm of health care, and include patients, employers, health product manufacturers, payers, policy makers, providers, and researchers. As a guiding principle for the Roundtable, decisions shaping American health and health care will draw from a proven evidence base, appropriately accommodate patient variation, and simultaneously generate additional insight into clinical effectiveness. Roundtable participants established a goal that, by the year 2020, 90 percent of clinical decisions will be supported by accurate, timely, and up-to-date clinical information and will reflect the best available evidence. Central to this goal is the development of a learning health system designed to generate the best evidence for the collaborative healthcare choices of each patient and each provider; to drive the process of discovery as a natural outgrowth of patient care; and to ensure innovation, quality, safety, and value in health care. The broader availability and use of clinical data is an essential component of a learning system given the large potential for gains

OCR for page 1
 CLINICAL DATA AS THE BASIC STAPLE OF HEALTH LEARNING in the efficiency, quality, and safety of the care delivered; however, such a shift will have systemwide implications: drawing upon resources in each sector, and requiring cross-sector cooperation and discussion to ensure the appropriate development, support, and use of these resources. The Roundtable’s Learning Health System series of workshops and publications are opportunities to foster the broad cross-sector discussions needed to better characterize the key elements, barriers, and needs of a transformed healthcare system. Each workshop is summarized in a pub- lication available through the National Academies Press. Workshops and publications in this series since 2006 include: • The Learning Healthcare System • Judging the Evidence: Standards for Determining Clinical Effectiveness • Leadership Commitments to Improve Value in Health Care: Find- ing Common Ground • Redesigning the Clinical Effectiveness Research Paradigm: Innova- tion and Practice-Based Approaches • Clinical Data as the Basic Staple of Health Learning: Creating and Protecting a Public Good • Engineering a Learning Healthcare System: A Look at the Future • Learning What Works: Infrastructure Required to Learn Which Care Is Best • Value in Health Care: Accounting for Cost, Quality, Safety, Out- comes, and Innovation • The Healthcare Imperative: Lowering Costs and Improving Outcomes—A Four-Part Workshop Series This publication summarizes the proceedings of the sixth workshop in the series, Clinical Data as the Basic Staple of Health Learning: Creat- ing and Protecting a Public Good. A summary chapter includes highlights from each workshop session; manuscripts submitted by each speaker and panel discussion summaries can be found in the subsequent chapters. Two keynote presentations, included in Chapter 1, titled “Clinical Data as the Basic Staple of the Learning Health System” and “Creating a Public Good for the Public’s Health,” offered critical context for the workshop. The first day of the 2-day workshop also featured presentations that profiled data in the current healthcare system (Chapter 2), provided an overview of innovative efforts to use data (Chapter 3), evaluated the public and private natures of healthcare data (Chapter 4), and discussed issues related to privacy and security (Chapter 5). The second day featured a panel dis- cussion on policy opportunities (also in Chapter 5) and presentations and discussions that identified next-generation data utilities (Chapter 6). The

OCR for page 1
 SUMMARY workshop concluded with a focus on engaging the public in efforts to use clinical data for insights (Chapter 7) and some final observations on meet- ing themes and potential follow-on activities (Chapter 8). The workshop agenda, biographical sketches, and a list of participants are located in the appendixes. COMMON THEMES Apart from shedding light on the issues that impede or challenge improved data utility, the discussion identified a rich array of ideas for accelerating progress toward better application of data. Across the 2 days of presentations and discussion, a compelling set of reoccurring themes emerged for follow-on attention. BOX S-2 Workshop Common Themes • Clarity on the basic principles of clinical data stewardship. • Incentives for real-time use of clinical data in evidence development. • Transparency to the patient when data are applied for research. • Addressing the market failure for expanding EHRs. • P ersonal records and portals that center patients in the learning process. • Coordinated EHR user organization evidence development work. • T he business case for expanded data sharing in a distributed network. • Assuring publicly funded data are used for the public benefit. • Broader semantic strategies for data mining. • Public engagement in evidence development strategies. Clarity on the basic principles of clinical data stewardship. The • starting point for expanded access and use of clinical data for knowledge development is agreement on some of the fundamental notions to guide the activities for all individuals and organizations with responsibility for managing clinical data. Workshop partici- pants repeatedly mentioned the need for consensus on approaches to such issues as data structure, standards, reporting requirements, quality assurance, timeliness, deidentification or security measures, and access and use procedures—all of which will determine the pace and nature of evidence development.

OCR for page 1
 CLINICAL DATA AS THE BASIC STAPLE OF HEALTH LEARNING Incentives for real-time use of clinical data in evidence devel- • opment. Current barriers to the real-time use of clinical data for new knowledge discussed at the workshop ranged from regulatory and commercial issues to cost and quality issues. Participants sug- gested the need for a dedicated program of activities, incentives, and strategies to improve the methods and approaches, their test- ing and demonstration, the cooperative decision making on priorities and programs, and the collective approach to regulatory barriers. Transparency to the patient when data are applied for research. • Patient acceptance is key to use of clinical data for knowledge development, and patient engagement and control are key to accep- tance. In this respect, clarity to individual patients on the structure, risks, and benefits of access to data for knowledge development was noted by participants as particularly important. Patient confidence and system accountability may be enhanced through transparent notification and audit processes in which patients are informed of when and by whom their information has been accessed for knowl- edge development. Addressing the market failure for expanding electronic health • records. Currently, market incentives are not enough to bring about the expansion of use of electronic health records necessary to make the point of care a locus for the development, sharing, and applica- tion of knowledge about what works best for individual patients. Shortfalls noted by participants included demand by providers or patients that is not sufficient to counter the expense to small organizations, competing platforms, and asynchronous reporting requirements that work against their utility for broad quality and outcome determinations, and that even the larger payers—apart from government—do not possess the critical mass necessary to drive broader scale applicability and complementarity. Deeper, more directed, and coordinated strategy involving Medicare lead- ership will likely be needed to foster such changes. Personal records and portals that center patients in the learn- • ing process. Patient demand could be instrumental in spreading the availability of electronic health records for improving patient care and knowledge development. Such demand will depend on much greater patient access to, comfort with, and regular use of programs that allow either the maintenance of personal electronic health records or access through a dedicated portal to their pro- vider-maintained electronic medical record. As noted during the workshop, many consumer-oriented products under development give patients and consumers more active roles in managing per-

OCR for page 1
 SUMMARY sonal clinical information. These may help to demonstrate value in the speed and ease of personal access to the information, better accommodate patient preference in care, and foster a partnership spirit conducive to the broader electronic health records (EHRs) application. Coordinated EHR user organization evidence development work. • The development of a vehicle to enhance collaboration among larger EHR users of different vendors was raised during the workshop as a means to accelerate the emergence of more standardized agreements and approaches to integrating and sharing data across multiple plat- forms, common query strategies, virtual data warehousing rules and strategies, relational standards, and engagement of ways to reduce misperceptions on regulatory compliance issues. The business case for expanded data sharing in a distributed • network. Demonstrating the net benefits of data sharing could promote its use. Benefits suggested by participants included cost savings or avoidance from facilitated feedback to providers on quality and outcomes; quick, continuous improvement informa- tion; and improved management, coordination, and assessment of patient care. Assuring publicly funded data for the public benefit. Federal and • state funds that support medical care and support insights into medical care through clinical research grant funding are the source of substantial clinical data, yet many participants observed that these resources are not yet effectively applied to the generation of new knowledge for the common good. Broader semantic strategies for data mining. Platform incompat- • ibilities for clinical data substantially limit the spread of electronic health records and their use for knowledge development. Yet dis- cussion identified strategies using alternative semantic approaches for mining clinical data for health insights, which may warrant dedicated cooperative efforts to develop and apply them. Public engagement in evidence development strategies. Generat- • ing a base of support for and shared emphasis on developing a healthcare ecosystem in which all stakeholders play a contributory role was noted by many participants as important for progress. Ultimately, the public will determine the broad acceptance and applicability of clinical data for knowledge development, under- scoring the importance of keeping the public closely involved and informed on all relevant activities to use clinical data to generate new knowledge.

OCR for page 1
 CLINICAL DATA AS THE BASIC STAPLE OF HEALTH LEARNING PRESENTATION AND DISCUSSION SUMMARIES Presentations at the Clinical Data as the Basic Staple of Health Learn- ing: Creating and Protecting a Public Good included perspectives from healthcare sectors and beyond on the current state of clinical data and data systems, the implications of healthcare data as a public good, and potential opportunities for improving their collection and use. These workshop pre- sentations served as the genesis of the papers that constitute the chapters that follow, and are summarized below. Clinical Data as the Basic Staple of Health Learning Clinical data consist of information ranging from determinants of health and measures of health and health status to documentation of care delivery. These data are captured for a variety of purposes and stored in numerous databases across the healthcare system. Advances in health infor- mation technology (HIT) and analytics raise the potential for these data to be used to fill substantial knowledge gaps in health care, but complicating the needed aggregation and use of these data are technical, cultural, and legal barriers. Although efforts are underway to address technical barriers and privacy concerns, many have suggested that a shift is needed to a data- sharing culture in which clinical data are considered a basic staple of health learning. Chapter 1 provides a brief overview of these issues and includes summaries of the context setting remarks of the workshop’s two keynote speakers. David Brailer’s presentation profiled current clinical data collec- tion and use, and offered his perspective on future applications that would improve care delivery, research, and health outcomes; and Carol Diamond offered her perspective on what might be possible if data were treated as a public good and identified several policy and technical issues important to achieving this vision. Clinical Data as the Basic Staple of the Learning Health System Brailer, Chair of Health Evolution Partners, was appointed in 2004 as the first national coordinator for health information technology. He served in that position until 2006. He described the potential of clinical data as a key building block for a learning health system by profiling the utility of clinical data currently available, as well as what might be possible if all data sources could be readily and reliably drawn upon for new insights into healthcare effectiveness. A significant gap exists between the potential utility of clinical data and how data are treated in the current healthcare market—where clinical information is proprietary and used for strategic

OCR for page 1
9 SUMMARY benefit. A question important for progress is whether clinical data are a public or private good. Brailer noted that significant progress has been made in the past few years to broaden adoption of HIT. Advances in HIT certification and stan- dardization efforts have produced portable health information and enabled exchange of significant volumes of information. Moreover, many hospitals have made progress in implementing electronic records, as have many phy- sicians, especially those in large group practices. Emphasizing the important role of engaging the public, Brailer discussed opportunities for HIT compa- nies such as Microsoft and Google to interact with the public and to raise the potential for data access and use for health improvement. Yet, misaligned incentives, based on current systems of reimbursement, and an outdated privacy paradigm currently hinder progress. Brailer sug- gested that the development of a framework for privacy that recognizes the dynamic, portable, and compounding nature of health information assets is a necessary first step to facilitating greater data sharing and use. A second major challenge is ensuring that information developed via data sharing efforts are truly useful to clinical care—and in this respect, there is a major tension between adoption and interoperability. Interoperability—or the capacity to share, integrate, and apply health information from disparate sources—has been the principal priority of the nation’s health informa- tion agenda. However, as the push for adoption gains momentum, there is potential for moving health information tools into broad use. This may not be best suited to also support the interoperability needed for a learning health system. Many aspects of the data and data systems essential for the develop- ment and assembly of coherent, representative, timely, and valid information that can inform decisions at patient or population levels are understood. However, leadership is needed to help maintain a focus on developing and using data to make health care smarter in the face of competing near-term priorities—especially given the many challenges faced by providers, pay- ers, and consumers in term of access and cost. Progress in efforts to make clinical data structured, intelligent, useful, assembled, and applied in a way that makes care better requires a sharper focus on data stewardship. Under one scenario, health information could become a true public good that is not proprietary; alternatively, clinical information could become a private good, used differentially for comparative advantage. Nothing in federal or state statutes, regulations, or other guidance confers control of health information to any data originator (e.g., pro- vider, hospital, manufacturers); yet, in practice, clinical information today is largely a private good, controlled by data producers. Brailer observed that the Health Information Portability and Accountability Act (HIPAA) enables de facto provider control over health information as patients can-

OCR for page 1
0 CLINICAL DATA AS THE BASIC STAPLE OF HEALTH LEARNING not direct that their information be sent to a third party, nor are providers obligated to make data available in a timely or convenient format. Other regulations also create barriers to portable, available, and acceptable health information. Brailer described the potential implications of proprietary use versus transparency of health information for health system stakeholders, and noted that it should be feasible to create a system in which providers can gain advantage from being performance driven, yet not gain advantage from exclusive use of health information as a private good. Ultimately, advancing the notion of clinical data as a public good is essential to a healthcare system that learns. Such efforts also offer the potential to extend the benefits of the information revolution—already experienced by many other industries—to health care by providing the power of choice to consumers. Brailer contended there is a limited window of opportunity available to achieve this end through technical and policy advances that make data more useful and valuable while also ensuring equitable access and maintaining a competitive marketplace. Clarification of data stewardship is needed to promote a shared understanding and trans- parency with respect to data control, ownership, and access. Vision for the Future: Creating a Public Good for the Public’s Health Carol Diamond, managing director of the Markle Foundation’s Health Program, delivered the keynote address on the second day of the workshop. She outlined a vision for clinical data positioned as a public good and provided guidance on the technical and policy issues required to build the public trust necessary to achieve this vision. The work of the public–private collaborative, Connecting for Health (CFH), was discussed to illustrate key opportunities to develop a health information sharing environment that seeks to improve the quality and cost effectiveness of health care. The work of CFH to improve how information is used to address research, public health, and quality measurement was emphasized. Achieving population health goals requires analysis, decision sup- port, and feedback loops embedded throughout the system. However, as revealed by the significant challenges of collecting, cleaning, and analyzing health data for existing data reporting demands, progress will require a new approach to collecting, accessing, and using health information. To guide system development, Diamond suggested the need to consider three central requirements for responsible information policies: fulfilling seven core privacy principles (openness and transparency, purpose specification, collection and use limitation, individual participation and control, data integrity and quality, and security safeguards and controls); ensuring sound network design; and enabling accountability and oversight. As the needs of information users constantly evolve, Diamond also raised the importance

OCR for page 1
 SUMMARY of developing a flexible information technology architecture that is adapt- able to different users, data sources, and research methods. A vision for a 21st-century approach to information sharing for public health was illus- trated through nine “First Principles for Population Health”: (1) designed for decisions; (2) designed for many; (3) shaped by public policy goals and values; (4) boldly led, broadly implemented; (5) possible, responsive, and effective; (6) distributed, but queriable; (7) trusted through safeguards and transparency; (8) layers of protection; and (9) accountability and enforce- ment of good networking citizenship. To convey the potential impact of a 21st-century vision for data, Diamond offered three scenarios for how decision making by providers, consumers, and policy makers might be enhanced by broader access to information grounded in reliable evidence. Realizing this vision will require moving to a new paradigm for health information in which, instead of col- lecting data in centralized databases for research, questions are brought to the data. Such an approach would emphasize the specific information needs of decision makers; a networked approach that supports efficient research analyses and allows data to remain distributed; and greater involvement of consumers as participants and producers of information. U.S. Healthcare Data Today: Current State of Play The first set of workshop sessions provided an overview of existing healthcare data—the sources, types, accessibility, and uses in the United States. In an exploration of example initiatives in the current healthcare marketplace that collect and use these data, presentations considered fac- tors motivating the work and profiled elements of the system from different perspectives. Issues considered included the accessibility of data for new clinical insights, the extent of current uses of clinical data, and barriers to the advancement of next-generation data applications. The manuscripts in Chapter 2 reflect opportunities present within the current healthcare data profile to assess and manage clinical outcomes, as well as to glean new healthcare insights through the use of data from public and private sources. Current Healthcare Data Profile When discussing elements associated with evidence-based medicine or when defining the data or the taxonomies regarding health and health care, the healthcare community does not always consider all of the potential effects on health. As evidence-based medicine is more fully adopted, it will be important to evaluate all facets of evidence development and application necessary to transform health care. Simon P. Cohn, chair of the National

OCR for page 1
2 CLINICAL DATA AS THE BASIC STAPLE OF HEALTH LEARNING times directs information engineers to pursue certain tactics. For example, the commonality of molecular data might drive the desire to have all related information in one data pool, so that a researcher could search all the data comprehensively, perhaps not even with a specific goal in mind. This could lead to the kind of serendipitous connection that is fundamen- tal to the nature of discovery. At the same time, however, there must be a balance toward collecting only those pieces of data that make sense in a universal way. The NIH has required researchers to pool data collected under NIH grants so that other investigators might benefit from those data. NIH cre- ated dbGaP to archive and distribute the results of studies that have inves- tigated the interaction of genotype and phenotype. Such studies include genome-wide association studies, medical sequencing, and molecular diag- nostic assays, as well as association between genotype and nonclinical traits. The advent of high-throughput, cost-effective methods for genotyping and sequencing has provided powerful tools that allow for the generation of the massive amounts of genotypic data required to make these analyses possible. dbGaP incorporates phenotype data collected in different studies into a single common pool so the data can be available to all researchers. Dozens of studies are now in the database, and by the end of 2008, the database was expected to hold data on more than 100,000 individuals and tens of thousands of measured attributes. Hundreds of researchers have already begun using the resource. There is also a movement on the part of the major scientific and medical journals to require deposition accession numbers when they publish the types of studies alluded to above, the same as required for DNA sequence data. The publications recognize the importance of other people being able to confirm or deny a paper’s conclusions, which requires investigators to review the data that informed the paper. To further encourage secondary use of data, other accession numbers are used when people take data out of a database, reanalyze the data, and then publish their analysis. Professional organization-sponsored data. Guidelines and performance measures in cardiology developed by the American College of Cardiology (ACC), often in association with the American Heart Association, typically are adopted worldwide. ACC Chief Executive Officer Jack Lewin described ongoing efforts to ensure that ACC guidelines, performance measures, and technology appropriateness criteria are adopted in clinical care, where they can benefit individual patients. Although most guidelines are currently available on paper, the vision is to have clinical decision support integrated into EHRs. The ACC’s National Cardiovascular Data Registry (NCDR) was designed to improve the quality of cardiovascular patient care by providing

OCR for page 1
 SUMMARY information, knowledge, and tools; benchmarks for quality improvement; updated programs for quality assurance; platforms for outcomes research; and solutions for postmarket surveillance. The NCDR strives to standardize data and to provide data that are relevant, credible, timely, and actionable, and to represent real-life outcomes that help providers improve care and that help participants meet consumer, payer, and regulator demands for quality care. The NCDR’s flagship registry, the national CathPCI Registry, is considered the gold standard for measuring quality in the catheteriza- tion laboratory. Other NCDR registries collect data on acute coronary syndrome, percutaneous coronary interventions, implantable cardioverter defibrillators, and carotid artery revascularizations. The ACC is currently working to standardize registry data to be able to measure gaps in perfor- mance and adherence to guidelines, with an ultimate goal of being able to teach how to fill those gaps and thus create a cycle of continuous quality improvement. Mandates from Medicare and states have pushed hospitals to use the ACC registries, but there is room for wider adoption. The ACC is working to alleviate barriers such as the need for standardization, the expense of collecting needed data, and the lack of clinical decision support processes built into EHRs. The ACC would also like to see a national patient identi- fier that would enable the tracking of an individual’s overall health con- tinuum while preserving patient privacy; such an identifier would bolster longitudinal studies. The ACC believes wider adoption of data sharing via registries is within reach, should be encouraged, and would ultimately result in better health care overall, but that strategies need to be developed and implemented that foster systems of care versus development of data collec- tion mechanisms specific to a single hospital. Toward the development of business strategies needed to develop the clinical decision support capac- ity, standardization, and interoperability, the ACC wants to collaborate with other medical specialties, EHR vendors, the government, insurers, employers, and other interested parties. Going forward, the ACC supports investment in rigorous measurement programs, advocating for government endorsements of a limited number of data collection programs, allowing professional societies to help providers meet mandated reporting require- ments, and implementing systematic change designed to engage physicians and track meaningful measures. Product development and testing data. The pharmaceutical industry col- lects and shares a great deal of clinical data. Because the industry is heavily regulated, the data it collects are voluminous and made available publicly under strict regulations that, it is hoped, ensure their accuracy and the accuracy of their interpretations. Eve Slater, senior vice president for world- wide policy at Pfizer, noted that the pharmaceutical industry is interested

OCR for page 1
 CLINICAL DATA AS THE BASIC STAPLE OF HEALTH LEARNING in ensuring the widespread availability of data to support research at the point of patient care and care at the point of research. In the pursuit of that goal, the industry is interested in pursuing the alignment of data quality, accessibility, integrity, and comprehensiveness. An influx of regulations and an acknowledged need for transparency are prompting the appearance of product development and testing data in the public domain. Nonetheless, attention is needed to ensure data standards, integrity, and appropriate, individualized interpretation. Although significant amounts of product development data are required by law to be in the public domain, roadblocks prevent the effective sharing of clinical data. In the area of clinical trials posted on www.clinicaltrials. gov, for example, shared information can be incomplete, duplicative, and hard to search, and nomenclature is not always standardized. The infor- mation also needs to be translated into language that patients can under- stand. The lack of an acceptable format for providing data summaries for the public is linked to concerns about disseminating data in the absence of independent scientific oversight; once data are in the public domain, controlling quality assurance and the accuracy with which the information is translated to patients become difficult. Policies to address some of these issues lag behind the actual availability of data. These issues argue in support of the data-sharing and standardization principles that the IOM has articulated. The Clinical Data Interchange Stan- dards Consortium (CDISC) and other organizations are currently focused on the issues of standardizing electronic data. Regulatory policies to promote sharing. Although large repositories now exist for controlled clinical trial data, including primary data, Janet Woodcock, deputy commissioner and chief medical officer at the FDA, observed that much of that information unfortunately resides on paper in various archives, not in an electronic form that would readily enable sharing. The FDA’s Critical Path Initiative is an aggressive attempt to be able to combine research data from the various clinical trials in different ways and to extend learning beyond a particular research program. The FDA has been working with the CDISC to try to standardize as many data elements as possible. Several years ago, the FDA established the ECG Warehouse, an anno- tated electrocardiogram (ECG) waveform data storage and review system, for which a standard was established for a digital ECG. The FDA asked companies engaged in cardiac safety trials to use that standard. Today the ECG Warehouse holds more than 500,000 digital ECGs along with the clinical data, and the FDA is collaborating with the academic community to analyze those data to learn new knowledge that would not have been accessible before the development of a standardized dataset. The FDA is constructing quantitative disease models from clinical trials

OCR for page 1
 SUMMARY data, building electronic models that incorporate the natural history of the disease, performance of all the different biomarkers about the disease over time, and results from interventions. Given multiple interventions, the approach allows researchers to model quantitatively. The FDA expects more of these models to evolve in the future. Within the Critical Path Initiative, the FDA worked with various phar- maceutical companies to pool all their animal data for different drug-induced toxicities, before the drugs are given to people. This groundbreaking con- sortium worked to cross-validate all the relevant biomarkers in each other’s laboratories. The first dataset, on drug-induced kidney toxicity in animals, has been submitted to the FDA and is under review. Similar approaches could be undertaken with humans; pooling those data from various sources could lead to new knowledge. The FDA also plans to build a distributed network for pharmaco- vigilance. The Sentinel Network seeks to integrate, collect, analyze, and disseminate medical product (e.g., human drugs, biologics, and medical devices) safety information to healthcare practitioners and patients at the point of care. Required under the 2007 Food and Drug Administration Amendments Act (FDAAA), the Sentinel Network is currently the focus of discussions by many stakeholders about how best to proceed. One approach is to build a secure distributed network in which data stay with the data owners, but are accessible to others. Legislative change to allow sharing. The Center for Medical Consumers, a nonprofit advocacy organization, was founded in 1976 to provide access to accurate, science-based information so that consumers could participate more meaningfully in medical decisions that often have profound effects on their health. Arthur Levin, the center’s cofounder and director, believes government has a role to play in regulating the healthcare sector; key ques- tions in this arena concern what government can and cannot do, and what it should and should not do. Legislatively, most of the action concerning data sharing is currently in the states. Levin noted that we may face a scenario similar to that with managed care legislation, where in the absence of federal legislation, states moved ahead on their own, for better or worse. Currently states are moving ahead rapidly with HIT and health information exchange. Issues of privacy and confidentiality are very much in the forefront and driving state legisla- tion. In terms of legislation covering data sharing, we need to make sure that whatever policy is developed moves things in an agreed-upon direc- tion that does not create new obstacles and barriers. A first step will be to develop a much better understanding of what barriers exist in the states and federal government to aggregating data for research, quality improvement, and similar goals.

OCR for page 1
 CLINICAL DATA AS THE BASIC STAPLE OF HEALTH LEARNING Another issue is that data sharing is, in essence, a social contract between individuals and researchers who want to use their data. Patients are told there will be some payoff from sharing data, but perhaps patients do not hear enough about how that is supposed to happen. Where does the payoff come? How does the other side of that contract deliver? What are the deliverables? Is there a time line for those deliverables? Is there accountability for those deliverables? As part of the social contract, there should be a burden on col- lecting data, a requirement that the collector do something specific with the data being collected. Privacy and confidentiality rules and remedies can be legislated; however, trust must be built. All who believe that data represent a public good—and that data sharing is a public responsibility to advance the public interest in improving healthcare quality, safety, and efficacy—also understand that such a message may not resonate so readily with the public. The public has not yet been brought up to that level, and more is needed to engage consumers in this enterprise. Engaging the Public The final session of the workshop examined the public’s role in improv- ing the clinical data utility, considering how the public currently views the use of clinical care data for research, what types of information the public is interested in deriving from such research, and how that interest might influence public response to future developments in the use of health infor- mation. The session further considered what technical, communication, and demonstration-of-value advances might help address the concerns of healthcare consumers. As summarized in Chapter 7, participants provided an overview of public knowledge, issues, concerns, and discussion of strat- egies on public understanding, engagement, and support for the changes necessary to create the next-generation public data utility. Also discussed were the design and implementation of tools that would be enhanced by wider availability of clinical data—such as those that help improve patient access and use of information from, about, and by those who are dealing with similar circumstances. Finally, the nature and potential use of personal health records, safeguards for data access and entry, and possible influence on public perceptions about privacy and data use were considered. Generating Public Interest in a Public Good In many respects, the greatest challenge associated with establishing a medical care data system to serve the public interest lies in the fact that such data largely reside in the private sector, where commercial interests and other factors inhibit sharing. This paradigm has benefited discrete entities, but it has failed to serve the public health interests of the broader

OCR for page 1
 SUMMARY U.S. population or to promote awareness of how such information can be used to improve clinical decision making at the individual level. Though the public should have considerable interest in this information, the limitations of the data system as currently structured severely inhibit demonstration of the value proposition for consumers, both individually and collectively. Alison Rein, senior manager at AcademyHealth, identified key issues to be addressed to develop public awareness and perception of medical care data use for public good applications. She provided an overview of what little is known about this domain from the public’s perspective; discussed some assumptions and attitudes that may impede progress in this direction; and highlighted examples from which we might learn and share strategies for generating public interest. Rein discussed the public’s limited understanding of how their clini- cal data move within or outside our fragmented system and the conse- quences for discussions about data access and data protection and security. Although lessons might be learned from other industries’ transition to electronic systems for data management, the public expectation of trust and privacy between providers and patients, as well as the potential for irrevocable harm inherent to health care, enhance the challenge. Progress will require public education, outreach, and the demonstration of value in the use of health data. Generating interest in electronic access to personal health information might help overcome market obstacles related to sequestering data for pro- prietary interests. However, Rein suggested that until greater regulation is put in place to compel providers and healthcare institutions to share data appropriately, use of clinical data for the public good will remain con- strained. Efforts should also be made to align public and research interests toward pursuing common goals and helping the public develop a deeper appreciation for research as a public good. Public demonstration of the value of data sharing might help in this regard—showing, for example, the potential impact of clinical data on personal lifestyle, the bottom line, or other endpoints of interest to the public. Possible approaches to demon- strating the value of research as a public good included expanded reporting of limited, but meaningful, clinical health data to public health entities; the enhancement and expansion of clinical data registries; and the development of a nationwide health tracking network that could yield information of value to researchers, the public health community, providers, policy makers, and consumers. Implications of “Patients Like Me” Databases The longstanding tension between an individual’s desire for personal- ized information and the population’s interest in healthcare research is

OCR for page 1
 CLINICAL DATA AS THE BASIC STAPLE OF HEALTH LEARNING exacerbated by scientific advances such as molecular profiling, information sharing on the web, and modern data management tools. Both the public and private sectors are struggling to navigate this logistically challenging landscape to gain medical insights and occasionally to monetize these insights. Patient-focused clinical trial information services created in the past decade provide a unique view of how patients feel about healthcare research at both the individual and the population level. Courtney Hudson, chief executive officer and founder of EmergingMed, provided an over- view of EmergingMed, a company that helps cancer patients gain access to clinical trials and search for treatment options. Hudson discussed how this service addresses the intersection of an individual’s need for informa- tion, access, and transparency with the U.S. healthcare system’s desire for population-based research and data sharing in light of modern data man- agement and data-sharing capabilities. Patients in this country support mining clinical databases for the good of public health and for learning, and they believe overwhelmingly that it already happens. Patients seek information to inform treatment decisions, and Hudson indicated it would be unconscionable to not provide as much information as we have available in the public domain to possibly help each patient. As ways to use and aggregate public datasets are developed, it would be extremely difficult ethically to justify any decision to withhold information from patients. Similarly, Hudson highlighted the concept of promoting evidence-based medicine and garnering public approval and cooperation in terms of the potential benefit to the public, rather than the public understanding of research. Transparency and trust were also empha- sized. The more transparent the system, the more likely patients’ trust is gained. Regarding the informed consent process, a basic ethical concern is that the clinical trials system as it stands today has a narrow definition of informed consent. Hudson encouraged workshop participants to consider ways to provide context, full disclosure, or transparency to patients or to inform them about the larger process. A key distinction in considering the patient’s point of view might be to view clinical data utilities in terms of patient-driven solutions versus system-driven solutions. Implications of Personal Health Records Dramatic increases in medical information and increases in consumer access to information via the Internet, are making health care one of the most significant hot spots for technology innovation today. Currently the practice of medicine suffers from an information management problem. Control will eventually shift, moving the current top-down doctor-patient relationship to one that is characterized by mutual control. For physicians, the issue is about aggregating data within and across provider organiza-

OCR for page 1
9 SUMMARY tions, and for consumers it is about aggregating health data across all of their sources. Ultimately, these views will connect to enable informed health decisions and better clinical outcomes. Today, we have more personal health data than ever; however, the data are dispersed over a variety of facilities, providers, and even our own monitoring devices and home computers. As described by Jim Karkanias, partner and senior director of applied research and technology at Microsoft Corporation, Microsoft is working to address gaps in the healthcare data management system, both from an enterprise and a consumer standpoint, to enable a more connected, informed, and collaborative healthcare ecosystem. Microsoft HealthVault, a consumer health platform with specialized health search capabilities, deliv- ers a platform that puts users in control of their information so they can access, store, and recall it on demand. Karkanias indicated that such a level of access and control contributes to the ability to make good decisions. The platform is built on the premise that the consumer is at the center of health care, so patients are the logical aggregators of this information. HealthVault seeks to help patients to proactively manage their own health care—substituting, for example, costly visits to a doctor’s office with daily in-home monitoring to allow for proactive measures to be taken as they can be detected. Chronic conditions and more serious illnesses could be handled proactively. With appropriate privacy consents, a care- giver could have a full view of a patient’s underlying data; others could be granted access to different parts of that same data—an approach useful, for example, to adult children caring for their parents from afar. CLINICAL DATA AS THE BASIC STAPLE OF HEALTH LEARNING: IDEAS FOR ACTION The availability of timely and reliable evidence to guide healthcare decisions depends substantially on the quality and accessibility of the data used to produce the evidence. Important information about the results of different diagnostic and treatment interventions is collected in multiple forms by many institutions for different reasons and audiences—providers, patients, insurers, manufacturers, health researchers, and public agencies. Medical care data represent a vital resource for improving insight and action for more effective treatment. With the increasing potential of technical capacity for aggregation and sharing of data while ensuring confidentiality, the prospects are at hand for powerful and unprecedented tools to determine the circumstances under which medical interventions work best, and for whom. However, these data are usually held in a proprietary manner instead of being considered a public good that can be pooled and mined for new research and, ultimately, better patient care and outcomes. There are a number of challenges to the use of such

OCR for page 1
0 CLINICAL DATA AS THE BASIC STAPLE OF HEALTH LEARNING data—coding discrepancies, platform incompatibilities, patient protec- tion tools—yet practical approaches are and can be developed to contend with these issues. The most significant challenge may be the barriers and restrictions to data access inherent in treating clinical outcome data as a proprietary commodity. Chapter 8 summarizes the themes emerging from workshop discussion and opportunities for follow-up action by the Roundtable. Key issues dis- cussed include clarifying basic principles of data stewardship; creating next- generation data utilities and models; creating next-generation data policy; and engaging the public. Potential opportunities for follow-up attention by the members of the IOM Roundtable on Value & Science-Driven Health Care include those noted below—Roundtable Innovation Collaboratives already engaged in related follow-on work are indicated in parentheses. 1. Principles: Foster the development, review, and implementation of basic principles for data stewardship. 2. Use of electronic health records for knowledge deelopment: Con- vene an affinity group of EHR users and vendors to consider approaches to cooperative work on knowledge development, including issues related to standards and rules for governed data query and application (EHR Innovation Collaborative). 3. Collaboratie data mining: Organize exploratory efforts to inves- tigate cutting-edge data-mining techniques for generating evidence on care practices and research (EHR Innovation Collaborative). 4. Incenties: Convene an employer–payer workgroup to explore the use of economic incentives to reward providers/groups work- ing to improve knowledge generation and application in the care process. 5. Priacy and security: At the conclusion of a current IOM study on HIPAA and privacy protection regulations, convene a series of meetings to explore and clarify definitions as well as reduce the ten- dency toward unnecessarily restrictive interpretations, in particular as they relate to data sharing and secondary uses. 6. Transparency and access to federal data: Explore the marketplace for data, opportunities to enhance data sharing, governance/ stewardship issues, and ways to make federally sponsored clinical data widely available for secondary analysis. This includes not only data from federally supported research but also Medicare-related data, including from Part D (pharmaceutical) use. 7. Public inolement in the eidence process: Engage the public through communication efforts aimed at increasing public under- standing and involvement in evidence-based medicine (Evidence Communication Innovation Collaborative).

OCR for page 1
 SUMMARY REFERENCES Arrow, K., J. Bertko, S. Brownlee, L. P. Casalino, J. Cooper, F. J. Crosson, A. Enthoven, E. Falcone, R. C. Feldman, V. R. Fuchs, A. M. Garber, M. R. Gold, D. Goldman, G. K. Hadfield, M. A. Hall, R. I. Horwitz, M. Hooven, P. D. Jacobson, T. S. Jost, L. J. Kotlikoff, J. Levin, S. Levine, R. Levy, K. Linscott, H. S. Luft, R. Mashal, D. McFadden, D. Mechanic, D. Meltzer, J. P. Newhouse, R. G. Noll, J. B. Pietzsch, P. Pizzo, R. D. Reischauer, S. Rosenbaum, W. Sage, L. D. Schaeffer, E. Sheen, B. M. Silber, J. Skinner, St. M. Shortell, S. O. Thier, S. Tunis, L. Wulsin, Jr., P. Yock, G. Bin Nun, S. Bryan, O. Luxenburg, and W. P. M. M. van de Ven. 2009. Toward a 21st-century health care system: Recommendations for health care reform. Annals of Internal Medicine 150(7):493–495. Blumenthal, D., E. G. Campbell, M. Gokhale, R. Yucle, B. Clarridge, S. Hilgartner, and N. A. Holtzman. 2006. Data witholding in genetics and the other life sciences: Prevalence and predictors. Academic Medicine 82(2):137–145. Detmer, D. E. 2003. Building the national health information infrastructure for personal health, health care services, public health, and research. BMC Medical Informatics and Decision Making 3(1):1–40. Editorial. 2005. Let data speak to data. Nature 438:531. Health care spending in the United States and OECD countries. 2007. http://www.kff.org/ insurance/snapshot/chcm010307oth.cfm (accessed July 14, 2008). Hrynaszkiewicz, I., and D. Altman. 2009. Towards agreement on best practice for publishing raw clinical trial data. Trials 10(17). IOM (Institute of Medicine). 2009. Beyond the HIPAA Priacy Rule: Enhancing priacy, improing health through research. Washington, DC: The National Academies Press. Ness, R.B. 2007. Influence of the HIPAA Privacy Rule on health research. Journal of the American Medical Association 298(18):2196–2198. NRC (National Research Council). 2009. Computational technology for effectie health care: Immediate steps and strategic directions. Washington, DC: The National Academies Press. Piwowar, H. A., M. J. Becich, H. Bilofsky, and R. S. Crowley. 2008. Towards a data sharing culture: Recommendations for leadership from Academic Health Centers. PLoS Medicine 5(9) e183. Safran, C., M. Bloomrosen, W. E. Hammond, S. Labkoff, S. Markel-Fox, P. C. Tang, D. E. Detmer, with input from the expert panel. 2007. Toward a national framework for the secondary use of health data: An American Medical Informatics Association white paper. Journal of the American Medical Informatics Association 14(1):1–9. http://www. healthlawyers.org/Members/PracticeGroups/HIT/Toolkits/Documents/5_Health_Data_ AMIA_Summary.pdf (accessed August 18, 2008).

OCR for page 1