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 on which to base findings and conclusions. Information about the results of 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. These medical care data represent a vital resource for improving insight and action for more effective treatment. With the increasing technical potential for aggregation and sharing of data while ensuring confidentiality, the prospects are at hand for powerful and unprecedented tools for data analysis and determination of the circumstances under which medical interventions work best, and for whom. Although many challenges exist to the use of such data—coding discrepancies, platform incompatibilities, patient protection tools—as evident throughout this publication, practical approaches can be developed for most. The most significant challenge may be the barrier to data access and the restrictions in treating clinical outcome data as a proprietary commodity. This chapter summarizes the workshop discussions on principles, opportunities, strategies, and projects as possible follow-up actions for Roundtable engagement.
Across the 2 days of presentations and discussion, several common themes—listed in Box 8-1 and elaborated below—emerged as issues for particular attention in accelerating progress in the availability and use of clinical data for new insights.
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 participants repeatedly mentioned the need for consensus on approaches to such issues as data structure, standards, reporting requirements, quality assurance, timeliness, deidentification or security measures, access, and use procedures—all of which will determine the pace and nature of evidence development.
Incentives for real-time use of clinical data in evidence development. 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 suggested the need for a dedicated program of activities, incentives, and strategies to improve the methods and approaches, their testing and demonstration, the cooperative decision making on
Workshop Common Themes
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 acceptance. 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 knowledge development.
Addressing the market failure for expanding electronic health records. Currently, market incentives are inadequate 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 application 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 the reality that even the larger payers—apart from government—do not possess the critical mass necessary to drive broader scale applicability and complementarity. It will likely take a deeper, more directed, and better coordinated strategy involving Medicare leadership to foster such changes.
Personal records and portals that center patients in the learning 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 upon 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 provider-maintained electronic medical record. As noted during the workshop, many consumer-oriented products currently under development give patients and consumers more active roles in managing personal clinical information, and they may help to demonstrate value in the speed and ease of personal access to the information, to better accommodate patient preference in care, and to foster a partnership spirit conducive to the broader EHR 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 platforms, 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 information; and improved management, coordination, and assessment of patient care.
Using publicly funded data for the public benefit. Federal and state funds that support medical care, as well as 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.
Broader semantic strategies for data mining. Platform incompatibilities for clinical data substantially limit the spread of electronic health records and their use for knowledge development. Yet discussion 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. Generating 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, underscoring the importance of keeping the public closely involved and informed on all relevant activities to use clinical data to generate new knowledge.
ISSUES AND OPPORTUNITIES
Workshop discussions touch on various issues and opportunities to improve the clinical data utility. These related to notions summarized below on clinical data stewardship, clinical data infrastructure, incentives for data sharing, creating the next generation data utilities and models, creating next generation data policies, and engaging the public.
Frequently expressed throughout the workshop were the beliefs that
new clarity, new thinking, new practices, and perhaps new regulations are needed broadly across a range of issues related to data stewardship. Expanded access and use of clinical data for knowledge development should begin with efforts to build consensus on guiding principles for the individuals and organizations who manage clinical data. Issues that were raised as particularly important to progress included data structure, standards, reporting requirements, quality assurance, timeliness, deidentification and other security measures, and access and use procedures.
Positioning Data as a Public Good
Emphasized in several presentations was the notion that understanding data ownership is central to considering data as a public good. Although data ownership is complex and highly nuanced, one consideration advanced focused on whether data are rightfully owned by those who provide the data—that is, patients—or those who collect and maintain the data. Similarly, a question repeatedly raised was whether data, if collected with public funds, should be considered part of the public domain. Data ownership is further complicated when data are deidentified and recollated for secondary use. The pressing needs expressed during discussion to clarify data ownership and to conceptualize new models for data stewardship present a compelling set of challenges. If an overarching goal is to make data more readily available and accessible for informing medical decision making, new solutions need to be identified and implemented to ease the tensions inherent in data ownership.
A significant challenge noted by participants is the need to break down barriers to data access based in assumptions and practices that treat clinical outcome data as a proprietary commodity. A paradigm shift might change assumptions that data are a commodity to be traded in a competitive marketplace into more open and supportive thinking about practices and policies that make clinical data more portable, transparent, and contributory to better health care. In discussions on the nature of clinical data, participants suggested that these data seem to exist in a gray area between a public and private good—and it is precisely in that gray area that considerable energies are needed to establish new definitions concerning the use of data for today’s healthcare market.
Data for Improvements at the Point of Care
Ultimately, the utility of data is dependent on its application. As one workshop speaker said, it is important to “be able to take information drawn from actual experience in care delivery to be able to shape that process.” For example, although strong progress has been made in understand-
ing disease and prevention, apart from filling the gaps in the evidence base, considerable delays persist in applying the knowledge to improve actual patient care. Part of the delay may be related to current approaches to using clinical data, which historically involved collecting, cleaning, and then—to some extent—hoarding data. Participants noted several key shortfalls of this approach. Separate repositories tend to be created for every specific purpose at great cost in both money and time. Privacy and security vulnerabilities are created due to multiple redundancies of large datasets and an absence of connectivity. Restrictions on data have the cumulative effect of precluding the ability of many people to use these data to make better decisions. Notably, exclusive and proprietary treatment of data effectively keeps the consumer and patient out of the equation. Furthermore, as many participants noted, in the current paradigm, by the time one collects and cleans data, the original research question or topic has often changed.
A new action agenda, one that is open to resetting some definitions and assumptions of health data and research approaches, was suggested as a first step toward the next generation of data translation and to positioning clinical data resources so that they contribute more readily and directly to effective health care. Progress might also depend on a fundamental shift in perspective. For example, instead of looking at how to achieve public health objectives from a data perspective, progress may require approaching issues and opportunities in evidence collection from the perspectives of medical decision makers, defined broadly to include providers, consumers, payers, and policy makers. Such a model for the clinical data utility would start in a climate of trust, with a policy framework that enables information liquidity. It would engage stakeholders in a constructive forward-looking process that prioritizes creating value for the participants and involves and rewards consumers for participating. It would focus on the infrastructure requirements to push more questions to the data as opposed to trying to bring all the data to every question. The vision put forth by many at the workshop was one in which research is a normative part of health care and in which every intervention with a patient presents an opportunity for learning.
Incentives for Data Sharing
Clarifying the business case for data sharing is one significant dimension of the economics of clinical data. Many participants noted the challenge and need for articulating a value proposition that clarifies the potential economic and health returns for the investment—for individual patients, for individual organizations that hold data, and for society as a whole. Unless overcome, the market obstacles related to sequestering data for proprietary interests and the technical obstacles related to individual identification
authorization and related issues will continue to compromise efforts to improve clinical data. Workshop presentations highlighted several opportunities for expanded data sharing to increase the value of healthcare delivered. More feedback to providers on quality and outcomes could provide incentives for those who collect data. The pay-off for patients could be measured through continuous improvement data, improved management and coordination of patient care, and possible cost savings. Similarly, the broad ability to share results from clinical and research data may reduce or avoid costs associated with clinical trials, as well as care delivery and patient management. Collaborative efforts to find new incentive aproaches that meet the multiple, often conflicting needs of diverse stakeholders will be important to facilitate data sharing.
Access to Data
Throughout the workshop, the need for increased access to a wider sample of clinical data called for new models that promote data sharing in both the public and private sectors. For the private sector, new incentives might encourage broader sharing of data in the marketplace. One area highlighted in the workshop focuses on data that are collected with public funds. Federal and state funds that support medical care as well as clinical research represent a source of substantial clinical data, yet participants repeatedly observed that these data are not effectively applied toward the generation of new knowledge. Government agencies that distribute funds to support such data collection have established guidelines and regulations designed to foster more data sharing, but an ethos committed to data sharing remains elusive. More aggressive enforcement of government regulations on privacy and funding was offered as a possible next step to encourage broader data sharing.
The model of the Human Genome Project was offered as an example of the benefit of open data sharing, as were the public registration of clinical trials and the growth of new models of disclosure/publication of research results in open-access journals and digital repositories. Expanded access and use, though, go hand in hand with clarity, assurance, and transparency as to security safeguards and nature of health research processes.
Creating Next-Generation Data Utilities and Models
Potential solutions to the tensions around data ownership and stewardship come in many forms, including ideas and models for next-generation data utilities. Broadly speaking, the goals of the approaches suggested by participants are to find utilities that align data quality, standards, integrity, accessibility, and comprehensiveness, and that offer quick, open sharing
of data. Pathways are also needed that enable appropriate, individualized interpretation of data, and that appropriately translate information for patients.
Models of Note
Federal agencies are developing a number of utilities that can help make data—often large pools of data—more broadly and readily accessible, and that serve as potentially replicable models for further development. The National Institutes of Health (NIH), for example, requires researchers to pool data collected under NIH grants so that other investigators might benefit from those data. The NIH created the database of Genotypes and Phenotypes (dbGaP) to archive and distribute the results, for example, of genome-wide association studies. Significant amounts of product development data are required by law to be in the public domain. The more than 50,000 trials registered at www.clinicaltrials.gov also provide rich data resources. The Food and Drug Administration (FDA) registration approval process deriving from the Food and Drug Administration Amendments Act of 2007 will ensure the posting of more clinical summary data. The Cancer Biomedical Informatics Grid (caBIG) program was launched by the National Cancer Institute to connect the cancer research community to more easily share information and to build or adapt tools for collecting, analyzing, integrating, and disseminating data. The Centers for Medicare & Medicaid Services (CMS) has developed The Coverage with Evidence Development program to require the delivery of clinical data over and above the typical claims data as a provision for payment for certain services. Such an approach has the potential to provide significant amounts of information if we can learn how to meet the challenge of what we can do with data that have been collected, and merge those data with other sources of data so that data collection can inform clinical practice. The development of such approaches, which seek to make data in the government’s domain more readily and openly accessible, could be expanded across all of the government—and serve as models for the private sector.
Efforts to develop next-generation data utilities are occurring in multiple loci. The model presented at the meeting of registries developed by medical disciplinary societies hold promise for the future, and their further development should be encouraged and supported. The American College of Cardiology’s (ACC’s) National Cardiovascular Data Registry (NCDR), for example, collects data for measuring quality in the catheter-ization laboratory and on acute coronary syndrome, percutaneous coronary interventions, implantable cardioverter defibrillators, and carotid artery revascularizations. NCDR registries were designed to improve the qual
ity of cardiovascular patient care by giving cardiologists wide access to information, knowledge, and tools; benchmarks for quality improvement; updated programs for quality assurance; platforms for outcomes research; and solutions for postmarket surveillance. Mandates from Medicare and states have pushed hospitals to use the ACC registries, but there is room for wider adoption of such approaches.
Electronic Health Records
A central emphasis in presentations was the need for much more developmental work to address the issues of basic technology, interoperability, and standardization of terminology that currently impede the sharing of knowledge via EHRs. A vehicle to enhance collaboration among larger EHR users of different vendors may accelerate the emergence of the fol-lowing: (1) more standardized agreements and approaches to integrating and sharing data across multiple platforms; (2) common query strategies; (3) virtual data warehousing rules and strategies; (4) relational standards; and (5) engagement of ways to reduce misperceptions on regulatory compliance issues. A potential area of action would be to convene an affinity group of EHR stakeholders to consider approaches to cooperative work on knowledge development, including issues related to standards and rules for governed data query.
There was also the sense that correction is needed to what is perceived as a market failure for expanding electronic health records. As evidenced by participant observations such as the insufficient demand by providers or patients in the face of the considerable expense of EHR adoption to small organizations, and challenges related to the diversity of platforms and reporting requirements, market incentives have not resulted in the large-scale EHR adoption needed. A particular emphasis in discussions was the notion that apart from government, no stakeholder group has the critical mass necessary to drive the broad-scale adoption, application and complementarity of EHR systems and a more focused strategy, perhaps involving Medicare leadership, is needed for progress.
One impediment to the use of EHRs for data aggregation was illustrated through the experience of one disciplinary association, which found that early adoption of EHRs among physicians may not have as much to do with quality, e-prescribing, or population management as with day-to-day business management concerns. Broader thinking about the potential and use of EHRs is needed to achieve widespread data aggregation at any level other than administrative data.
Patient-Focused Approaches to Clinical Data
Patient demand was viewed by many participants as an important strategic consideration for efforts to accelerate broad adoption and use of EHRs to improve patient care and knowledge development. Such demand may be boosted by greater patient use of programs that facilitate access to or maintenance of personal electronic health records. Several consumer-oriented products—currently deployed or under development—were presented at the workshop as emerging services that seek to enable patient and consumer engagement in clinical information management. Participants noted several potential impacts of these tools on patient care, including thedemonstration of the value in the speed and ease of personal access to the information, better accommodation of patient preference in care, and fostering a partnership spirit conducive to broader EHR application.
Patient engagement and control is key to enabling broader use of clinical data for knowledge development. One suggested approach to investing patients in the process is to guarantee transparency when data are provided for research. Clarity should extend to issues such as the structure, risks, and benefits of access to data. A model being developed by vendors in the private sector—notably, Microsoft and Google—is for a health platform that puts users in control of their information so they can access, store, and call on it however and wherever they wish, including for the purpose of making better informed health decisions. Importantly, though, strong policies and clear operating standards are needed when anyone, including patients, access and use sensitive health information.
Interoperability, Data Aggregation, and Data Mining
Across the $2.5 trillion healthcare system few resources are devoted to data sharing, despite its centrality to patient care and improvement. Many barriers to data sharing exist, ranging from competitive concerns to technological challenges, and overall progress in this area has been frustrating. As one workshop participant said, “we have spent the past decade wondering why we cannot collect the data we need to answer our questions.” Stakeholders across the healthcare system currently struggle with poor data quality and formats and lack of the data needed. Nonetheless, despite the considerable barriers, many voices recognize that combining large sets of data offers distinct advantages, underscoring the need for practices that will encourage such aggregation.
In practice, there are considerable technical and operational challenges in data sharing across institutions. Health information technology (HIT) can effectively support quality improvement only to the extent that concerted efforts are made to ensure interoperability. Workshop discussion highlighted
the barriers to broad adoption and use of EHRs for knowledge development posed by platform incompatibilities. For example, the Department of Health and Human Services (HHS) operates 200 separate data systems in a range of areas with little or no means of coordination. Options proposed to help address these issues included establishing standards for data sharing, resolving issues of patient privacy that sometimes preclude data sharing, and revising the architecture of platforms to expedite the sharing of data so they can inform agreed-on goals. Workshop presentations illustrated that while some progress has been made in all of these areas, additional efforts are needed, including collaborative initiatives involving many stakeholders and a commitment of more energy and resources to the ongoing collection, integration, and interpretation of health data in order to better inform policy makers and the public.
In an examination of the trade-offs between pulling data from different data aggregators and the concept of a pooled mega-database, it was suggested that the need is growing for such a database that would pull data from different health plans, the Department of Veterans Affairs, state Medicaid programs, Medicare, and other sources. Such data could then be standardized, creating a public good that would be available for research and multiple other purposes, such as cost-effectiveness studies and explorations of drug safety. An alternative model would be a distributive research network, such as one in which it would be possible to conduct research in different settings with a standard research protocol, and then to pool the results afterward; specific data could conceivably continue to reside with the individual partners who collected them.
To improve interoperability, access, transferability, and translation, improved standards are needed across the clinical data space. Data standardization is partially an issue of messages and transporting data; however, many workshop participants emphasized the need to address standardization issues related to terminologies and classification—noting that a common lexicon is needed to help ensure that data entered into one place in one system can be useful not only elsewhere in that system, but also in other systems. Common diagnosis codes, for example, are needed to help push the translation of data into healthcare improvements at the point of care—to say nothing of accelerating efficiencies in billing processes.
The ACC is working to standardize data that are collected for its registries. The short- term goal is to measure gaps in performance and guideline compliance; the long-term goal is to teach others how to fill those gaps, thus creating a cycle of continuous quality improvement. The American Academy of Family Physicians has been working to establish and promote HIT
standards that are focused on clinical data, such as the American Society for Testing and Materials’ Continuity of Care Record Standard.
Another standardization issue discussed at the workshop underscores the ways in which current technologies lag behind current needs. Although large repositories of controlled clinical trial data exist, including primary data, much of that information exists on paper in various archives, not in any electronic form that would enable sharing. Efforts to digitize health records continue, but further work is needed to effectively retire the paper generation and fully migrate data to electronic forms. Without the complete migration to digital health records, these data will not be immediately accessible, useful, and analyzable.
Creating Next-Generation Data Policy
In one sense, limitations imposed on clinical data by law create what one workshop speaker described as a health information chess board. Often, legislation and regulation impede rather than support our ability to ensure that health information is a public good. In the sense that many of these restrictions—such as those that govern paper-based data collection—were born in a different age and may not be as relevant and useful today, policy does not keep up with practice. Some of today’s barriers are unanticipated byproducts of earlier regulatory decisions. To reach goals based on wider access and utility of clinical data, therefore, some of those regulatory underpinnings may need to be reevaluated.
New thinking regarding patient privacy in the context of data emerged from discussion as an important opportunity for progress. One participant noted that in some ways we still have a privacy paradigm rooted in the paper age. Important implications of this lag behind technology include the absence of a framework for privacy that recognizes that health information is no longer a static good, but increasingly is a portable, moving, compounding, growing asset, and privacy practices that impede the sharing of data for point-of-service health care.
Deidentification of data raises privacy issues. Several participants stressed that unless, for example, the standard notification of privacy practices is changed so that data can be used if they are deidentified for secondary use in clinical research, the challenges to aggregating data among various institutions will likely persist. Possible solutions proposed include initially registering patients with a unique identifier that at some point could be associated for research purposes.
As an advisory committee to HHS, the National Committee on Vital
and Health Statistics (NCVHS) has developed some principles that might inform further thinking. For example, NCVHS has recommended that covered entities strengthen the terms of their business contracts to be more specific about what data will be used, how, and by whom. Recognizing that transparency is important to consumers, another NCVHS recommendation was that notices of privacy practices need to be more meaningful, and that individuals should be able to request and be given additional information about the specific uses and users of their data. New models of personal health records, such as Microsoft’s HealthVault, are being designed in tandem with new models of voluntary patient control privacy policies. Such avenues deserve closer attention as potential guides for new thinking.
A view expressed throughout the workshop is that many elements of the Health Insurance Portability and Accountability Act of 1996 (HIPAA) are outdated. HIPAA’s Privacy Rules were characterized as confusing and, among other drawbacks, HIPAA limits the portability of data and overall data sharing, does not encourage standardization, and is inadequate in ensuring timely use of data. Moreover, enforcement of HIPAA was seen as nearly nonexistent. Several participants suggested that modifications are needed to strike the proper balance between protecting patient privacy and making data available for research necessary to improve healthcare quality and lower costs; and that a revised legislative code of privacy, confidentiality, and security would help to support and promote the next generation of clinical data.
Raised during the meeting as an important issue to address was the elimination of accounting disclosure obligations—which could help to reduce the cost of sharing data. Because of HIT and other developments in technology, the deidentification standard discussion might be best framed in the context of whether the deidentification safe harbor is too narrow. Another question raised by participants as important for discussion is whether liability burdens are properly distributed. Identifying the most significant barriers that remain, including those related to future unspecified research and data deidentification, and clearly defining policy alternatives will be helpful in promoting the research enterprise. Bills currently proposed in support of HIT and EHR systems, with strong built-in privacy protections, may offer necessary remedies, but continued work and vigilance in this area is needed. One specific suggestion was that at the conclusion of the Institute of Medicine’s recent study on HIPAA and privacy protection regulations a follow-up meeting could be convened to explore what can be done within the existing structure to clarify definitions and reduce the
tendencies for unnecessarily restrictive interpretations, in particular related to secondary use of data.1
In addition to regulatory concerns, participants also raised concerns regarding clinical data within the construct of the legal system. The legal system enters the “public good” debate because it reflects and so perpetuates the current “excludability” state of clinical data with property and intellectual property models. Furthermore, market exchanges or shifts to public good “nonexcludability” face legal barriers (e.g., privacy, confidentiality, and security) that are designed to reduce or eliminate negative externalities suffered by data subjects. Presentations illustrated how certain legal rules create barriers to clinical data as a public good, such as property or inalienability rules, federal–state disconnects, and evolving data protection models. Resolving the current excludability rules was noted as an area in need of greater attention, and it was suggested that a more rigorous data protection model may be required as a predicate for greater access to patient data.
For clinically rich information, one suggested approach was to start from scratch to build a new, much stronger model, as has been recommended several times by NCVHS. Alternatively, NCVHS’s secondary stewardship model could be combined and melded with a slimmed-down version of the European data directive. This would potentially create a more robust data protection model that would impose stronger obligations on data stewards through chain-of-trust data processes. Other attributes of this model would be strict limitations on data being processed for a purpose other than the original purpose of collection, a more relative approach
to data than HIPAA, and an overall design aimed at gaining the trust of patients and providers by making sure they understand secondary uses of data, adjustments possible when relative levels of deidentification are encountered, lack of reidentification, and so on.
Engaging the Public
The meeting emphasized the fact that moving to the next generation of clinical data depends in large part on an ability to engage and inform the public in shaping evidence development strategies. As illustrated by the broad representation at the meeting, all stakeholders can play a contributory role in better orienting data collection and use efforts to improve health. Noted in particular was the importance of keeping the public closely involved in and informed about all activities related to using clinical data to generate new knowledge—as progress will likely hinge on public acceptance. Discussion focused in particular on efforts that encouraged direct engagement of consumers with their personal health data.
Participants underscored the need for new approaches that engage the public in a deeper conversation about data utility—to better educate the public about the importance and intricacies of the data debate, to help the public become more fully vested in the discussion, and to help the research community to better understand the public’s point of view and stake in the data utility. Such efforts simultaneously present the opportunity to reinstate the patient as the focal point of the data utility, in contrast to a role somewhere on the periphery, and to engage the public as a key driver of change to improve data utility overall. Finding genuine ways to respond to the public’s desires regarding key issues, including access to data in language they can understand, portability of individual data throughout the healthcare system, and quality data that informs health care at the point of care was viewed as an important means to fostering broader public engagement in a healthcare system.
Clarifying the Social Contract
Data sharing is, in essence, a social contract between individuals and researchers who want to use their data. The current approach to obtaining data access; however, was described as falling far short of a clear illustration of the potential returns on this contract. Patients are told there will be some pay-off from sharing data—that they will have better, safer quality care, and that researchers will learn more about the disease so the healthcare system may be able to take better care of the patient or the patient’s children. Yet many participants suggested that perhaps patients do not hear enough about how that is supposed to happen. Where does the pay-off come? How does
the other side of that contract deliver? What are the deliverables? Is there a timeline for those deliverables? Is there accountability for those deliverables? Those questions need to be addressed, probably by a broad coalition of stakeholders in clinical data, with patients at the center of the discussion. The experience of the VA with My Healthy Vet showed that patients want to be asked about the use of their personal data and to engage in a process to give consent about how those data are used; but, overall, patients do not demonstrate a need to control their data at a microscopic level.
As part of the social contract, it was suggested that perhaps more specific requirements are needed of those collecting the data. Fundamentally, policies could be developed that require those collecting data to do something specific with the information they collect, and that further require reporting back on what was done with the data. At the same time, perhaps policies could be set that inform and guide quality assurance about the data, and set specific expectations about the timeliness of their use.
Participants also noted the need for more attention to mechanisms and practices that ensure and protect patient privacy. For example, the suggestion was made that an independent health privacy audit and verification process be established. One presenter suggested that a program of empirical studies on the impacts of EHRs may be warranted—to assess privacy, access, and security programs in selected research settings—as well as the development of patient satisfaction and trust surveys to chart patients’ experiences and attitudes in evidence-based research programs.2
Public Information and Education
Educating patients and the public about the value of clinical data, and promoting privacy-compliant, evidence-based health research might require national educational campaigns. To date, there has not been a public demonstration of the utility of data sharing and of the potential impact of data on personal lifestyle, bottom line, or other meaningful endpoints—an area viewed by some participants as ripe for further exploration. National public information campaigns and programming could go a long way to help convince consumers and patients of the public good aspect of sharing their medical data.
One suggested option to demonstrate the value of research as a public good is to consider expanded reporting of meaningful clinical health data. The New York Department of Health’s effort to have all labs report A1C data from diabetics to the public health department, while not a perfect
model, shows potential in part because it actively engages the department in prevention measures. Toward different but similar goals, the Massachusetts Health Quality Partners draws on health plan claims data to report trusted, reliable information on physician performance as a means of developing valid, comparable measures that could lead to quality improvement. The information is shared both with physicians, to help them improve the quality of care they provide, and to consumers, to help them make informed decisions about their health care. Information posted for the public has a patient information component in the sense that it is accompanied by consumer information about specific medical conditions, and about what patients should expect of their physician in that regard. Such models may have potential for duplication in other venues.
Another possible approach to demonstrating the value of research is the enhancement and expansion of clinical data registries. Many registries today remain siloed, and do not collect data in a way that can be useful and meaningful to the public. Current systems are not designed, for example, to track major causes of U.S. death and disability that may be compelling and ultimately important to the public. Discussion about the use of registries highlighted their development as a key opportunity to think about data elements needed and information and outcomes desired so that the use of registry data can generate more public interest and consumer value.
Another possibility suggested is to develop a nationwide health tracking network. Such an approach could help to identify, track, and prevent health-related causes of death, whether they are environmental, occupational, or lifestyle/behavioral. It could inform the public health community, providers, policy makers, and consumers about disease rates by geography, ethnicity, and other relevant criteria.
The public and the patient must drive change and advocate for using data as a public utility. As noted by several participants, some hospitals and research institutions have shown innovation in educating their patients about how important clinical research is to patient care; many have started what are essentially marketing campaigns to educate patients and their families on the importance of participation in clinical trials and related research endeavors. Learnings from these initial efforts might help shape broader efforts to educate people on the importance and potential benefits of using data for secondary purposes.
Ultimately, the disparate voices engaged in efforts and thinking designed to improve clinical data utilities are looking for clarity on how they should go about, in the words of one workshop presenter, “compiling, analyzing, structuring, artifacting, [and] accountable-izing.” As demonstrated throughout workshop discussions, stakeholders across health care are interested in designing an agenda that will move this work forward, and engaging with leaders who can advance the agenda. Such work was viewed by many par-
ticipants as essential to making the use of clinical data more efficient and perhaps equitable, and, ultimately ensuring that evidence-based medicine can draw more effectively and productively on the rich intelligence inherent in the data.
AREAS FOR INNOVATION AND COLLABORATIVE ACTION
Workshop presentations and discussions highlighted multiple opportunities to accelerate collaborative efforts to advance clinical data frontiers. Potential opportunities for follow-up attention by the members of the IOM Roundtable on Value & Science-Driven Health Care include those noted below—with Roundtable Innovation Collaboratives already engaged in related follow-on work indicated in parentheses.
Principles: Foster the development, review, and implementation of basic principles for data stewardship.
Use of electronic health records for knowledge development: Convene 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).
Collaborative data mining: Organize exploratory efforts to investigate cutting-edge data-mining techniques for generating evidence on care practices and research (EHR Innovation Collaborative).
Incentives: Convene an employer–payer workgroup to explore approaches for the use of economic incentives to reward providers/groups working to improve knowledge generation and application in the care process.
Privacy and security: Follow the IOM study on HIPAA and privacy protection regulations with a series of meetings to explore and clarify definitions and reduce the tendency toward unnecessarily restrictive interpretations, in particular as they relate to data sharing and secondary uses.
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 Medicare-related data, including from Part D (pharmaceutical) use.
Public involvement in the evidence process: Engage the public through communication efforts aimed at increasing public understanding and involvement in evidence-based medicine (Evidence Communication Innovation Collaborative).