1

Introduction

Health and health care are going digital. As multiple intersecting platforms evolve to form a novel operational foundation for health and health care—the nation’s digital health utility—the stage is set for fundamental and unprecedented transformation. Most changes will occur virtually out of sight, and the pace and profile of the transformation will be determined by stewardship that fosters alignment of technology, science, and culture in support of a continuously learning health system. In the context of growing concerns about the quality and costs of care, the nation’s health and economic security are interdependently linked to the success of that stewardship.

Progress in computational science, information technology, and biomedical and health research methods have made it possible to foresee the emergence of a learning health system that enables both the seamless and efficient delivery of best care practices and the real-time generation and application of new knowledge. Increases in the complexity and costs of care compel such a system. With rapid advances in approaches to diagnosis and treatment, and new genetics insights into individual variation, clinicians and patients must sort through exponentially increasing numbers of issues with each clinical decision. At the same time, healthcare costs are draining the purchasing power of consumers and handicapping the competitiveness of U.S. businesses, yet health outcomes are falling far short of the possible.

Against this backdrop of opportunity and urgency, the Institute of Medicine (IOM) of the National Academies, sponsored by the Office of the National Coordinator for Health Information Technology (ONC), convened a series of expert meetings to explore strategies for accelerating the



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1 Introduction Health and health care are going digital. As multiple intersecting plat- forms evolve to form a novel operational foundation for health and health care—the nation’s digital health utility—the stage is set for fundamental and unprecedented transformation. Most changes will occur virtually out of sight, and the pace and profile of the transformation will be determined by stewardship that fosters alignment of technology, science, and culture in support of a continuously learning health system. In the context of growing concerns about the quality and costs of care, the nation’s health and economic security are interdependently linked to the success of that stewardship. Progress in computational science, information technology, and bio- medical and health research methods have made it possible to foresee the emergence of a learning health system that enables both the seamless and efficient delivery of best care practices and the real-time generation and ap- plication of new knowledge. Increases in the complexity and costs of care compel such a system. With rapid advances in approaches to diagnosis and treatment, and new genetics insights into individual variation, clinicians and patients must sort through exponentially increasing numbers of issues with each clinical decision. At the same time, healthcare costs are draining the purchasing power of consumers and handicapping the competitiveness of U.S. businesses, yet health outcomes are falling far short of the possible. Against this backdrop of opportunity and urgency, the Institute of Medicine (IOM) of the National Academies, sponsored by the Office of the National Coordinator for Health Information Technology (ONC), con- vened a series of expert meetings to explore strategies for accelerating the 53

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54 ENGINEERING A LEARNING HEALTHCARE SYSTEM development of the digital infrastructure for the learning health system. Major elements of those discussions are summarized in this publication, Digital Infrastructure for the Learning Health System: The Foundation for Continuous Improvement in Health and Health Care. THE LEARNING HEALTH SYSTEM In 2001, the IOM report Crossing the Quality Chasm called national attention to untenable deficiencies in health care, noting that every patient should expect care that is safe, effective, patient-centered, timely, efficient, and equitable (IOM, 2001). Based on the determination that health care is a complex adaptive system—one in which progress on its central purpose is shaped by tenets that are few, simple, and basic—the report identified several rules to guide health care. In particular, these rules underscore the importance of issues related to the locus of decisions, patient perspectives, evidence, transparency, and waste reduction. The report envisioned, in ef- fect, engaging patients, providers, and policy makers alike to ensure that every healthcare decision is guided by timely, accurate, and comprehensive health information provided in real time to ensure constantly improving delivery of the right care to the right person for the right price. The release of the IOM Chasm report stimulated broad activities re- lated to clinical quality improvement and the effectiveness of health care, including the creation by the IOM of the Roundtable on Value & Science- Driven Health Care. Begun in 2006 as the IOM Roundtable on Evidence- Based Medicine, it has explored ways to improve the evidence base for medical decisions and sought the development of a learning health system “designed to generate and apply the best evidence for collaborative health choices of each patient and 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.” From its inception, the Roundtable has con- ducted The Learning Health System Series of public meetings in an effort to outline components of the conceptual foundation of the learning health system. Since 2006 the IOM has conducted 15 workshops in the Learning Health System Series, with 10 reports published and in production: • T he Learning Healthcare System • Leadership Commitments to Improve Value in Health Care: Find- ing Common Ground • E vidence-Based Medicine and the Changing Nature of Health Care • R edesigning the Clinical Effectiveness Research Paradigm: Innova- tion and Practice-Based Approaches • C linical Data as the Basic Staple of Healthcare Learning: Creating and Protecting a Public Good

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55 INTRODUCTION • E ngineering a Learning Healthcare System: A Look at the Future • L earning What Works: Infrastructure Required for Comparative Effectiveness Research • V alue in Health Care: Accounting for Cost, Quality, Safety, Out- comes, and Innovation • T he Healthcare Imperative: Lowering Costs and Improving Outcomes • P atients Charting the Course: Citizen Engagement and the Learn- ing Health System As the most recent contribution to this series, this publication considers what has been variously described as the system’s nerve center, its circula- tion system, or the engine to drive the progress envisioned in the Learning Health System Series: the digital infrastructure. As it has been laid out by the work of the Roundtable, in a learning health system patients and providers will have access to timely, accurate, and comprehensive health information that can be used to deliver services effectively and efficiently. Characteristics of such a system are noted in Box 1-1 and in matrix form in Appendix A. Because information technology serves as the functional engine for the continuous learning system, this ONC-commissioned exploration was broadly conceived to consider the issues and strategies required for the emergence of a digital infrastructure that allows data collected during activities in various settings—clinical, research, and public health—to be integrated, analyzed, and broadly applied (“collect once, use for multiple purposes”) to inform and improve clinical care decisions, promote patient education and self-management, design public health strategies, and sup- port research and knowledge development efforts in a timely manner. THE DIGITAL HEALTH INFRASTRUCTURE The digital infrastructure for the learning health system will not solely be the result of features designed and built de novo; there is a growing body of existing initiatives and resources actively in play at multiple levels. These include expanding adoption of technologies such as electronic health records (EHRs), personal health records (PHRs), telehealth, health informa- tion portals, electronic monitoring devices, mobile health applications, and advances in molecular diagnostics. Also in play are collections of health information, such as biobanks, and health information databases main- tained by large health systems, private insurers, and regulatory agencies. Each adds important capacity for clinical care, clinical and health services research, public health surveillance and intervention, patient education and self-management, and safety and cost monitoring. Still, these capacities are relatively early in their development and as

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56 ENGINEERING A LEARNING HEALTHCARE SYSTEM BOX 1-1 Learning Health System Characteristics Culture: participatory, team-based, transparent, improving Design and processes: patient-anchored and tested Patients and public: fully and actively engaged Decisions: informed, facilitated, shared, and coordinated Care: starting with the best practice, every time Outcomes and costs: transparent and constantly assessed Knowledge: ongoing, seamless product of services and research Digital technology: the engine for continuous improvement Health information: a reliable, secure, and reusable resource The Data utility: data stewarded and used for the common good Trust fabric: strong, protected, and actively nurtured Leadership: multi-focal, networked, and dynamic SOURCE: Adapted from The Learning Healthcare System (IOM, 2007). they continue to unfold, progress toward a digital health infrastructure depends on continuous improvement. Challenges include the fact that as of 2009, only about 12% of hospitals and 6% of clinician offices had an EHR in place (DesRoches et al., 2008; Jha et al., 2010) and only about 1 in 14 Americans had electronic access to any patient-oriented version of their health record (CHCF, 2010). On the other hand, since 2000, the num- ber of Americans who have access to the Internet has jumped from 46% to 74%, and the number of American adults who have looked online for health information has jumped from 25% to 61% (Fox, 2010), suggesting a change in the way people access health information. Wireless technology is quickening the pace of change. With 6 in 10 American adults using wireless capability with a laptop or mobile device (Smith, 2010), mobile applica- tions are rapidly developing for remote site access to health information, as well as diagnostic and even treatment services.

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57 INTRODUCTION The striking progress in the capacity and influence of information tech- nology on society over the past three decades is a blended product of inter- related initiatives arising from within the commercial, independent, and public sectors. Leaps in the speed and power of information processing, the efficiency of the operations, the development of the Internet and World Wide Web, and its use to facilitate near-universally available real-time access to information have spawned a new economy and new vehicles for progress. Health information vendors, large and small, have emerged to meet the growing demand for capacity to manage the retrieval, storage, and delivery of information for agencies, institutions, professionals, and individuals in virtually every aspect of health and health care. The range of newly digi- talized services—and the growth of vendors to provide them—is startling. Through technologies developed by companies such as Google, Microsoft, and Yahoo, the rapidly expanding amounts of health-related information available on the Internet have become increasingly easy to access and query. The amount of web-based health information accessed daily by individuals and clinicians, and the frequency with which they turn to the Internet for this information, is already transforming the care process. Care Management Resources Beyond publicly available digital resources, a vast array of specialized care management products have emerged to support a broad range of ac- tivities. A wide array of companies have emerged to support the various facets of clinical recordkeeping and information management needed to support clinical processes. Many of these, such as individual patient chart- ing, are served through EHRs. Vendors include EPIC, Cerner, Greenway Medical, General Electric, and Allscripts, as well as newer companies that provide web-based services such as Practice Fusion. Most of these are comprehensive EHR products that integrate support of administrative pro- cesses such as scheduling, billing, claims processing, payment, and even supply and equipment inventory maintenance. Other products supporting health information management are PHRs—records maintained by indi- vidual consumers—that provide patients a format for contributing and managing their health information electronically. Microsoft HealthVault and Google Health are two of the leading efforts in this area, as well as Dossia, an employer-led, open source effort. Prescribing is another compo- nent of the clinical care continuum moving to the digital platform. Led by companies such as Surescripts—with an expansive network and increasing capabilities—e-prescribing is, in many ways, leading the way in current health information exchange. EHRs, PHRs, and their associated functions represent a wealth of potential in the support of clinical decisions and as sources of information

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58 ENGINEERING A LEARNING HEALTHCARE SYSTEM for research, surveillance, public health reporting, and patient–clinician communication. This is accomplished through portals for more regular, di- rect communication between patients and their providers; clinical research protocol processes; postmarket product monitoring; safety and hazard exposure monitoring; disease and intervention registries; and data aggre- gation, analysis, and modeling. Increased use of digital technology also includes remote examination and diagnosis through telehealth technologies, such as those used by the military and in rural locations. Furthermore, the use of monitoring sensors to follow patients remotely and collect informa- tion in real time is growing in use, especially among the chronically ill. Several organizations are actively involved in employing these technologies at their full potential, and some of these are highlighted in the case studies presented in Appendix B and discussed below. Healthcare Delivery Organizations Various large academic health centers and healthcare delivery organizations—Veterans Health Administration (VHA), Kaiser Perman- ente (see summary in Box 1-2, and the full written description in Appendix B), Geisinger Health System, Vanderbilt, MD Anderson, Palo Alto Medical Foundation, Group Health Cooperative, several Harvard facilities, Chil- dren’s Hospital of Philadelphia, Virginia Mason, and the Mayo Clinic, to name a few—have invested substantially in the creation of advanced digital resources for administrative, patient care, and research functions. For example, the VHA established one of the first EHR systems, Veterans Health Information Systems and Technology Architecture (VISTA), and has been a pioneer in its use of health information technology (HIT) for quality improvement. More recently, VHA launched the ‘My HealtheVet’ program, a PHR system that allows veterans to track their clinical visits, tests, and prescriptions, while also having access to relevant health informa- tion and patient support communities. Other important HIT applications employed by these organizations include: clinical decision support tech- nologies integrated within their EHR systems and data mining for adverse event surveillance and identification of populations at risk or in need of directed follow-up. Nonetheless, the diversity and limited compatibility of the products, coupled with the lack of economic incentives for their use, has, to date, restrained the uptake, application, and functional utility of these capacities across the broader system. Independent Sector A number of public, private, and independent sector initiatives have emerged to accelerate stakeholder action on various dimensions important

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59 INTRODUCTION BOX 1-2 Case: Kaiser Permanente In 2003, Kaiser Permanente (KP) launched a $4 billion health information system called KP HealthConnect that links its facilities and clinicians throughout their delivery system and represents the largest civilian installation of electronic health records (EHRs) in the United States. The EHR at the heart of KP Health- Connect provides a reliably accessible longitudinal record of member encounters across clinical settings including laboratory, medication, and imaging data; as well as supporting • lectronic prescribing and test ordering (computerized physician-order E entry) with standard order sets to promote evidence-based care • opulation and patient-panel management tools such as disease regis- P tries to track patients with chronic conditions • ecision support tools such as medication-safety alerts, preventive-care D reminders, and online clinical guidelines • lectronic referrals that directly schedule patient appointments with spe- E cialty care physicians • ersonal health records providing patients with the ability to view their P personal clinical information including lab results, plus linkage with phar- macy, physician scheduling, and secure and confidential e-mail messag- ing with clinicians. • erformance monitoring and reporting capabilities P • atient registration and billing functions P Physician leaders report that access to the EHR in the exam room is helping to promote compliance with evidence-based guidelines and treatment protocols, eliminate duplicate tests, and enable physicians to handle multiple complaints more efficiently within one visit. Ongoing evaluation by Kaiser indicates that pa- tient satisfaction with outpatient physician encounters has increased and that the combination of computerized physician-order entry, medication bar coding, and electronic documentation tools is helping to reduce medication administration errors in hospital care. Overall, Kaiser’s experience suggests that use of the EHR and online portal to support care management and new modes of patient encounters is having positive effects on utilization of services and patient engagement. For example, three-quarters or more of online users surveyed agreed that the portal enables them to manage their health care effectively and that it makes interacting with the healthcare team more convenient. to progress. To supplement the relatively limited pre-2009 public invest- ments, independent sector leadership has come from foundations such as the Markle Foundation, the Robert Wood Johnson Foundation (RWJF), and the California HealthCare Foundation (CHCF). For example, the

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60 ENGINEERING A LEARNING HEALTHCARE SYSTEM Markle Foundation has played a leading role in facilitating conversations in the areas of privacy and security in order to ensure that the patient is the ultimate beneficiary of a digitally–supported learning health system. Their Common Framework for sharing and protecting health information has been fundamental in identifying principles and approaches for safe health information exchange. Among many other activities, RWJF has led the way in stimulating innovation in PHRs through its Project HealthDesign, and CHCF has funded a number of projects to explore the use of HIT to improve the care of patients with chronic conditions. As a result of the increased activity in the area, a number of facilitative stakeholder groups have emerged. A portion of these have taken the shape of capacity-building resources such as the Health Information Exchanges, which serve to work with clinicians and institutions to facilitate the ex- change of health information between systems, often within a defined geo- graphic area. Other groups include the Clinical Data Interchange Standards Consortium (CDISC) an organization involved in developing standards to enable aggregation of health information across datasets and methodologies to support its use for research, and Integrating the Healthcare Enterprise (IHE), which promotes coordinated use of established standards to improve health information interoperability. An example of the coordinative poten- tial of these groups is found in the development of integration profiles by IHE and CDISC to support the use of EHRs for clinical research, quality and public health, and the testing and demonstration of these profiles by several vendors including Cerner, Allscripts, Greenway Medical, and GE Healthcare. Additionally, there are a number of organizations working to promote the use of information and information technology to improve health and health care. Notable among them are the eHealth Initiative, the National eHealth Collaborative, and the Healthcare Information and Management Systems Society. Finally, on the professional advancement dimension, the American Medical Informatics Association has emerged as a growing resource for the contributions of biomedical and health in- formaticians working in activities to organize, manage, analyze, and use information in health care. Examples from Outside Health Care The developing potential presents opportunities and challenges for stewardship. Issues related to interoperability, governance, engagement of patients and the general population, and privacy and security concerns resulting from the collection and use of health information will need to be better addressed for successful progress toward a learning health system. Given these challenges, workshop proceedings included the consideration of a number of different cases studies of innovative approaches from both

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61 INTRODUCTION within and outside the healthcare space to inform participants’ consider- ations of the challenges ahead. These case studies are included in their en- tirety in Appendix B and summarized in boxes in several places throughout this introductory chapter. Two of those cases drawn from outside health care were VISA and Consumer Energy. VISA was introduced as an example of an innovative approach to the governance of a highly decentralized network of service providers. Through the leadership of Dee Hock, a system based on a minimal set of core stan- dards that maximized peripheral autonomy was created. The principles of this approach—which include maximizing human ingenuity, shared clarity on the purpose and principles of the group, pushing all possible operations to the periphery, and fostering and tolerating evolution—were specifically highlighted as important for consideration. Consumer Energy’s work in the Smart Grid Initiative was used to il- lustrate a systematic approach to implementation of a complex systems development project of nationwide scale. This approach, based on the ultra-large-scale (ULS) system principles, includes applying an engineering approach to accommodate and network a wide variety of legacy nodes while allowing for continuous expansion and evolution without the use of a comprehensive internal design or rigid standardization. The Smart Grid case is summarized in Box 1-3 and the full written description is included in Appendix B. Regardless of the model, a key rationale for workshop discussions was the reality that effective and efficient progress in the growth and develop- ment of our national and global digital health infrastructure requires active cooperation, collaboration, and role delineation among many organiza- tions, companies, and agencies—private and public—at the cutting edge of using HIT for improving health and health care. Federal and State Governments At the national level, stewardship of the digital health infrastructure has fallen primarily to the federal government. ONC was created in 2004 in the U.S. Department of Health and Human Services (HHS) to stimulate progress in the field by providing leadership, policy coordination, stra- tegic planning, and infrastructure development for the adoption of HIT. Since 2009, with the enactment of the Health Information Technology for Economic and Clinical Health Act (HITECH) as part of the American Recovery and Reinvestment Act, the federal government leadership profile has become especially prominent. The principal goals of HITECH are to build approval for HIT adoption and meaningful use; increase patient and provider participation in electronic health information exchange; educate the public about the uses of personal health information and privacy and

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62 ENGINEERING A LEARNING HEALTHCARE SYSTEM BOX 1-3 Case: The Smart Grid The Smart Grid is a long-term, complex systems development project using an engineering approach to accommodate a wide variety of legacy nodes that are organic—constantly growing and evolving, much like a biological system. This con- tinuous evolution allows the Smart Grid’s architecture to preserve and encourage the capacity of each node to innovate locally and deal with complexity in a way that suits local and grid needs. As conceived, the Smart Grid will • Enable active participation by consumers • Accommodate all generation and storage options • Enable new products, services, and markets • Provide power equality for the digital economy • Optimize asset utilization and operate efficiently • Anticipate and respond to system disturbances (self-heal) • Operate resiliently against attack and natural disaster Because there is no need for consensus among the nodes on how they should operate within local boundaries, the Smart Grid development methodology is not based on comprehensive internal design and operating standards for each node on the Grid to follow. Instead, the approach accommodates highly diverse nodes connecting to the Smart Grid using open data translation protocols that standardize information management, rather than using the internal workings of each node. The Grid becomes a communications bus to which each node must be able to write, and from which each node must be able to read. This architecture preserves capacities for local operating autonomy and innovation throughout the Smart Grid. It also manages a standardized communications capacity among complex, and otherwise noninteroperable, legacy nodes on the Grid. These fea- tures are all characteristics of ultra-large-scale software-intensive systems. security protections available to them; and use a comprehensive, integrated approach to successfully communicate about privacy, security, and mean- ingful use to target audiences. Meeting these goals has come with the com- mitment of unprecedented resources administered through the leadership of ONC. Implementation of HITECH by ONC has been done with the aid of two federal advisory committees made up of representatives from across all HIT stakeholder areas, the HIT Policy Committee and the HIT Standards Committee. The committees have guided ONC’s work on meaningful use, certification and adoption, information exchange, strategic planning, pri- vacy and security, and enrollment. Under HITECH, ONC was granted $2 billion to facilitate the adop- tion and meaningful use of HIT. In addition, an estimated $27 billion was designated for the Centers for Medicare & Medicaid Services (CMS) to be

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63 INTRODUCTION distributed as incentive payments for physicians and hospitals to become meaningful users of HIT. Designed as a set of staged requirements to qualify for CMS incentive payments, the first-stage elements of “meaningful use” were released by CMS on July 13, 2010. These established a core set of requirements for eligible professionals and hospitals, as well as a menu of additional choices, from which five are to be chosen. The stage 1 meaning- ful use target elements are listed in summary fashion in Box 1-4, and details are contained in Appendix D. The subsequent stages of meaningful use are currently under development and are presented in Chapter 10, along with an indication of related issues flagged in workshop discussions. In addition to the meaningful use requirements, ONC has funded a series of grant programs through HITECH such as the Beacon Community grants (aimed at demonstrating community-wide digital infrastructure capacity and use for health improvement) and the Strategic Health Information Technol- ogy Advanced Research Projects Program (aimed at fostering the capture of technological advances to improve system performance). At the broader level, ONC is pursuing a series of initiatives to foster health information exchange among stakeholders under the Nationwide Health Information Network. Several additional HHS agencies have activities important to the de- velopment of the digital infrastructure for the learning health system. CMS has had primary responsibility for establishing rules for meaningful use and requirements for uniform condition identifiers central to healthcare payment and research. Additionally, the passage of the Affordable Care Act (ACA) created the $10 billion Center for Medicare and Medicaid Innovation (CMMI). CMMI will test innovative payment and program service delivery methods, many of which will rely on robust information technology systems. Within the National Institutes of Health (NIH), the National Library of Medicine (NLM) serves as the central coordinating body for clinical terminology standards. In addition, NLM also supports a number of HIT system development tools—in areas such as language and knowledge pro- cessing—and offers grant programs in HIT education and training. The NIH Clinical and Translational Science Awards Program provides funding for a consortium of organizations to facilitate collaborative research and speed the adoption of clinical research results in the clinic including sup- porting the development and use of innovative technologies by individual grantee organizations. Additionally, the National Cancer Institute has a number of initiatives that serve as key contributors to building the capacity to derive scientific discovery from patient care. Among these are the Enter- prise Vocabulary Services which provide controlled terminology and ontol- ogy services for use by researchers, and the cancer Biomedical Informatics Grid (caBIG®) which is designed to improve care and accelerate scientific discoveries by enabling the collection and analysis of large amounts of

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64 ENGINEERING A LEARNING HEALTHCARE SYSTEM BOX 1-4 Meaningful Use Requirement Categories Core structured personal data (age, sex, ethnicity, smoking status) Core list of active problems and diagnoses Core structured clinical data (vital signs, meds, [labs]) Outpatient medications electronically prescribed Automated medication safeguard/reconciliation Clinical decision support Care coordination support/interoperability Visit-specific information to patients Automated patient reminders e-Record patient access (copy or patient portal) Embedded measures for clinical quality reporting Security safeguards Examples of optional elements: Advance directives for ages >65 Condition-specific data retrieval capacity Public health reporting (reportable conditions) SOURCE: Adapted from Blumenthal and Tavenner (2010). See Appendix D for details. biological and clinical information (see Box 1-5 and Appendix B for addi- tional information). Through its National Resource Center for Health IT and initiatives on patient registries, the Agency for Healthcare Research and Quality (AHRQ) supports a number of programs to advance the digital utility for healthcare quality and safety. Currently these programs are focused on the areas of support for HIT program management, guidance, assessment, and plan- ning; HIT technical assistance, content development, and program-related projects and studies; HIT dissemination, communication, and marketing; and HIT portal infrastructure management and website design and usability

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65 INTRODUCTION BOX 1-5 Case: The National Cancer Institute’s caBIG® Initiative The National Cancer Institute of the National Institutes of Health has devel- oped an informatics program designed to improve patient care and accelerate scientific discoveries by enabling the collection and analysis of large amounts of biological and clinical information and facilitating connectivity and collaboration among biomedical researchers and organizations. More than 700 different orga- nizations are actively engaged in caBIG®, including basic and clinical researchers, consumers, physicians, advocates, software architects and developers, bioinfor- matics specialists and executives from academe, medical centers, government, and commercial software, pharmaceutical, and biotechnology companies from the United States and in 15+ countries around the globe. At the heart of the caBIG® program is caGrid, a model-driven, service- oriented architecture that provides standards-based core “services,” tools, and interfaces so the community can connect to share data and analyses efficiently and securely. More than 120 organizations are connected to caGrid. In partnership with the American Society of Clincal Oncology, caBIG® is developing specifica- tions and services to support oncology-extended EHRs that are being deployed in community practice and hospital settings. caBIG® tools and technology are also being used by researchers working on cardiovascular health, arthritis, and AIDS. In addition, pilot projects have successfully connected caGrid to other net- works, including the Nationwide Health Information Network, the CardioVascular Research Grid, and the computational network TeraGrid. support. AHRQ also supports the National Guideline Clearinghouse which provides healthcare institutions, providers, and researchers access to objec- tive, detailed information on clinical practice guidelines. At the Food and Drug Administration (FDA), the Sentinel Initiative (see Box 1-6 and Appendix B) has been designed to build and implement a na- tional electronic system for postmarket surveillance of approved drugs and other medical products. A smaller working pilot of the Sentinel system has been developed, under contract from the FDA, by Harvard Pilgrim Health Care to test epidemiological and statistical methodologies on distributed data sources. As the federal focal point for programs in public health, the Centers for Disease Control and Prevention have supported several major HIT- anchored programs including the surveillance programs BioSense, EPI-X, and the National Healthcare Safety Network. The Health Resources and Services Administration, as the primary federal agency for improving access to healthcare services for the uninsured, isolated, or medically vulnerable, supports a portfolio of HIT programs aimed at improving care access and coordination for underserved populations and those in rural areas.

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66 ENGINEERING A LEARNING HEALTHCARE SYSTEM BOX 1-6 Case: The FDA’s Sentinel Initiative In 2008, the Department of Health and Human Services and the Food and Drug Administration (FDA) announced the launch of FDA’s Sentinel Initia- tive, a long-term program designed to build and implement a national electronic s ystem—the Sentinel System—for monitoring the safety of FDA-approved drugs and other medical products. Data partners in the Sentinel System will include organizations such as academic medical centers, healthcare systems, and health insurance companies. As currently envisioned, participating data partners will access, maintain, and protect their respective data, functioning as part of a “dis- tributed system.” In a related pilot activity, FDA is working with Harvard Pilgrim Health Care, Inc. to develop a smaller working version of the future Sentinel System, dubbed “Mini-Sentinel.” Through this pilot, FDA will learn more about some of the barriers and challenges, both internal and external, to establishing a Sentinel System for medical product safety monitoring. The Mini-Sentinel Coordinating Center (MSCC) represents a consortium of more than 20 collaborating institutions, working with participating data partners to use a common data model as the basis for their ap- proach. Data partners transform their data into a standardized format, based upon which the MSCC will write a single analytical software program for a given safety question and provide it to each of the data partners. Each partner will conduct analyses behind its existing, secure firewall, and send only summary results to the MSCC for aggregation and further evaluation. As this pilot is being implemented, a governance structure is being devel- oped to ensure that the activity encourages broad collaboration within appropri- ate guidelines for the conduct of public health surveillance activities. In order to accomplish that, the MSCC is developing a Statement of Principles and Policies that will include descriptions of the organizational structure and policies related to communication, privacy, confidentiality, data usage, conflicts of interest, and intellectual property. Efforts to promote the development, implementation, and widespread adoption of HIT also build on a wide array of digital learning leadership efforts by other federal agencies. In particular, important contributions stem from responsibilities and activities of the VHA and the Department of De- fense (DOD). The Telemedicine and Advanced Technology Research Center is a joint program between DOD and the VHA to promote research and applications in health informatics, telemedicine, and mobile health moni- toring systems. Additionally, the DOD and VHA are working together to create a Virtual Lifetime Electronic Record to allow for seamless availability of healthcare, benefits, and services information for service members from enlistment to death. Additional efforts include defining a plan for HIT in the Federal Communications Commission’s National Broadband Plan, and

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67 INTRODUCTION the National Science Foundation’s Smart Health and Wellbeing initiative. Because of the deep and broad set of capabilities and initiatives collectively sponsored by federal agencies, their coordination and interface with private sector activities offer a vital strategic opportunity to accelerate the learning health system’s development. Testament to the compelling priority of the prospects, in December 2010 the President’s Council of Advisors on Science and Technology (PCAST) issued its report, Realizing the Full Potential of Health Informa- tion Technology to Improve Healthcare for Americans: The Path Forward (PCAST, 2010). The PCAST report examines the opportunities and needs for the use of HIT to improve healthcare quality and reduce cost, as well as the activities and alignments of current federal programs with relevant responsibilities. It sets out a series of recommendations intended to facilitate private, entrepreneurial initiatives through governmental action to speed development of a “universal exchange language” for health information, the application of which would maximize the ability to use existing and developing electronic record systems. Specifically, it recommends action by the federal government—especially ONC and CMS—accelerate the iden- tification of standards required for health information exchange using metadata-tagged data elements, map various existing semantic taxonomies onto the tagged elements, develop incentives for product use of tagged ele- ments; foster use of metadata for security and safety protocols, bring federal program capacity and policy leverage to bear in implementing and guiding the efforts, and develop metrics to assess progress. The PCAST recommen- dations are included in Appendix E. ABOUT THE DIGITAL INFRASTRUCTURE MEETINGS As indicated by the title of this report, the primary intent of the meet- ings was to identify and explore strategic opportunities for accelerating the evolution of a digital infrastructure necessary to support and drive con- tinuous assessment, learning, and improvement in health and health care. Three meetings were held in the summer and fall of 2010, bringing together researchers, computer scientists, privacy experts, clinicians, healthcare ad- ministrators, HIT professionals, representatives of patient advocacy groups, healthcare policy makers, and other stakeholders. A planning committee,1 composed of leading authorities on various aspects of the digital health learning process, established the main objectives for the workshop series. The series began by fostering a shared understand- 1 Institute of Medicine planning committees are solely responsible for organizing the workshop, identifying topics, and choosing speakers. The responsibility for the published workshop summary rests with the workshop rapporteurs and the institution.

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68 ENGINEERING A LEARNING HEALTHCARE SYSTEM ing of the vision for the digital infrastructure for continuous learning and quality-driven health and healthcare programs by building on the existing foundations of HIT. Following the establishment of a vision, participants explored the current capacity, approaches, incentives, and policies and identified key technological, organizational, policy, and implementation priorities for the development of the digital infrastructure. Finally, partici- pants considered strategy elements and priorities for accelerating progress on building a more seamless learning enterprise that will improve the health and health care of Americans. Several contextual considerations informed the Committee’s develop- ment of the agenda. These included rapid developments in information technology that promise to facilitate exponentially the potential of health data for knowledge generation and care improvement—these developments include federated and distributed research approaches that allow data to remain local while enabling querying and virtual pooling across systems, as well as ongoing innovation in search technologies with the potential to accelerate use of available data from multiple sources for new insights. Accordingly, considerations included developing standards that will fa- cilitate distributed access to large datasets for comparative effectiveness research, biomarker validation, disease modeling, and improving research processes. This technological promise, coupled with policy initiatives like HITECH and the ACA that encourage the digital capture and storage of health data, provide starting points, incentives, and guidance, while encour- aging innovation. Additionally, the committee considered the coevolving re- quirement for governance policies that foster strengthening the data utility as a core resource to advance the common good; in particular by cultivating the trust fabric among stakeholders and accelerating collaborative prog- ress. Hand in hand with these were practical considerations including the increasing appreciation of the need to limit the burden of health data collec- tion to the issues most important to patient care and knowledge generation. The three workshops in the series progressed from a broad explora- tion of the state of play and various stakeholder perspectives on a learning health system, to a more specific identification of strategic approaches to components of the challenge, and concluded with detailed discussions of strategic elements, stakeholder responsibilities, and key crosscutting chal- lenges. To maximize the identification and sharing of perspectives, expert presentations were followed by open discussion among participants and separate small group discussion sessions were incorporated in all of the workshops. The first workshop, “Opportunities, Challenges, Priorities,” consid- ered the overall vision of the digital infrastructure for the learning health system as well as some of the prominent issues and opportunities related to technical progress, ensuring commitment to population and patient

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69 INTRODUCTION needs, development of the necessary trust fabric, stewardship and gover- nance, and the implications of a global character of the health data trust. These presentations are captured in the speaker-authored manuscripts in Chapters 2 through 8. The second meeting, “The System After Next,” went deeper into three cross cutting areas identified during the first work- shop: engaging the patient and population, promoting technical advances, and fostering stewardship and governance structures. The third and final meeting of the series, “Strategy Scenarios,” reviewed the common themes and information from the previous workshops and extended into deeper consideration of strategy elements, opportunities, responsibilities, and next steps for progress on four key focus areas: technical progress, knowledge generation and use, patient and population engagement, and governance. An integrated summary of the discussions during the second and third meet- ings is captured in Chapters 9 and 10. Collectively, the discussions captured in this publication represent un- precedented promise for innovation and progress in health and health care. Yet, the discussions also underscored that without successful efforts to cre- ate the conditions necessary for seamless interoperability, to build the pro- tocols for enhanced access and use of available information for knowledge generation, and to nurture a culture of engagement and support on behalf of the sort of information utility possible, the potential will go unmet. By thoroughly and candidly engaging in discussions on the vision, the current state of the system, the key priorities for future work, and the strategic elements for accelerating progress, participants have set in motion perspec- tives that can quicken the progress in building the digital infrastructure required for the continuously learning health system necessary to ensure better health for all. REFERENCES Blumenthal, D., and M. Tavenner. 2010. The “meaningful use” regulation for electronic health records. New England Journal of Medicine 363(6):501-504. CHCF (California HealthCare Foundation). 2010. New national survey finds personal health records motivate consumers to improve their health. http://www.chcf.org/media/press- releases/2010/new-national-survey-finds-personal-health-records-motivate-consumers-to- improve-their-health#ixzz12kT8FU00 (accessed October 18, 2010). DesRoches, C. M., E. G. Campbell, S. R. Rao, K. Donelan, T. G. Ferris, A. Jha, R. Kaushal, D. E. Levy, S. Rosenbaum, A. E. Shields, and D. Blumenthal. 2008. Electronic health records in ambulatory care—a national survey of physicians. New England Journal of Medicine 359(1):50-60. Fox, S. 2010. E-patients, cyberchondriacs, and why we should stop calling names. http:// www.pewinternet.org/Commentary/2010/August/Epatients-Cyberchondriacs.aspx (ac- cessed October 19, 2010). IOM (Institute of Medicine). 2001. Crossing the quality chasm: A new health system for the 21st century. Washington, DC: National Academy Press.

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70 ENGINEERING A LEARNING HEALTHCARE SYSTEM ———. 2007. The learning healthcare system: Workshop summary. Washington, DC: The National Academies Press. Jha, A. K., C. M. DesRoches, P. D. Kralovec, and M. S. Joshi. 2010. A progress report on electronic health records in U.S. hospitals. Health Affairs (Millwood) 29(10):1951-1957. Smith, A. 2010. Mobile access 2010. http://www.pewinternet.org/Reports/2010/Mobile- Access-2010.aspx (accessed October 19, 2010).