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Summary The fundamental notion of the learning healthcare system—continuous improvement in effectiveness, efficiency, safety, and quality—is rooted in principles that medicine shares with engineering. In particular, the fields of systems engineering, industrial engineering, and operations research have long experience in the systematic design, analysis, and improvement of complex systems, notably in such large sectors as the airline and auto- mobile industries. Working cooperatively with the National Academy of Engineering (NAE), the Institute of Medicine (IOM) organized Engineering a Learning Healthcare System: A Look at the Future to bring together lead- ers from the fields of health care and engineering to identify particularly promising areas for application of engineering principles to the design of more effective and efficient health care—a learning healthcare system. This report presents the summary of the meeting’s discussions. Currently, the organization, management, and delivery of health care in the United States falls short of delivering quality health care reliably, consistently, and affordably. As health care continues to increase in scope and complexity, so will the challenges to efficiency. In part, the capacity to address these challenges will depend on the ability to develop information about the relative effectiveness of interventions in a fashion that is more timely and practical than is typically the case for individually designed prospective studies, such as randomized clinical trials. It will also depend on the ability to design delivery systems in which the dynamics at the com- ponent interfaces are much more efficient. In both cases, the adaptation of engineering principles to facilitate continuous learning will be key. 1

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2 ENGINEERING A LEARNING HEALTHCARE SYSTEM The goal of a learning healthcare system is to deliver the best care every time, and to learn and improve with each care experience. This goal is attainable only through system-wide changes of the sort that have been successfully undertaken in certain activities of the manufacturing sectors. In these cases significant benefits have been realized through organization- wide transformations guided by principles of systems and process engineer- ing and the practices of structured data feedback for process improvement. Data collection and monitoring are increasingly important components of health care, but much remains to be done in their application for continu- ous improvement. Engineering sciences associated with system design could contribute to a learning healthcare system that applies the best-known evidence, encourages continuous learning, and allows for knowledge gen- eration as a natural by-product of patient care delivery. A fully functional system of this sort would advance quality; improve patient and provider safety, in turn delivering increasing value to consumers; and ensure that the care that is delivered is centered on the best outcome for each patient. With these issues in focus, Engineering a Learning Healthcare System: A Look at the Future was organized by the National Academies to take stock of lessons from engineering that might be applicable to health, to investigate examples of efforts completed or under way in that respect, and to examine prospects for increasing the level of interdisciplinary, coopera- tive activity. The workshop was one of a series of workshops sponsored by the IOM Roundtable on Value & Science-Driven Health Care (then, the Roundtable on Evidence-Based Medicine) and focused on the development of a learning healthcare system. Because the workshop aimed to identify learning opportunities from health care, and teaching opportunities from engineering, it was structured both to review already well-established ex- amples of activities in which engineering principles—in particular, systems engineering—have been adapted for use in healthcare settings, as well as to encourage discussion of additional opportunities and approaches to foster- ing ongoing progress in communication between the two fields. An overview of the premises of the workshop identified by the work- shop planning committee is found in Box S-1. Throughout the meeting’s discussions, frequent mention was made of the cross-relevance of the con- cepts, and participants observed that even some of the terminology and reference points were similar—e.g., the discussions of Harold W. Sorenson and William W. Stead who addressed, respectively, how to engage health as a complex system, and approaches to adjusting to a more complex clini- cal decision environment. Case studies illustrated achievements in health care that have drawn upon systems engineering, and breakout sessions challenged workshop participants to identify opportunities and actions for generating additional value in health care through application of engineer- ing concepts. Neither the case studies nor the breakout sessions yielded

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 SUMMARY BOX S-1 Workshop Premises • ealth care is substantially underperforming on most dimensions: effective- H ness, appropriateness, safety, cost, efficiency, and value. • ncreasing complexity in health care is likely to accentuate current problems I unless reform efforts go beyond financing to foster significant changes in the culture, practice, and delivery of health care. • xtensive administrative and clinical data collected in healthcare settings are E largely unused for new insights on the effectiveness of healthcare interventions and systems of care. • f the effectiveness of health care is to keep pace with the opportunity of di- I agnostic and treatment innovation, system design and information technology must be structured to ensure application of the best evidence, continuous learning, and research insights generated as a natural by-product of the care process. • ngineering principles are at the core of a learning healthcare system—one E structured to keep the patient constantly in focus, while continuously improving quality, safety, knowledge, and value in health care. • mpressive transformations have occurred through systems and process en- I gineering in service and manufacturing sectors—e.g., banking, airline safety, automobile manufacturing. • espite the obvious differences that exist in the dynamics of mechanical vs. D biological and social systems, the current challenges in health care necessitate an entirely fresh view of the organization, structure, and function of the delivery and monitoring processes in health care. • aking on the challenges in health care offers the engineering sciences an op- T portunity to test, learn, and refine approaches to understanding and improving innovation in complex adaptive systems. breakthrough insights, but that fact itself is testament to the need for more systematic engagement of terms, education, and opportunities for jointly targeted projects. THE ROUNDTABLE AND THE LEARNING HEALTHCARE SYSTEM Convened in 2006 under the auspices of the IOM, the Roundtable on Value & Science-Driven Health Care provides a trusted setting for healthcare stakeholders—patients, employers, manufacturers, payers, policy makers, providers, and researchers—to discuss strategies to improve the ef- fectiveness and efficiency of the nation’s healthcare system. The Roundtable is therefore aimed at exploring ways in which health care may be improved through the systematic and routine capture and analysis of clinical data for

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 ENGINEERING A LEARNING HEALTHCARE SYSTEM point-of-care learning, the seamless application of insights to improve the effectiveness and efficiency of care processes, and the outcomes and value optimized for each patient and the system as a whole. It has devoted sub- stantial attention to prospects and strategies for substantially expanded use of clinical data, with careful attention to security and privacy protection, as a basic resource for the generation of new knowledge. Roundtable participants established a goal that, by the year 2020, 90 percent of clinical decisions will be supported by accurate, timely, and up-to-date clinical information, and will reflect the best aailable eidence (IOM Roundtable on Evidence-Based Medicine, 2005). Members are com- mitted to identifying, prioritizing, and addressing opportunities through ongoing public–private initiatives, including convening the Learning Health System series of workshops and resulting publications. To date, the work- shop series has included The Learning Healthcare System (July 2006) • J udging the Evidence: Standards for Determining Clinical Effective- • ness (February 2007) L eadership Commitments to Improve Value in Healthcare: Finding • Common Ground (July 2007) R edesigning the Clinical Effectiveness Research Paradigm: Innova- • tion and Practice-Based Approaches (December 2007) C linical Data as the Basic Staple of Health Learning: Creating and • Protecting a Public Good (February 2008) E ngineering a Learning Healthcare System: A Look at the Future • (April 2008) L earning What Works: Infrastructure Required for Comparative • Effectiveness Research (July 2008) V alue in Health Care: Accounting for Cost, Quality, Safety, Out- • comes, and Innovation (November 2008) T he Healthcare Imperative: Lowering Costs and Improving Out- • comes (May, July, September, and December 2009) • Patients Charting the Course: Citizen Engagement and the Learn- ing Health System (April 2010) • Digital Infrastructure for the Learning Health System: The Founda- tion for Continuous Improvement in Health and Health Care (July, September, and October 2010) Engineering a Learning Healthcare System: A Look at the Future was the sixth workshop in the Learning Health System series, and this chapter briefly summarizes the presentations, discussions, and recurring themes. The first day of the workshop provided insights into potential synergies

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 SUMMARY between engineering disciplines and healthcare challenges (Chapter 1) and guided the audience through some of the processes by which engineering deals with systems complexity (Chapter 2). The afternoon sessions on the first day lent insight into the complexities of health care (Chapter 3) and the mechanisms through which other industries have addressed complexity (Chapter 4). The second day’s presentations identified opportunities for systems improvement followed by a breakout session, and it concluded with observations on systems change (Chapter 5 and Berwick, Chapter 1, p. 53) and a discussion on opportunities to align policies with leadership opportunities. Chapter 6 explores the next steps for aligning policies with leadership opportunities and summarizes the common themes and issues for the Roundtable’s attention. The workshop agenda, biographical sketches of participants, and a list of attendees can be found in the appendixes. COMMON THEMES The presentations and discussions within the workshop highlighted multiple opportunities for applying engineering principles in the establish- ment of a learning healthcare system. The presentations and discussions also provided insight into engineering approaches to systems complexity and identified critical areas that need attention in health care. Throughout the 2 days of the workshop, a set of common themes emerged as recurring elements of the discussion (Box S-2). T he system’s processes must be centered on the right target—the • patient. Patient-centered care was defined in the 2001 IOM report Crossing the Quality Chasm as providing care that is respectful of and responsive to individual patient preferences, needs, and values and ensuring that patient values guide all clinical decisions (IOM, 2001). However, health care is by nature highly complex, involving multiple participants and parallel activities that sometimes take on a character of their own, independent of patient needs or desires. Throughout several sessions, workshop participants emphasized the need to ensure that processes support patients—and that pa- tients are not forced into processes. Patient needs and perspectives must be at the center of all process design, technology application, and clinician engagement. S ystem excellence is created by the reliable deliery of established • best practice. Identifying and embedding practices that work best, and developing the system processes to ensure their delivery every time, help to define excellence in system performance and to fo- cus the system on delivering the best possible care for patients. In health care, establishing practices from the best available evidence

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 ENGINEERING A LEARNING HEALTHCARE SYSTEM and building them as routines into practice patterns, as well as de- veloping systems to document results and update best practices as the evidence evolves, will integrate some of the best elements from the engineering disciplines into healthcare issues. Participants often cited the need for better integration of development and commu- nication of best practices in healthcare systems, as well as the need for process systems to track healthcare details and outcomes, with feedback for practice refinement and better patient outcomes. C omplexity compels reasoned allowance for tailored adjustments. • Established routines may need circumstance-specific adjustments related to differences in the appropriateness of established health- care regimens for various individuals, variations in caregiver skill, and the evolving nature of the science base—or all three. Mass customization and other engineering practices can help assure a consistency that can accelerate the recognition of the need for tailoring and delivering the most appropriate care—with the best prospects for improved outcomes—for the patient. Participants pointed to the need for the development of a system of care flex- ible enough to incorporate these considerations and to leverage the lessons learned from their employment in a process of continuous learning. BOX S-2 Workshop Common Themes • The system’s processes must be centered on the right target—the patient. • System excellence is created by the reliable delivery of established best practice. • Complexity compels reasoned allowance for tailored adjustments. • Learning is a non-linear process. • Emphasize interdependence and tend to the process interfaces. • Teamwork and cross-checks trump command and control. • Performance, transparency, and feedback serve as the engine for improvement. • Expect errors in the performance of individuals but perfection in the perfor- mance of systems. • Align rewards on key elements of continuous improvement. • Education and research can facilitate understanding and partnerships between engineering and the health professions. • Foster a leadership culture, language, and style that reinforce teamwork and results.

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 SUMMARY earning is a non-linear process. The focus on an established hier- L • archy of scientific evidence as a basis for evaluation and decision making cannot fully accommodate the fact that much of the sound learning in complex systems occurs in local and individual settings. Participants cited the need to bridge the gap between dependence on formal trials, such as randomized clinical trials, and the experi- ence of local improvement in order to speed learning and avoid impractical costs. mphasize interdependence and tend to the process interfaces. A E • system is most vulnerable at links between critical processes. In health care, attention to the nature of relationships and hand-offs between elements of the patient care and administrative processes is therefore vital and a crucial component of focusing the process on the patient experience and improving outcomes. eamwork and cross-checks trump command and control. Espe- T • cially in systems designed to guarantee safety, system performance that is effective and efficient requires careful coordination and teamwork as well as a culture that encourages parity among all those with established responsibilities. During the workshop, sev- eral examples were cited of other industries that have used systems design and social engineering to better integrate and strengthen their systems processes with great improvements in efficiency and safety. P erformance, transparency, and feedback sere as the engine for • improement. Continuous learning and improvement in patient care requires transparency in processes and outcomes as well as the ability to capture feedback and make adjustments. E xpect errors in the performance of indiiduals, but perfection in • the performance of systems. Human error is inevitable in any sys- tem and should be assumed. On the other hand, safeguards and de- signed redundancies can deliver perfection in system performance. Mapping processes and embedding prompts, cross-checks, and information loops can assure best outcomes and allow human ca- pacity to focus on what can not be programmed—compassion and individual patient needs. Several workshop presentations shared success stories and lessons learned from other industries, such as the automotive and airline industries, that have effectively incor- porated this strategy. A lign rewards on the key elements of continuous improement. • Incentives, standards, and measurement requirements can serve as powerful change agents. Therefore, it is vital that they be carefully considered and directed to the targets most important to improv- ing the patient and provider experiences. Participants noted that it

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8 ENGINEERING A LEARNING HEALTHCARE SYSTEM is vital that incentives be carefully considered and directed to the targets most important to improving the efficiency, effectiveness, and safety of the system—and ultimately patient outcomes—as well as taking into consideration the patient and provider experiences. E ducation and research can facilitate understanding and partner- • ships between engineering and the health professions. The relevance of systems engineering principles to health care and the impressive transformation brought to other industries speaks to the merits of developing common vocabularies, concepts, and ongoing joint education and research activities that help generate stronger ques- tions and solutions. Workshop participants pointed to the dearth of training opportunities bridging these two professions and spoke of the need to encourage greater collaborative work between them. F oster a leadership culture, language, and style that reinforce team- • work and results. Positive leadership cultures foster and celebrate consensus goals, teamwork, multidisciplinary efforts, transparency, and continuous monitoring and improvement. In citing examples of successful learning systems, participants highlighted the need for a supportive and integrated leadership. PRESENTATION AND DISCUSSION SUMMARIES The workshop opened with keynote addresses outlining the current challenges faced in health care and suggesting pathways by which engi- neering principles might improve the way care is delivered. Sessions that followed examined how engineering disciplines engage system complexity, explored some of the impediments and failures in health care that engineer- ing might help ameliorate, and presented case studies of successful transfor- mations via applied systems engineering. Further sessions looked in depth at the value that could be derived from systemic change in the healthcare system, at specific types of change that would create the greatest value, and at the entities and actions that might best facilitate change. Engineering a Learning Healthcare System Opening the workshop and providing context for the meeting were Brent C. James, executive director of the Institute for Health Care Delivery Research at Intermountain Healthcare, and W. Dale Compton, the Lillian Gilbreth Distinguished Professor (Emeritus) of Industrial Engineering at Purdue University. In his keynote on the second day, Donald M. Berwick, then president and chief executive officer (CEO) of the Institute for Health- care Improvement, offered an overview of some of the key factors in ini- tiating health system change. Together, the speakers addressed the central

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9 SUMMARY systemic shortfalls and challenges in health care today, reflecting on the changes needed and how systems engineering might help foster a healthcare system that delivers care that we know works, and that learns from the care delivered. Learning Opportunities for Health Care As the first keynote speaker, James suggested that the healthcare indus- try is experiencing the results of a disconnect between the rapid expansion of knowledge and the traditional cultural and organizational constructs of modern medicine. This incongruity has created a system that has certain strengths, such as excellent rescue care, but also has many weaknesses, including inadequate primary and preventive care, spiraling costs, and inef- ficient and ineffective care delivery. James identified several current weaknesses in the care delivery sys- tem as opportunities for improvement, including high levels of variation in services and outcomes, with often inverse associations between service intensity and outcomes; increasing rates of inappropriate care, where the risk to the patient outweighs potential benefits; unacceptable rates of care associated with adverse outcomes; inconsistent application of evidence; and significant waste within the system, leading to increased prices and limited access to care. Although the healthcare industry continues to develop solutions at vari- ous loci in the system, James stressed the importance of additional stron- ger and more sustained gains that might be achieved through engineering approaches to system redesign. Opportunities include efforts to improve the protocols and predictability of care delivered, the implementation of team-based processes, structured engagement of care complexity, and active management of knowledge and learning. Perhaps most important over the long term, James said, is designing health care to be fully coordinated and interconnected as a key to the future effectiveness of American medicine. Teaching Opportunities from Engineering Framing the range of possible responses to the identified healthcare challenges from the engineering field, Compton discussed some of the op- portunities available in making changes to a large system such as health care. He identified two particular areas where engineering can help: the or- ganization of the delivery system and its structure. Compton suggested that appreciation of the engineering tool set can begin by clarifying several main elements, including healthcare system objectives, performance parameters, and existing control points within the system. Compton also provided rel- evant examples of quality and process improvement from large commercial

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10 ENGINEERING A LEARNING HEALTHCARE SYSTEM product industries, including Ford Motor Company and Toyota, and sug- gested that they have relevance to current challenges facing the healthcare system. In particular, he posited that engineering principles that support continuous improvement by leveraging data, and empowering all members of the organization to communicate and participate, hold much promise for the movement toward a learning healthcare system. In the long term, Compton said, medical and engineering professionals will need to work together much better to create common vocabulary and understanding. Specific solutions offered during his presentation included multidisciplinary involvement in research, tool development and applica- tion, and the generation and implementation of new interdisciplinary edu- cational models for both medical and engineering professions (NAE/IOM, 2005). Obserations on Initiating Systems Change in Health Care Citing the general areas of technique, culture, training, and economics, Berwick offered an assessment of the major challenges to the successful ap- plication of systems thinking to health care, stemming fundamentally from its basic design. That is, improvement will require fundamental changes to the system, not simply “trying harder.” Berwick outlined seven major deficiencies that must be overcome to truly wed medicine and systems knowledge: (1) a lack of emphasis on co- ordination and interdependence in the current practice of medicine; (2) the lack of a patient-centered approach to the care process; (3) the lack of ap- preciation of the power of dynamic learning and local adaptation; (4) a lack of knowledge about, or action to counteract, waste within the system; (5) the absence of a platform for interdisciplinary research and collaboration between health care and systems engineering; (6) the absence of systems thinking in the current process of healthcare providers’ professional devel- opment; and (7) the lack of incentives or levers for the vast institutional rearrangement necessary to achieve the potential offered in the application of systems science to the healthcare system. Drawing on examples, Berwick both identified the challenges and set the stage for discussion of how systems engineering principles could succeed in drawing improvement from the intersection of health care and systems thinking. Engaging Complex Systems Through Engineering Concepts The meeting’s first panel discussion addressed how various engineering disciplines—including systems engineering, industrial engineering, opera- tions research, human factors engineering, financial engineering, and risk

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11 SUMMARY analysis—deal with system complexity and how these approaches might inform and improve health care. Speakers provided examples of past suc- cesses in other industries and offered analyses about what can be learned from the contrasts. Systems Engineering Perspecties William B. Rouse, executive director of the Tennenbaum Institute at the Georgia Institute of Technology, provided perspectives and principles related to systems engineering approaches to complex problems, including health care. He emphasized that engineering builds on scientific findings and works to identify ways to redesign and provide for better system controls. As a starting point, Rouse emphasized the importance of a common understanding between the healthcare and engineering vocabularies. In elaborating, he reviewed a number of engineering concepts that have ap- plicability to health care. One class of concepts concerns the operation of a system, including measurement, defining and measuring the state of a system; feedback, comparing desired and actual outcome states of the system; and control, influencing system input to correct for differences be- tween the desired and actual states. A second class of concepts concerns the creation of a system to achieve objectives of interest. The elements of this class include analysis, understanding input–output relationships, including uncertainties; synthesis, configuring input–output relationships to achieve objectives; design, integrating input–output relationships; production, cre- ating systems that embody desired relationships; and sustainment, creating mechanisms to ensure the achievement of future objectives. He then went on to show how engineers use mathematical modeling to analyze the phe- nomena of spiraling healthcare costs caused by technological innovation, noting multiple opportunities for increased system efficiency. Engineering Systems Analysis Tools Operations research (OR) uses aspects of the scientific method to help frame, formulate, and solve difficult operations problems involving people and technology. Richard C. Larson, the Mitsui Professor of Engineering Systems and Civil and Environmental Engineering and director of the Cen- ter for Engineering Systems Fundamentals at the Massachusetts Institute of Technology, described the evolution of OR and provided several models of its applications in health care. Strongly systems oriented, OR has been used successfully to improve aspects of performance in healthcare settings and therefore has value and potential in developing learning healthcare systems. Larson described how OR was used to advance cancer therapeutics

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1 ENGINEERING A LEARNING HEALTHCARE SYSTEM ment and feedback. He described some important lessons associated with data-driven analysis and decision making for identifying opportunities and motivating change. The UPHS experience with workflow redesign and role restructuring, based in part on integrated IT, facilitated the identifica- tion of goals and improvement in performance. Muller discussed UPHS’s approaches to engaging physicians, management, and staff in systems im- provement initiatives as a testament to the possibility of gaining efficiency yields in an overwhelmingly complex American healthcare system through incremental changes at individual institutions. Information Knowledge and Deelopment As the nation’s healthcare system moves toward increasingly integrated information systems, it will be important to support information exchange and knowledge management while evaluating and improving the quality and value of healthcare practices. Eugene C. Nelson, professor in the Dart- mouth Institute for Health Policy and Clinical Practice at Dartmouth Medi- cal School and director of quality administration at Dartmouth–Hitchcock Medical Center, presented a case study, based on the Dartmouth–Hitchcock Spine Center’s work, that illustrated the principles and methods of feed- forward, which builds feedback from past experiences into the future design and improvement of the system. Such an approach serves to increase the efficiency of patient care as well as to generate and manage new informa- tion about individual patients and entire patient populations. In his presentation, Nelson outlined how the Spine Center’s system focuses on the critical function of patient-reported data embedded into the process of healthcare delivery, including some of the complexities associated with developing patient-centered, feed-forward data systems. In particular, he highlighted the challenges stemming from embedding decision-support evidence into the care delivery process, and he advocated “collaboratories” in which professionally organized networks for both care and care research could develop sustainable feed-forward data systems. Case Studies in Transformation Through Systems Engineering Several workshop case studies illustrated the successful application of systems engineering in various circumstances and sectors. Airline Safety The aviation industry has successfully integrated engineering solutions that transformed safety outcomes. John J. Nance, founding member of the National Patient Safety Foundation, discussed the possibilities sug-

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1 SUMMARY gested by the aviation industry’s experience. Nance summarized elements of aviation’s use of engineering principles, including critical feedback sys- tems associated with detecting and managing mechanical problems and the notion of “exquisite redundancy.” The airlines built a system around the assumptions that humans are imperfect and that systems can be structured to correct—and even anticipate—human errors through training programs, procedure standardization, and variable minimization. He described the need for healthcare systems to plan for and expect failure in every aspect as well as the need for acceptance of these realities operationally and cultur- ally. The wide scope and variety of engineering experiences adopted in avia- tion could be directly applicable to health care, legitimizing and inculcating known best practices, eliminating the need to reinvent every procedure, and providing operational buffers against human fallibility in order to allow for safer care delivery systems, Nance said. Alcoa’s Reorientation Innovations designed and implemented by organizations can advance the frontiers of business operations. Earnest J. Edwards, senior vice presi- dent and controller (retired) of Alcoa, Inc., and now the vice chair of Mar- tha Jefferson Health Service, offered what he called the five basic truths of organizational innovation: (1) high quality in tandem with low cost creates high efficiency, (2) informed decision making originates in effective systems, (3) change agents are solution-oriented, (4) strategic planning is preferred over historical reporting, and (5) vital business partners leverage their roles to make strategic decisions. Edwards described successful applications of cycle-time reduction in the financial closing process in a leading company (Alcoa), a major government agency (the U.S. Treasury), and a community hospital (Martha Jefferson Health Service) that all achieved their goals through the application of five key strategies: (1) expecting high value, (2) effectively using information, (3) becoming solution oriented, (4) focusing on planning the future, and (5) becoming vital business partners with expanded roles in strategic decisions. In addition to streamlining financial functions, projects to reduce financial closing cycles at each of these companies provided more timely information for business decision making, served as an example of how to make major improvements to a routine process, and were a major motivating force for the staff of the organizations. Health care could benefit by adopting similar programs, he suggested.

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18 ENGINEERING A LEARNING HEALTHCARE SYSTEM Veterans Health Affairs The veterans healthcare system, managed by the Veterans Health Ad- ministration in the U.S. Department of Veterans Affairs (VA), is the larg- est integrated healthcare system in the United States. As recently as the 1990s, the VA system was widely criticized for providing fragmented and disjointed care that was expensive, difficult to access, and insensitive to in- dividual needs. Kenneth W. Kizer, chair of Medsphere Systems Corporation, described the radical re-engineering of VA health care that was launched in 1995, a program aimed at creating a continuum of consistent, predictable, high-quality, patient-centered care. The effort was based on specific inter- related and overlapping strategic goals: (1) create an accountable manage- ment structure and control system, (2) integrate and coordinate services across the continuum of care, (3) improve and standardize the quality of care, (4) modernize information management, and (5) align the system’s finances with desired outcomes. The effect of the reform was transformative. In recent years, the Veter- ans Health Administration has been hailed as providing the best health care in the United States and is held out as an exemplary model of high-quality, low-cost (i.e., high value) health care. Kizer reviewed some of the systemic changes integral to the transformation and some of the improvements in performance. Examples include decentralizing operational decision making and instituting both the computerized patient record system and the veter- ans equitable resource allocation methodology. He declared that relatively simple interventions can be implemented and hold promise for the reform of health care. Ascension Health Ascension Health is the largest not-for-profit healthcare delivery system in the United States, the largest Catholic healthcare system, and the third largest healthcare system overall (after the VA and the Hospital Corpora- tion of America). David B. Pryor, the system’s chief medical officer, detailed Ascension Health’s “Call to Action,” a reform effort established in October 2002 that focused on three goals: health care that works, health care that is safe, and health care that leaves no one behind. During the presentation, Pryor focused on the steps taken to improve safety related to hospital mortality, adverse drug events, Joint Commission National Patient Safety Goals, nosocomial infections, falls and fall injuries, pressure ulcers, perinatal safety, and surgical complications, with the goal of no preventable injuries or deaths. Those steps addressed challenges in culture, infrastructure, the business case, standardization, and staff col- laboration. Strategies were derived for each challenge and implemented

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19 SUMMARY with great success. Pryor offered several crucial factors that contributed to this success, including a clear focus with accountable goals, transparency in results reporting, addressing all challenge areas, and a deep organizational commitment across all levels of leadership with mutual accountability. Fostering Systems Change to Drive Continuous Learning in Health Care The IOM workshop publication The Learning Healthcare System (2007) identified several common characteristics of a learning healthcare organization, including a culture that emphasizes transparency and learn- ing through continuous feedback loops, care as a seamless team process, best practices that are embedded in system design, information systems that reliably deliver evidence and capture results, and results that are captured and used as feedback to improve the level of practice and the state of the science. Each speaker addressed what feedback and performance improve- ment look like and how impediments can be turned into enablers. Learning, Team, and Patient-Oriented Culture In manufacturing, heavy industry, high-tech services, aviation, the mili- tary, and elsewhere, a small number of organizations will be innovative leaders. These innovators may use similar science and technology to meet the needs of a similar customer base, depend on the same group of suppli- ers, hire from the same labor pools, and be subject to the same regulations as other organizations in their fields, but they deliver far more value, often with less effort and at a lower cost. These “rabbits” gain and sustain leader- ship by managing their systems of work in markedly different ways. Steven J. Spear, senior lecturer at the Massachusetts Institute of Tech- nology and a senior fellow at the Institute for Healthcare Improvement, described several such “rabbits,” including Toyota and Southwest Airlines. He pointed out that healthcare organizations can and have learned from these types of companies, with impressive improvements in efficacy, effi- ciency, safety, and quality of care. Spear proposed that delivering better care to more people at lower costs and with less effort is achievable by adopting elements of “clinical evidence” from other organizations. He emphasized that these transformations require an approach of process reform rather than managing individual functions and also need continuous, dynamic monitoring and management. Knowledge Deelopment, Access, and Use In addition to requiring education and research agendas, knowledge management for clinical decision support (CDS) also requires a policy

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20 ENGINEERING A LEARNING HEALTHCARE SYSTEM framework. Donald E. Detmer, then president and CEO of the American Medical Informatics Association (AMIA) and professor of medical educa- tion at the University of Virginia, asserted that we do not have the appro- priate policy infrastructure to support some of these goals. Drawing from the AMIA CDS Roadmap for National Action, Detmer proposed several policy solutions. The AMIA recommends a three-pillar structure of timely availability of quality knowledge, high adoption and effective use, and continuous improvement of knowledge and methods. He noted that this roadmap was used by the U.S. Department of Health and Human Services to identify priorities for CDS development, including achieving measurable progress toward performance goals for healthcare quality improvement, exploring private–public partnerships to facilitate collaboration, and ac- celerating development and employment through federal programs and collaborations. Technology Management For health care, technology management is a growing issue that con- tinues to require significant attention. Because a large portion of the recent growth in healthcare expenditures is a direct outcome of technology devel- opment, many look to technology as an opportunity to streamline processes and reduce costs. Stephen J. Swensen, director of quality at the Mayo Clinic and professor of radiology in the Mayo Clinic College of Medicine, presented several perspectives on the issue of technology management in U.S. health care. Swensen outlined four primary elements of healthcare technology man- agement. First, policies—particularly those policies that create incentives, such as payment—can be central motivators of activities and performance. The appropriateness and reliability of technology offer opportunities in terms of managing the appropriate use and ensuring the high reliability of the technologies applied. Effective diffusion of best practices and safety nets is crucial for efficient and effective technology management, as it allows for the optimization of technology use. Finally, social engineering strate- gies, including transparency, team-work training, horizontal infrastructure, and cross-functional team-based simulations, can contribute to moving an organization toward integrated care coordination in which decisions are made with an organizational perspective. In conclusion, Swensen noted that, in order to reach technology management goals and provide reliable patient care, the healthcare industry must foster systems changes to drive continuous learning.

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21 SUMMARY Information Systems Organization and Management Simulation can help accelerate progress. Over the past decade, numer- ous healthcare delivery organizations have implemented clinical informa- tion systems in order to improve the quality and safety of patient care. Recent studies have suggested that, despite considerable investment in these systems, many organizations have failed in these efforts. David C. Classen, chief medical officer of First Consulting Group and an associate professor of medicine at the University of Utah, explored current approaches to evalu- ating clinical information systems and detailed a new simulation tool that has been developed and used by healthcare organizations to evaluate the effectiveness of these systems in improving the safety of care. He described several strategies for evaluating the computerized physician order entry system, one of the ways that hospitals work toward safe medication man- agement. These strategies included electronic health record (EHR) product certification as well as approaches by the National Quality Forum and the Leapfrog Group that employ simulation. Classen noted that the widespread use of simulation in these instances holds great promise for the evaluation of clinical information systems. Capturing More Value in Health Care During a breakout session, participants assembled in small groups to discuss the engineering approach likely to yield the greatest return in health, the amount of enhanced effectiveness and efficiency that might be anticipated, and what actions might facilitate change. The main points of their discussions were reported back to the entire group. In response to the question of how much more value (health returned for dollars invested) could be obtained through application of systems engineering principles in health care, respondents felt that the definition of value was problematic as it depends on the stakeholder in question. In con- trast, other small groups reported that based on some workshop estimates, suggesting that 50 percent of the current system resources were wasted, it was reasonable to assume that a doubling of value ought to be attainable through systematic changes, including realignment of payment incentives, health IT, and better systems integration. When asked to identify where the greatest value could be returned, participants listed a number of different areas. Among these were health IT, for better systemic coordination and informed decision making; education reform, for the necessary cultural changes within professions and greater interdisciplinary exposure and training; realignment of incentives to pro- mote best practices; greater emphasis on collaboration; better integration of

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22 ENGINEERING A LEARNING HEALTHCARE SYSTEM systems; adoption of processes that lead to use and evaluation; and adop- tion and implementation of process technologies. Responding to the question of which actions could do the most to facilitate the needed changes, participants elaborated on some of the areas mentioned previously. Participants noted that the approach to reform was important and should start with easy, manageable issues and progress to broader, more difficult reforms. This two-tiered approach would al- low for demonstrations of the potential for improvement and would thus provide the opportunity to get greater buy-in from stakeholders. Several groups mentioned the need to encourage a more collaborative approach to the care process that would involve multidisciplinary groups. Participants mentioned the need for changes in the current culture in order to allow for more integrated care, including reforms to the models of education for healthcare providers. Changes in the availability, implementation, and application of EHRs and health IT were discussed as ways to better communicate best practices, to allow for improved analysis of process and outcomes data that can be fed back and used to improve the system, and to create better continuity of care. In order to achieve this, however, interfaces between technology and users need to be redesigned to allow for ease of use and seamless integra- tion into the care process. Use of data from health IT systems to model and optimize care processes was discussed as a natural application of sys- tems engineering to health care, as was the idea of combining healthcare economics models with process engineering models to get a better grasp on measuring value. Participants also discussed the need for collaboration between process engineering and medical professional organizations and other groups concerning issues of education, nomenclature, and develop- ment of best practices and core performance measures. Finally, several groups mentioned the need to better define value in the context of a learning healthcare system and from the perspective of all of the stakeholders involved. This would make possible the creation of processes that allow for the measurement of value and its inclusion in decision-making processes. Next Steps: Aligning Policies with Leadership Opportunities A concluding panel discussion on aligning policies with leadership opportunities was held with five leaders from key settings in health care reflecting on their visions for changes in practice, policy, and culture. Con- tributing members of the panel discussion were Denis A. Cortese of the Mayo Clinic, Paul F. Conlon of Trinity Health, Mary Jane Koren of The Commonwealth Fund, Louise L. Liang of Kaiser Permanente, and Douglas W. Lowery-North of Emory University.

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2 SUMMARY Several of the themes mentioned previously were raised again and expanded upon during the question-and-answer session with the panel- ists. Cortese, for example, shared his experiences with the achievement of interoperable systems for radiology, pointing out that it was driven by de- mands from the radiology professional groups. There was also discussion of the need for consideration of interoperability on the part of manufacturers in their business models as well as the need for agreement on requirements on the part of potential IT systems users in order to allow for the emergence of a unified market. The need for a patient-centered approach was a common theme in pan- elists’ comments. This included the use of market segmentation strategies (e.g., mass customization) to allow for the identification and individualized targeting of different groups as well as for the consideration of patient preferences in treatment and care coordination strategies. The need for the development of value standards that factor in out- comes, safety, and cost was discussed. Panelists suggested the development of such standards for the five most common diseases as a potential first step and emphasized the need for transparency in this and all development processes. One of the panelists proposed a human resources–focused approach to initiating reform. It would be aimed at encouraging the training of new professionals in both health care and systems engineering, as well as col- laboration across those fields, and it could incentivize participation with such strategies as debt relief for new trainees. Finally, panelists voiced an overarching concern about potential sup- port for the work that is needed to reengineer the healthcare system and hence the importance of reforming financial incentives throughout the system. AREAS FOR INNOVATION AND COLLABORATIVE ACTION Presentations and discussions during the workshop offered insights into the opportunities for Roundtable members to consider along with possible follow-up actions for ongoing multistakeholder involvement to advance the integration of engineering sciences into healthcare systems improvement. Areas mentioned as possibilities include the following: 1. Clarify terms: The ability of healthcare professionals to draw upon relevant and helpful engineering principles for system improve- ment could be facilitated by a better mutual understanding of the terminology. A collaborative effort by the IOM and the NAE could create a targeted glossary and develop potentially bridging terminology for use as appropriate.

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2 ENGINEERING A LEARNING HEALTHCARE SYSTEM 2. Identify best practices: Three areas of systems orientation are par- ticularly important to improving the efficiency and effectiveness of health care: (1) focusing the system elements more directly on the key outcome—the patient experience; (2) ensuring transparency in the performance of the system and its players and components; and (3) establishing a culture that emphasizes teamwork, consistency, and excellence. Progress could be accelerated by identifying and disseminating examples of best practices from health care and from engineering on each of these dimensions. 3. Explore health professions education change: In the face of a rapidly changing environment in health care—the expansion of diagnostic and treatment options, much greater knowledge avail- able, movement beyond the point at which any one individual can personally hold all the information necessary, and IT that opens new capabilities—changes to the education of health professionals can advance caregiver skills in knowledge navigation, teamwork, patient–provider partnership, and process awareness. 4. Adance the science of payment for alue: With cost increases in health care consistently outstripping gains in performance by most measures, progress toward counteracting this trend could be achieved with a stronger focus on ways to enhance both health and economic returns from healthcare investments. This could include work in the areas of understanding, measuring, and providing in- centives for value in health care. 5. Explore fostering the deelopment of a science of waste assessment and engagement: Similarly, and directly related, an exploration of the elements of inefficiency in health care, how to define and mea- sure waste, and how to mobilize responses to eliminating waste could contribute to increasing value within healthcare systems. 6. Support the deelopment of a robust health IT system: The de- velopment of a health IT system, designed with systems-related continuous improvement principles in mind, must lie at the core of an efficient, effective learning system. Beginning with challenges to EHR adoption, much work remains in order to achieve a system that allows for continuous learning; permits data sharing, includ- ing the construction of databases; employs consistent standards; and addresses privacy and security concerns. Health IT is a natural place for collaborative work between engineers and caregivers, beginning with better resolution of barriers to the achievement of such a system through the employment of both expert lenses.

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2 SUMMARY REFERENCES IOM (Institute of Medicine). 2001. Crossing the quality chasm: A new health system for the 21st century. Washington, DC: National Academy Press. _____. 2007. The learning healthcare system. Washington, DC: The National Academies Press. IOM Roundtable on Evidence-Based Medicine. 2005. Roundtable on Eidence-Based Medi- cine charter and ision statement. Washington, DC: The National Academies Press. NAE (National Academy of Engineering)/IOM. 2005. Building a better deliery system: A new engineering/health care partnership, edited by P. P. Reid. W. D. Compton, J. H. Grossman, and G. Fanjiang. Washington, DC: The National Academies Press.

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