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Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
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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 automobile 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 leaders 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 component interfaces are much more efficient. In both cases, the adaptation of engineering principles to facilitate continuous learning will be key.

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×

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 engineering 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 continuous 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 generation 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, cooperative 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 examples 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 fostering ongoing progress in communication between the two fields.

An overview of the premises of the workshop identified by the workshop planning committee is found in Box S-1. Throughout the meeting’s discussions, frequent mention was made of the cross-relevance of the concepts, 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 clinical 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 engineering concepts. Neither the case studies nor the breakout sessions yielded

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×

BOX S-1
Workshop Premises

  • Health care is substantially underperforming on most dimensions: effectiveness, appropriateness, safety, cost, efficiency, and value.
  • Increasing complexity in health care is likely to accentuate current problems unless reform efforts go beyond financing to foster significant changes in the culture, practice, and delivery of health care.
  • Extensive administrative and clinical data collected in healthcare settings are largely unused for new insights on the effectiveness of healthcare interventions and systems of care.
  • If the effectiveness of health care is to keep pace with the opportunity of diagnostic 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.
  • Engineering principles are at the core of a learning healthcare system—one structured to keep the patient constantly in focus, while continuously improving quality, safety, knowledge, and value in health care.
  • Impressive transformations have occurred through systems and process engineering in service and manufacturing sectors—e.g., banking, airline safety, automobile manufacturing.
  • Despite the obvious differences that exist in the dynamics of mechanical vs. 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.
  • Taking on the challenges in health care offers the engineering sciences an opportunity 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 effectiveness 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

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×

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 substantial 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 available evidence (IOM Roundtable on Evidence-Based Medicine, 2005). Members are committed 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 workshop series has included

  • The Learning Healthcare System (July 2006)
  • Judging the Evidence: Standards for Determining Clinical Effectiveness (February 2007)
  • Leadership Commitments to Improve Value in Healthcare: Finding Common Ground (July 2007)
  • Redesigning the Clinical Effectiveness Research Paradigm: Innovation and Practice-Based Approaches (December 2007)
  • Clinical Data as the Basic Staple of Health Learning: Creating and Protecting a Public Good (February 2008)
  • Engineering a Learning Healthcare System: A Look at the Future (April 2008)
  • Learning What Works: Infrastructure Required for Comparative Effectiveness Research (July 2008)
  • Value in Health Care: Accounting for Cost, Quality, Safety, Outcomes, and Innovation (November 2008)
  • The Healthcare Imperative: Lowering Costs and Improving Outcomes (May, July, September, and December 2009)
  • Patients Charting the Course: Citizen Engagement and the Learning Health System (April 2010)
  • Digital Infrastructure for the Learning Health System: The Foundation 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

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×

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 establishment 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).

  • The 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 patients are not forced into processes. Patient needs and perspectives must be at the center of all process design, technology application, and clinician engagement.
  • System excellence is created by the reliable delivery 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 focus the system on delivering the best possible care for patients. In health care, establishing practices from the best available evidence
Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×

     and building them as routines into practice patterns, as well as developing 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 communication 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.

•    Complexity compels reasoned allowance for tailored adjustments. Established routines may need circumstance-specific adjustments related to differences in the appropriateness of established healthcare 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 flexible 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 performance 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.
Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×
  • Learning is a non-linear process. The focus on an established hierarchy 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 experience of local improvement in order to speed learning and avoid impractical costs.
  • Emphasize interdependence and tend to the process interfaces. A 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.
  • Teamwork and cross-checks trump command and control. Especially 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, several 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.
  • Performance, transparency, and feedback serve as the engine for improvement. Continuous learning and improvement in patient care requires transparency in processes and outcomes as well as the ability to capture feedback and make adjustments.
  • Expect errors in the performance of individuals, but perfection in the performance of systems. Human error is inevitable in any system and should be assumed. On the other hand, safeguards and designed redundancies can deliver perfection in system performance. Mapping processes and embedding prompts, cross-checks, and information loops can assure best outcomes and allow human capacity 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 incorporated this strategy.
  • Align rewards on the key elements of continuous improvement. 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 improving the patient and provider experiences. Participants noted that it
Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×

    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.

•   Education and research can facilitate understanding and partnerships 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 questions 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.

•   Foster a leadership culture, language, and style that reinforce teamwork 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 engineering 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 engineering might help ameliorate, and presented case studies of successful transformations 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 Healthcare Improvement, offered an overview of some of the key factors in initiating health system change. Together, the speakers addressed the central

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×

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 industry 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 inefficient and ineffective care delivery.

James identified several current weaknesses in the care delivery system 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 various loci in the system, James stressed the importance of additional stronger 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 opportunities available in making changes to a large system such as health care. He identified two particular areas where engineering can help: the organization 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 relevant examples of quality and process improvement from large commercial

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×

product industries, including Ford Motor Company and Toyota, and suggested 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 application, and the generation and implementation of new interdisciplinary educational models for both medical and engineering professions (NAE/IOM, 2005).

Observations 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 application 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 coordination and interdependence in the current practice of medicine; (2) the lack of a patient-centered approach to the care process; (3) the lack of appreciation 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 development; 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, operations research, human factors engineering, financial engineering, and risk

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×

analysis—deal with system complexity and how these approaches might inform and improve health care. Speakers provided examples of past successes in other industries and offered analyses about what can be learned from the contrasts.

Systems Engineering Perspectives

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 applicability 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 between 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, creating 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 phenomena 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 Center 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

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
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through sophisticated optimization modeling and computational techniques, yielding a much safer and more reliable treatment that saved an estimated $459 million per year. He described the development of a needle exchange program in New Haven based on the application of OR modeling techniques to reduce the spread of HIV among injection drug users, leading to a 33 percent reduction in HIV/AIDS incidence. Finally, he cited his own work on the low-probability/high-consequence event of a repeat pandemic influenza on the scale of 1918, in which application of OR principles has helped to plan the application of nonpharmaceutical interventions as part of local governments’ disaster planning. Larson went on to state that the most effective applications of OR to health care are likely still in the future and called for mobilization toward that goal.

Engineering Systems Design Tools

Health care can be evaluated as a service system. Indeed, the engineering of health care must recognize the fact that any service system is actually a complex integration of human-centered activities that is increasingly dependent on information technology (IT), and knowledge. As described by James M. Tien, distinguished professor and dean of the College of Engineering at the University of Miami, a service system could be considered a combination of three essential components: people, processes, and products. Services management includes managing all three toward a common end.

Tien provided an alternative systems management view of services and discussed the increasing complexity of systems, especially service systems with the attendant lifecycle design, human interface, and system integration issues. Additional elements of complexity include the increasing need for real-time, adaptive decision making within systems and the increasingly human-focused modern systems. Such a focus, Tien suggested, creates complex, customized, and personalized products and services. Methods currently used in the production of goods can be applied to improve services, such as ongoing health care, in processes that progress, for example, from supply-driven to demand-driven and from mass production to mass customization.

Engineering Systems Control Tools

In considering an approach for engineering complex healthcare systems, a patient-focused perspective is the necessary place to begin, according to Harold W. Sorenson, professor of mechanical and aerospace engineering in the Jacobs School of Engineering at the University of California, San Diego. According to Sorenson, an “integrated perspective” merges the views of management and engineering communities in navigating enterprise com-

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×

plexity. In health care this means marhsalling data, feedback, and control systems to improve performance in the close working relationships among all stakeholders, including healthcare administrators and practitioners, enterprise architects, and enterprise systems engineers. This notion, if successfully applied, could fundamentally change the culture, practice, and delivery of health care in the United States.

Healthcare System Complexities, Impediments, and Failures

The meeting then turned to a discussion of the inefficiencies, impediments, structural barriers, and failures within the current healthcare system that are most in need of attention and correction for progress toward a learning healthcare system to occur, with speakers offering insights on how systems engineering could address these issues.

Healthcare Culture

William W. Stead, McKesson Foundation Professor of Biomedical Informatics and Medicine and associate vice chancellor for strategy/transformation and Chief Information Officer at the Vanderbilt University Medical Center, addressed the human side of the system, one with a culture that is deep-rooted and complex and that may not always obey prescribed principles. The healthcare culture in the United States is one dominated by the current systems of education and professional survival, but it is also challenged by individual, competing forces that face discontinuous, disruptive change. In order to achieve meaningful improvement of the system and be poised to handle the continuous, disruptive change that is a fact of modern medicine, the culture will need to change to one that is outcome-driven and that values collaboration. Stead posited that opportunities for efficient and effective patient care will continue to be missed unless the healthcare culture fundamentally changes in areas such as decision-making processes, payment mechanisms, and care planning. To effect a cultural shift away from one where practitioners are instructed to trust themselves and provide care despite the system, it will be important to shift recruiting and education practices to individuals who recognize their own limits and who are comfortable with trusting the system. In moving from episodic care to patient- and population-based care, a simultaneous shift away from expert-based, mediated use of evidence to the systematic use of clinical evidence is necessary, Stead noted. He concluded by emphasizing that successful system reform will require changes in provider roles, education, decision making, financial structures, and the measurement of success on the part of every stakeholder.

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
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Diagnostic and Treatment Technologies

The significant increase in the availability of novel diagnostic and treatment technologies has generated sustained and dramatic increases in the costs of health care. Despite the potential of new technologies to improve the quality of care and outcomes, the limited systematic integration of healthcare technologies—including IT, laboratory/radiology/imaging systems, and monitoring equipment—has led to their misuse and overuse. Using computer-aided tomography in cardiology as an example, Rita F. Redberg, director of Women’s Cardiovascular Services at the University of California, San Francisco, described how the current approach to technology has resulted in use that often exceeds patient benefit. Increased collection and application of systematic data can lead to more informed decision making in the application of diagnostic and treatment technologies, Redberg suggested, and should be incorporated into practice guidelines and reimbursement policies. Additionally, a more frequent and consistent approach to reviewing evidence on the clinical benefits of new technologies might make it less likely that new practices are adopted before sufficient evidence for their effectiveness has been accumulated. Engineering integrated data collection and review into the core practices of medicine could aid in the establishment of such an approach.

Clinical Data Systems and Clinical Decision Support

In order to transform the current healthcare system into a learning healthcare system, the culture, processes, approaches to technology and the healthcare environment will all have to be transformed, said Michael D. Chase, associate medical director of quality at the Kaiser Permanente Colorado Medical Group. In particular, he noted that the U.S. healthcare system has not leveraged the available clinical data to the fullest extent possible. Data are often located in a variety of applications, cul-de-sac databases, and paper forms, which inherently limits their use. Furthermore, a lack of standardization of data models inhibits the ability of patients, clinicians, organizations, and the healthcare system to address opportunities to improve care and outcomes.

Chase described how changes could take advantage of data and health IT to develop a system of clinical decision support that is more patient-centric, takes into account process redesign, and has a team approach. He went on to describe examples of care services within Kaiser Permanente Colorado that are enabled by IT, focus on activities that improve patient outcomes, lower costs, and employ a collaborative care-giving approach. He stressed the need to take on all of the interrelated components of the

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×

healthcare system in order to achieve this level of progress on a system-wide scale.

Care Coordination and Linkage

The U.S. healthcare system has become more complex on every dimension: patient diagnosis, treatment and follow-up. Patient care is now so fragmented, disorganized, and disconnected that safety and quality depends on the ability of patients and providers to communicate and work together more effectively, said Amy L. Deutschendorf, senior director for clinical resource management at Johns Hopkins Hospital and Health System and principal of Clinical Resource Consultants, LLC. She suggested that efforts to reduce redundancies and decrease costs have challenged a healthcare system that is already marked by increased complexities, including an aging and chronically ill population, decreased lengths of stay, acute care capacity issues, convoluted payer structures and incentives, and higher consumer expectations.

To address these problems, Deutschendorf called for effective care-delivery models and new communication systems to provide the accurate, timely transfer of patient information throughout the healthcare continuum. The model she advocated focuses on the patient, fully engages all members of the healthcare team, emphasizes prevention and active care planning, and is fully integrated with the provider infrastructure. In this system, health care would go from “silo” to “systems” thinking, with stronger communication among all stakeholders, increased care based on evidence, and new approaches to staff deployment and role definitions. Additional components of this redefined system would include increased monitoring and surveillance, patient-focused care, thoughtful technology, and expedited care delivery. In closing, Deutschendorf stated that in order to achieve these major systematic changes in patient care delivery, certain healthcare “sacred cows” must be addressed—e.g., control authorities, financial rewards—and, that systems engineering principles would aid in this challenge

Administrative Business Systems

The care and administrative processes in American hospitals are still the most complex institutions in American health care, according to Ralph W. Muller, CEO of the University of Pennsylvania Health System (UPHS). These processes need to be significantly changed in order to achieve the performance improvements required of a learning healthcare system. Muller described UPHS transformation initiatives related to access to services, management and coordination of inpatient care, billing practices, data management and reporting, alignment of incentives, and change manage-

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×

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 identification of goals and improvement in performance. Muller discussed UPHS’s approaches to engaging physicians, management, and staff in systems improvement 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 Development

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 Dartmouth Institute for Health Policy and Clinical Practice at Dartmouth Medical 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 information 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-

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×

gested by the aviation industry’s experience. Nance summarized elements of aviation’s use of engineering principles, including critical feedback systems 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 culturally. The wide scope and variety of engineering experiences adopted in aviation 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 president and controller (retired) of Alcoa, Inc., and now the vice chair of Martha 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.

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×

Veterans Health Affairs

The veterans healthcare system, managed by the Veterans Health Administration in the U.S. Department of Veterans Affairs (VA), is the largest 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 individual 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 interrelated and overlapping strategic goals: (1) create an accountable management 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 Veterans 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 veterans 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 Corporation 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 collaboration. Strategies were derived for each challenge and implemented

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×

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 learning 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 improvement 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 military, 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 suppliers, 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 leadership by managing their systems of work in markedly different ways.

Steven J. Spear, senior lecturer at the Massachusetts Institute of Technology 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, efficiency, 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 Development, Access, and Use

In addition to requiring education and research agendas, knowledge management for clinical decision support (CDS) also requires a policy

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×

framework. Donald E. Detmer, then president and CEO of the American Medical Informatics Association (AMIA) and professor of medical education at the University of Virginia, asserted that we do not have the appropriate 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 accelerating development and employment through federal programs and collaborations.

Technology Management

For health care, technology management is a growing issue that continues to require significant attention. Because a large portion of the recent growth in healthcare expenditures is a direct outcome of technology development, 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 management. 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 strategies, 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.

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×

Information Systems Organization and Management

Simulation can help accelerate progress. Over the past decade, numerous healthcare delivery organizations have implemented clinical information 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 evaluating 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 management. 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 contrast, 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 promote best practices; greater emphasis on collaboration; better integration of

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
×

systems; adoption of processes that lead to use and evaluation; and adoption 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 allow 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 integration into the care process. Use of data from health IT systems to model and optimize care processes was discussed as a natural application of systems 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 development 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. Contributing 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.

Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
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Several of the themes mentioned previously were raised again and expanded upon during the question-and-answer session with the panelists. Cortese, for example, shared his experiences with the achievement of interoperable systems for radiology, pointing out that it was driven by demands 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 panelists’ 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 outcomes, 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 collaboration 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 support 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 improvement 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.
Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
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  1. Identify best practices: Three areas of systems orientation are particularly 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.
  2. 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 available, 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.
  3. Advance the science of payment for value: 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 incentives for value in health care.
  4. Explore fostering the development 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 measure waste, and how to mobilize responses to eliminating waste could contribute to increasing value within healthcare systems.
  5. Support the development of a robust health IT system: The development 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, including 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.
Suggested Citation:"Summary." Institute of Medicine and National Academy of Engineering. 2011. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/12213.
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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 Evidence-Based Medicine charter and vision statement. Washington, DC: The National Academies Press.

NAE (National Academy of Engineering)/IOM. 2005. Building a better delivery 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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Improving our nation's healthcare system is a challenge which, because of its scale and complexity, requires a creative approach and input from many different fields of expertise. Lessons from engineering have the potential to improve both the efficiency and quality of healthcare delivery. The fundamental notion of a high-performing healthcare system--one that increasingly is more effective, more efficient, safer, and higher quality--is rooted in continuous improvement principles that medicine shares with engineering. As part of its Learning Health System series of workshops, the Institute of Medicine's Roundtable on Value and Science-Driven Health Care and the National Academy of Engineering, hosted a workshop on lessons from systems and operations engineering that could be applied to health care.

Building on previous work done in this area the workshop convened leading engineering practitioners, health professionals, and scholars to explore how the field might learn from and apply systems engineering principles in the design of a learning healthcare system. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary focuses on current major healthcare system challenges and what the field of engineering has to offer in the redesign of the system toward a learning healthcare system.

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