Engineering a Learning Healthcare System A Look at the Future: Workshop Summary (2011) / Chapter Skim
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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.
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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.
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• 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.
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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)
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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.
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• Complexity compels reasoned allowance for tailored adjustments. • Learning is a non-linear process.
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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.
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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
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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.
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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
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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.
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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.
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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.
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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
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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 Administratie 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)
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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 feedforward, 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.
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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.
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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.
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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.
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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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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.
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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.
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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.
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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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2007. The learning healthcare system.
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