How Systems Engineering Can Improve Health Care
November 29, 2018
Systems engineering is the study of complex systems and involves the use of data, mathematical modeling, and computational methods to optimize these systems. Some of these tools include queuing models, regressions, and discrete event simulations. Systems science is not only a set of methods but also a way of thinking that proactively requires engineers to define the problem, understand its constraints, and consider the desired outcome. Health systems engineering, in particular, is a new area of health care delivery that examines system and process design in order to increase efficiency, reduce errors, and improve access and overall quality of health care. Systems engineering methods have allowed rapid growth in the manufacturing, logistics, distribution, and transportation sectors by increasing quality, efficiency, and safety, but have yet to be fully integrated into health care. Although the health care sector has some unique differences compared to other economic industries, there remain some common functions that could greatly benefit from the use of systems analysis, such as scheduling, resource allocation, and economic analysis.
Researchers are now beginning to apply systems techniques to medical decision-making and hospital processes. At the Mayo Clinic Health Care Systems Engineering Program, health care engineers are working to make blood transfusions more effective and safe by using models to predict adverse reactions prior to transfusion and developing algorithms for optimizing patient-specific triggers. Researchers at the Johns Hopkins University Center for Systems Engineering in Health have developed methods for “smart” scheduling of patients and clinicians by using optimization techniques that match demand for care to supply. Other engineers are also working with health care professionals to optimize liver transplants by using Markov decision processes and improve perioperative decision-making through combinatorial optimization modeling. Through these systems analysis techniques, inefficiencies can be minimized, allowing for better quality and lower costs.
Not only can systems engineering be applied to improve health care processes, but it can also be directly applied to health care policymaking. Evidence-based policy is gaining nationwide attention, but the use of specific systems engineering methods have not been widely accepted yet. Johns Hopkins University has a project area dedicated to health policy that has worked to create a decision support tool for prioritizing development of new vaccines. Researchers at the University of Pennsylvania are using tools such as agent-based modeling to determine interventions that can increase community mental health. Even in environments that are outside of academic research, engineering tools for health policy are starting to be utilized. For example, health care consultants at McKinsey are using a micro-simulation model to project health insurance coverage. Using mathematical models and data can greatly increase the effectiveness of policy interventions and better the health system as a whole.
Despite the potential of systems engineering within health care, there are several barriers that make it difficult for these methods to be integrated within the larger system. One of the biggest challenges is the fact that our current reimbursement practices provide little incentive for investing in quality and systems improvement. The predominant fee-for-service payment model fails to encourage efficiency, but to support the use of systems analysis, the U.S. needs to move to a more value-based model. But these models rely on metrics to identify high-value care, meaning that reliable quality measures and data will be needed. Another difficulty is that the current health care system is fragmented and has a culture of a rigid division of labor. Medical care is separated in an uncoordinated fashion across different specialties and settings, where health care providers are only focused on their particular task instead of working together to consider the holistic needs of the patient. This type of compartmentalization does not support the optimal application of systems engineering tools, which can span across different areas of care. Moving away from this siloed system would require a broad knowledge of the different processes involved in each patient’s care as well as a paradigm shift to a more collaborative-based work.
Although there are significant barriers to the full integration of systems engineering within health care, it remains an exceptional field with a great potential for bettering the health system of the U.S.
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