Day, T. Eugene DSc; Goldlust, Eric J. MD, PhD; True, William R. PhD, MPH
Dr. Day is health systems specialist, St. Louis Veterans Affairs Medical Center, and senior fellow, Center for Optimization and Semantic Control, Washington University, St. Louis, Missouri.
Dr. Goldlust is assistant professor, Department of Emergency Medicine, Warren Alpert Medical School, Brown University, Providence, Rhode Island.
Dr. True is director, Health Services Research and Development, St. Louis Veterans Affairs Medical Center, and research professor, George Warren Brown School of Social Work, Washington University, St. Louis, Missouri.
Correspondence should be addressed to Dr. Day, St. Louis VAMC, JC/00, 915 Grand, St. Louis, MO 63106; telephone: (314) 482-1996; e-mail: Eugene.email@example.com.
As the 21st century progresses, our health care delivery system faces major challenges. Increases in the number of patient visits and in expenditures per patient necessitate large-scale efforts to improve throughput times and cost-effectiveness, across the spectrum of medical care.1 We believe that improvements in these areas will require significant changes in practice patterns, as well as in the means by which health administrators analyze and address these issues. To this end, this transformation of health care delivery will almost certainly depend not only on physicians and health administrators but also on systems engineers. It therefore seems essential that health care practitioners and administrators learn more about the role of systems engineering and that the new generation of health care engineers be trained early in the language and domain of clinical practice.
Health Care Engineering
The field of systems engineering is uniquely qualified to model, analyze, and optimize the immensely complex interactions that occur among patients, health care providers, nursing staff, information systems, diagnostic labs and imaging, and therapeutic interventions. These are well modeled as human interactive hybrid dynamic systems (HDSs). Such systems are large and intricate, characterized by large numbers of semiindependent subsystems, dynamic and sometimes unpredictable human decision makers, and a mixture of continuous and discrete processes. Because of the convoluted dependencies between parts of the system, changes to one area of an HDS may propagate otherwise unpredictable consequences far from the source of system perturbation. As such, HDSs have become highly useful tools for modeling health care delivery in a number of settings.2,3
Currently, there remains a crevasse between the approaches of the four main stakeholders in the analysis and redesign of health care systems: the medical provider, the administrator, the engineer, and the researcher. Often, the same individual may hold more than one of these roles, but it remains rare that a trained engineer also serves as a health care provider or administrator. These roles, then, have different goals and provide different perspectives on health care delivery. The provider's desire, appropriately, is the optimal care of the patient, with the goal of yielding the best possible prognosis. Administration is chiefly concerned with convening a functional medical center conducive to medical care, convalescence, and financial sustainability. The systems engineer is responsible for systems analysis with the aim of maximizing access and throughput according to the constraints inherent in the system. Researchers in health care administration are charged with assessing care delivery processes and patient-centered outcomes, ultimately influencing and disseminating the results of evidence-based practice.
These roles and objectives are all critically important to the maintenance and improvement of health care delivery. Unfortunately, each of these roles uses idiosyncratic jargon and may have conflicting needs with regard to access, authority, and resources. Multiobjective optimization of a large-scale HDS is a developing field, tasked with determining optimal parameters for health care delivery under the constraints imposed by multiple care goals (e.g., safety and cost control). However, determining the parameterization of patient care, resource distribution, and sustainability of care is a delicate task. This is a task which, fundamentally, cannot be achieved so long as the principal stakeholders do not understand one another. As such, it is incumbent on the educational system to support the training of stakeholders with a working understanding of each others' goals and methods.
Many hospitals and medical centers have relationships with local institutions of higher education and, as such, provide training opportunities for graduate and undergraduate students in medical fields such as medicine, pharmacy, and nursing. Critically, however, the role of the teaching hospital needs to expand its basic organizational objective to include the training of health care engineers as well. The reason for this is straightforward: Although schools of health administration generally include courses on management science, a basic aspect of systems engineering, programs in systems engineering do not commonly provide training specific to health care in classroom settings.4 This is largely because the mathematical constructs which model health systems are highly analogous to those which model transportation or manufacturing systems; as such, on the surface, there seems to be no reason to provide specific exposure to the health care industry. It is notable that, despite the long and remarkable history of this industry, the relationship between the health care and systems engineering fields required for successful health systems engineering remains an underexploited potential partnership.
The advantages of cross-disciplinary training are not merely for those who intend to play a direct role in health care redesign. The multipartite relationship among engineer, administrator, researcher, and provider will likely engage all those looking to improve clinical practices, if only to learn from the growing body of literature in health care optimization. The reconciliation of these roles will undoubtedly be a slow process, but one profoundly and positively improved by embracing a common language. In particular, engineers must be able to communicate their ideas and solutions in language that is penetrable to physicians and administrators. The means of addressing the linguistic chasm lie in the educational process. Engineers must be exposed to medical optimization, health care, and public health conventions for dealing with quantitative data prior to entering the field as professionals. This can be achieved through large-scale adoption of mentored health care engineering internships at the undergraduate and graduate educational levels.
The structure of the mentored health care engineering internship is necessarily different from an administrative internship. Such an internship is best treated as a narrowly focused research project, conceived and organized by health administrators and physicians. In this way, the student engineer is required to learn and adopt the language of the medical sciences—administrative, medical, and epidemiological. However, the project must still be written and analyzed in the language of systems engineering and, as such, should be directed and evaluated in parallel by engineering faculty. A teaching hospital employing faculty who have engineering backgrounds and who are able to oversee such projects would create an optimal environment; in lieu of this, a teaching hospital affiliated with a school (or departments) of engineering would well suffice. Similarly, internships in applied epidemiology might involve internships spearheaded by medical faculty but mentored by faculty in epidemiology. The concomitant mentorship of systems engineers in epidemiology should similarly enable them to design studies and describe results in a language familiar to those in clinical medicine.
As an example of the internship methodology we espouse, during the fall and summer of 2009, St. Louis Veterans Affairs Medical Center (VAMC) engaged a systems engineering student intern in the observation and analysis of our pharmacy telephone help desk. The project was conceived by St. Louis VAMC staff and jointly overseen by one of the authors (T.E.D.), VA pharmacy staff, and the student's academic advisor at Washington University, in the Department of Electrical and Systems Engineering. The internship was performed as a partial fulfillment of the student's bachelor of science degree. The analysis, using queuing theoretic and discrete event simulation models to determine the optimal staffing requirements of the help desk, resulted in several key successes: first, a careful and rigorous understanding of the system and the means of improving system performance; second, the development of the student's understanding of both systems theory and pharmacy practice; and third, the juried publication of results.5
We find that the mentored internship model has at least three fundamental benefits. First, the medical center obtains access to a new type of systems research with the potential for real-world system improvement that has immediate impact on patient well-being. Second, the collaboration yields young systems engineers with direct experience in health care, able to address real-world problems in a language which is accessible to health care administrators, researchers, and providers. Third, by so affiliating with these medical centers, engineering schools garner access to fertile ground for research projects, for students and faculty alike. Similarly, the medical centers will be able to avail themselves of trained systems engineers as the need for such services increases.
The Future of Health Delivery Optimization
If there is any constant in the field of medicine, it is innovation. The collaboration between medical providers and engineers has been long and fruitful in the field of bioengineering. In the field of health care delivery, this relationship is new, but ramifying. Engineers do not desire to become the focus of a debate between providers, investigators, and administrators but, rather, full partners in the pursuit of the highest standard of care, balancing the needs of individual patients with the sustainability of the medical center—specifically, determining and diversifying those areas where the needs of the patient and the needs of the system are in concert rather than competition. Insightful and delicate engineering of medical systems is going to be paramount to the continuing improvement of the public health.
A drive toward undergraduate- and graduate-level mentored internships, in epidemiology as well as in hospital systems and medicine, as a basic aspect of health care engineering will result in a generation of linguistically agile systems engineers, capable of understanding and conveying problems and their solutions in a manner that is accessible and acceptable to both providers and administrators. Health care must become more efficient as an increasing and aging population begins to require more—and more expensive—treatments. We encourage engineers to take responsibility for the advancement of rigorous, more efficient health delivery models. Training them in the language of medicine now, rather than in an ad hoc manner in the future, will not only expedite that transition but also prevent costly misunderstandings and delays in the process.
Medicine, health care delivery, and public health efforts are all joining with systems engineering to find rigorous methods of improvement. The quality of engineering solutions themselves may be improved and made more implementable through more sophisticated mutual communication among the stakeholders in health systems. The mentored exposure of student engineers to the language and processes of medicine and epidemiology can only facilitate more effective collaboration, more impactful results, and better health for patients and populations.
The authors wish to thank Weiyu Max Li for participation in the referenced pharmacy project, and Dr. Heinz Schaettler, Dr. Ervin Rodin, and Dr. Hiroaki Mukai of the Department of Electrical and Systems Engineering, Washington University in St. Louis, and Dr. Nathan Ravi, chief of staff, St. Louis VAMC, for supporting mentored internships at St. Louis VAMC.
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5 Day TE, Li WM, Ingolfsson A, Ravi N. Use of queuing and simulative analyses to improve an overwhelmed pharmacy help desk. J Pharm Pract. 2010. In press.