Health Care Systems Engineering Program

Health care systems engineering is an area of research in health care delivery science that provides a mechanism to design or redesign the systems and processes of how care is delivered to increase efficiency, reduce errors, and improve access and overall quality of care.

The Health Care Systems Engineering Program brings together expertise, both from data-driven and mathematical sciences as well as human-based sciences, to provide integrated solutions to today's complex health care problems.

The data-driven and mathematical sciences include operations research, informatics, management and computational sciences that focus on quantitative evaluation and modeling of processes and systems of care to promote optimal care delivery and data-driven decision-making. The fields of human factors, ergonomics and organization sciences are dedicated to identifying and correcting incompatibilities among people, technology and work environments. They focus on improving technologies and systems so that they work optimally within the capabilities and limitations of humans, both physically and psychologically.

The mission of the Health Care Systems Engineering Program is to advance science through scholarship and innovation, and make significant impacts in practice through implementation, while educating future researchers and practitioners.

The program is accomplishing this by:

  • Identifying practice stakeholders within Mayo Clinic and beyond and establishing long-term research engagements
  • Leveraging scientific knowledge to transform health care delivery
  • Advancing knowledge in systems engineering and understanding of health care systems through scholarship and innovation
  • Disseminating knowledge to the health care and systems engineering community
  • Educating health care practitioners in systems engineering and engineering students in health care

For patients, this is leading to health care that is more patient-centered, as well as improvements in safety, access to care, efficiency and satisfaction. Importantly, health care providers likewise benefit from safer, more efficient health care delivery.

Areas of focus

  • Understanding risk factors and indicators of deterioration in hospitalized patients, and developing and implementing tools to improve care processes
  • Increasing the utilization and improving capacity management of surgical processes
  • Understanding work flow and teamwork in surgical suites and establishing work environments that enable providers to feel motivated and satisfied with their performance
  • Examining the workload in the surgical suite, and proposing and testing interventions to optimize task performance and staff well-being
  • Understanding the usability of medical equipment and its socio-technical impact
  • Embedding research in practice through clinical engineering labs to ensure research has relevance and practice changes are informed based on scientific rigor
  • Improving our understanding of patient demand and outpatient access and developing decision-support systems


Major findings and implementations by the program include:

  • Forecasting models for internal-referral specialty appointments at Mayo that have improved access times and reduced unfilled appointment slots
  • Prediction models and heuristics to increase the efficiency of surgical schedules
  • Increases in safety in the operating room for patients and surgical staff
  • A better understanding of the interactions among workload, work flow and team dynamics


Jeanne M. Huddleston, M.D.

Susan Hallbeck, Ph.D.

Kalyan S. Pasupathy, Ph.D.


Jeanne M. Huddleston, M.D.

  • Director
  • Health Care Systems Engineering Program

Jeanne M. Huddleston, M.D.: Hi, I'm Jeanne Huddleston. I work in the Health Care Systems Engineering Program in the Center for the Science of Healthcare Delivery. I think one of the best benefits for using engineering in healthcare could be very aptly described by one of my mentors at Arizona State. He told me that health care now reminds him of what industry was like in the '70s in the United States. Projects were late, everything came in over budget, nothing was done efficiently, lots of errors and lots of safety problems. That pretty much describes part of how health care is being delivered in the United States now. So I believe that we can translate those principals that were used to improve manufacturing and make us competitive again in the '70s and the '80s, apply those to health care, we ought to be able to get some of the benefits that we received decades ago, only improve the health of our population.

There's a couple of examples of systems engineering that's been applied even before we called it systems engineering in health care. One is our unified medical records. So, Henry Plummer was the first internist at Mayo Clinic. He also happened to be an engineer and an architect. So he actually engineered our medical record that we still use today that allows us to combine our outpatient record, our hospital record, our nursing home records, and everything from the time that you're born until you die here. So it's one of the only places in the world where you can actually have everything all at one time when you're taking care of somebody, which as a provider and a patient, being both here, is phenomenal.

Another example is one that probably people don't think about very much, but it's actually the whole development of anesthesia and anesthesiology here in the hospitals. It is the only specialty and the only profession in the hospital that is actually functioning at a reliability level that we would be proud of in manufacturing. Very few errors, very few problems, because as they developed their field, they watched for errors and they engineered equipment, and policies, and they used checklists like our airline industry does to make sure everything would go as smoothly as possible during a relatively dangerous period of time for patients. We're putting them to sleep, we're doing surgeries, and so they have perfected that at a level in health care that we haven't been able to do anywhere else. And it's all the engineering principles that have been applied along the way.

So there's a few examples of what we've been doing recently. One that I'm incredibly passionate about, because it has come out of the mortality work that I've been doing in the hospitals for the last eight years, is called bedside patient rescue. Our number one preventable cause of death here in Rochester is a clinician's inability to recognize when a patient's become sick, when their care or their condition has, all of a sudden, gone a different direction than we thought it was going. So that change in course is difficult for providers, physicians, nurses alike, to recognize when that change happens. A delay in that recognition can have serious consequences for patients.

Dr. Huddleston: So we're actually doing a full systems engineering approach to this from doing a failure modes effect analysis, literally going in and talking to every discipline from nurses, respiratory therapists, physicians, surgeons, residents, students, engineering students, patients, etc., to find out how this actually works from everyone's perspective. All the people who are involved. And then where are we missing from each of their perspectives. We're doing really sophisticated analytics in terms of trying to understand what the actual physiology, what conditions are happening to the patients so that we can recognize it in our electronics to tell the providers when something's changing, but that has to be done at a way so there aren't false alarms. Because if I tell you the patient is deteriorating and you go and they're not, then that hasn't been good for anybody involved. So we have to figure out how to do that better than we currently do, and then bring all of that together with our electrical engineers and our mechanical engineers to actually design equipment that will make this change in condition to patients obvious to everybody and make the recovery obvious to everybody from a visual perspective and a intellectual perspective. So it's a project that's going to take a little bit of time to pull all of this together, but ultimately we'll save lives, and our guess is that we'll save at least 50 lives a year just in Rochester by doing the math that the engineers can do and understanding the cognitive and the workflow pieces that are involved in, too.