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Release: May 25, 2001

UI researcher uses statistical analysis to improve staff scheduling for operating rooms

IOWA CITY, Iowa -- A nationwide decline in the number of people training to become anesthesiologists, operating room nurses, surgical technicians, and nurse anesthetists has made it more difficult for hospitals to hire operating-room staff. At the same time, hospitals are also facing reduced reimbursement, compared to costs, for perioperative services. These two problems pose serious challenges for hospitals providing perioperative care.

According to UI Health Care researcher, Franklin Dexter, M.D., Ph.D., UI associate professor of anesthesia and director of the department's division of management consulting, both problems can be addressed by increasing productivity in the operating room.

"It is important to minimize downtime by scheduling staff hours to coincide with when there are patients to treat," Dexter said. "But you also want to minimize the number of hours staff have to work when they weren't scheduled to be there, which results in higher costs."

Dexter explained that in the latter situation, the costs are both direct, in the form of overtime payments, and indirect, in the form of frustration on the part of staff and surgeons at having to work late in the day, which can result in difficulties with recruitment and retention. Likewise, patients have longer waiting times on the day of surgery.

Over the past few years, Dexter and his colleagues have developed a number of computer algorithms for finding solutions to these kinds of staffing problems. The computer program can generate and evaluate millions of possible solutions relatively quickly.

A request from a large health care system to generate optimal operating room staffing solutions for nine different, independent surgical suites, provided the researchers with an opportunity to test the statistical analysis methods. The suites included trauma centers, community-based hospitals doing mostly elective surgery with some urgent cases, and ambulatory surgery centers. The suites ranged in size from two to 17 operating rooms.

Dexter and his colleagues assessed weekday staffing at the nine surgical suites using two years' worth of operating room data on case duration and staffing levels. The results of the study appear in the June issue of the journal Anesthesia and Analgesia.

"We knew that the computer algorithms would generate the optimal solution for maximizing productivity," Dexter said. "But our question was whether they would perform significantly better than the solutions arrived at by the operating-room managers based on their experience."

In fact, the software package generated staffing schedules that increased productivity and decreased costs compared to those used by the managers in eight of the nine suites by an overall average of 19 percent. Only the smallest suite, with two operating rooms, was being staffed as efficiently as possible.

"We had hypothesized that for that surgical suite the human solution would likely be as good as any solution derived from our program because the situation was not very complicated," Dexter said. "There was no benefit to having a sophisticated mathematical way of obtaining a staffing plan for such a small surgical suite."

However, for each of the other eight surgical suites, the statistical methods identified staffing solutions with significantly lower costs than those currently being used, and for seven of the nine suites, the cost of the plan identified by the statistical method was at least 10 percent lower.

The study highlights the fact that even for suites with relatively few operating rooms, finding the optimal staffing solution is a complicated task. The computer software can assist operating room managers because it can generate and evaluate literally millions of potential solutions to find the best one, many more than a manager could do by hand.

Although the statistical methods produce the most efficient staffing solutions, Dexter suggested that even if surgical suites don't use the program to generate mathematically optimal solutions, the study still provides useful insights about new strategies managers could use to increase productivity.

Most importantly, managers tended to use the same staffing schedule for every day of the week. The software, however, showed that significant increases in productivity could be achieved by varying staffing hours among the days of the week.

Managers also had a tendency to use overlapping 8,10 and 13-hour shifts in an attempt to increase productivity. In fact, Dexter's study suggested that not only did this approach not improve productivity levels, it actually resulted in longer delays for surgeons and patients on the day of surgery.

"A consequence of everyone working 8 hour shifts is that you run more operating rooms and have more first-case-of-the-day starts," Dexter explained. "Surgeons and patients prefer a first case of the day because they know exactly when that case will start. With later cases you don't necessarily know that they will start at the scheduled time."

Dexter suggests that the empirical results could be useful to managers and hospitals in designing staffing solutions for operating rooms and deciding how many operating rooms a facility should run.

The software package used in this study, CalculatOR, was developed by Medical Data Applications, Ltd., of Jenkintown, Penn. Richard H. Epstein, M.D., associate professor of anesthesiology at Jefferson Medical College and president of Medical Data Applications, Ltd., and H. Michael Marsh, M.B.B.S., professor and chair of anesthesiology at Wayne State University were co-authors of the study.

This work was performed as part of a consultation by the Division of Management Consulting in the UI Department of Anesthesia.

For more information about consultations or about the CalculatOR software, contact Franklin Dexter at

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