Biomedical subjects

Rodney D Traub

Publications and source records attributed to Rodney D Traub.

5 recordsLinked to original sources

PubMed2003

How to release allocated operating room time to increase efficiency: predicting which surgical service will have the most underutilized operating room time.

At many facilities, surgeons and patients choose the day of surgery, cases are not turned away, and staffing is adjusted to maximize operating room (OR) efficiency. If a surgical service has already filled its allocated OR time, but has an additional case to schedule, then OR efficiency is increased by scheduling the new case into the OR time of a different service with much underutilized OR time. The latter service is said to be "releasing" its allocated OR time. In this study, we analyzed 3 years of scheduling data from a medium-sized and a large surgical suite. Theoretically, the service that should have its OR time released is the service expected to have the most underutilized OR time on the day of surgery (i.e., any future cases that may be scheduled into that service's time also need to be factored in). However, we show that OR efficiency is only slightly less when the service whose time is released is the service that has the most allocated but unscheduled (i.e., unfilled) OR time at the moment the new case is scheduled. In contrast, compromising by releasing the OR time of a service other than the one with the most allocated but unscheduled OR time markedly reduces OR efficiency. OR managers can use these results when releasing allocated OR time.

Appointments and Schedules↗

PubMed2003

Operating room utilization alone is not an accurate metric for the allocation of operating room block time to individual surgeons with low caseloads.

INTRODUCTION: Many surgical suites allocate operating room (OR) block time to individual surgeons. If block time is allocated to services/groups and yet the same surgeon invariably operates on the same weekday, for all practical purposes block time is being allocated to individual surgeons. Organizational conflict occurs when a surgeon with a relatively low OR utilization has his or her allocated block time reduced. The authors studied potential limitations affecting whether a facility can accurately estimate the average block time utilizations of individual surgeons performing low volumes of cases. METHODS: Discrete-event computer simulation. RESULTS: Neither 3 months nor 1 yr of historical data were enough to be able to identify surgeons who had persistently low average OR utilizations. For example, with 3 months of data, the widths of the 95% CIs for average OR utilization exceeded 10% for surgeons who had average raw utilizations of 83% or less. If during a 3-month period a surgeon's measured adjusted utilization is 65%, there is a 95% chance that the surgeon's average adjusted utilization is as low as 38% or as high as 83%. If two surgeons have measured adjusted utilizations of 65% and 80%, respectively, there is a 16% chance that they have the same average adjusted utilization. Average OR utilization can be estimated more precisely for surgeons performing more cases each week. CONCLUSIONS: Average OR utilization probably cannot be estimated precisely for low-volume surgeons based on 3 months or 1 yr of historical OR utilization data. The authors recommend that at surgical suites trying to allocate OR time to individual low-volume surgeons, OR allocations be based on criteria other than only OR utilization (e.g., based on OR efficiency).

Computer Simulation↗

PubMed2002

Statistical power analysis to estimate how many months of data are required to identify PACU staffing to minimize delays in admission from ORs.

When each nurse in the Phase I setting is caring for the maximum number of patients allowed by hospital staffing standards (typically 2 per ASPAN standards), patients may have to be held in the OR until a PACU nurse becomes available. Previously, the authors described a statistical method to determine the process of scheduling existing nurses without increasing staffing hours (Dexter et al. Anesth Analg. 92:947-949, 2001). The end result was to minimize the percentage of future workdays during which at least one patient would wait in his or her OR for Phase I PACU admission. In this study, the authors performed a statistical power analysis to determine how many months of PACU workload data are needed to optimize PACU staffing by using this "set covering" algorithm. One year (232 workdays) of data was available from a PACU employing up to 10 nurses working a total of 72 clinical hours a day. The data were divided into 2 subsets. Using the first subset, which varied in size between 20 and 140 days of data, the authors identified the optimal staffing solutions. These solutions were tested on the second subset of data. This process then was repeated thousands of times. There was a marked improvement in the performance of the staffing solutions at preventing "PACU hold" by increasing from 20 to 80 historical workdays of data, a slight but statistically significant improvement between 80 and 100 workdays, but no significant improvement in further increasing the number of workdays of data. PACU nurse managers should use at least 4 months of data when choosing a staffing solution to minimize the chance of patients waiting in ORs for PACU admission. Tampering with PACU staffing more often than every 4 months is unlikely to result in improvements in OR efficiency and may harm recruitment and retention of nursing staff.

Operating Rooms↗

PubMed2002

How to schedule elective surgical cases into specific operating rooms to maximize the efficiency of use of operating room time.

UNLABELLED: We considered elective case scheduling at hospitals and surgical centers at which surgeons and patients choose the day of surgery, cases are not turned away, and anesthesia and nursing staffing are adjusted to maximize the efficiency of use of operating room (OR) time. We investigated scheduling a new case into an OR by using two patient-scheduling rules: Earliest Start Time or Latest Start Time. By using several scenarios, we showed that the use of Earliest Start Time is rational economically at such facilities. Specifically, it maximizes OR efficiency when a service has nearly filled its regularly scheduled hours of OR time. However, Latest Start Time will perform better at balancing workload among services' OR time. We then used historical case duration data from two facilities in computer simulations to investigate the effect of errors in predicting case durations on the performance of these two heuristics. The achievable incremental reduction in overtime by having perfect information on case duration versus using historical case durations was only a few minutes per OR. The differences between Earliest Start Time and Latest Start Time were also only a few minutes per OR. We conclude that for facilities at which the goals are, in order of importance, safety, patient and surgeon access to OR time, and then efficiency, few restrictions need to be placed on patient scheduling to achieve an efficient use of OR time. IMPLICATIONS: We showed how elective cases should be scheduled to maximize the efficiency of use of operating room time. The analysis applies to surgical suites at which surgeons and patients have access to operating room time every workday.

Ambulatory Surgical Procedures↗

PubMed2002

What sample sizes are required for pooling surgical case durations among facilities to decrease the incidence of procedures with little historical data?

BACKGROUND: Better predictions of each case's duration would reduce operating room labor costs and patient waiting times. A barrier to using historical case duration data to predict the duration of future cases is the absence for some cases of previous data for the same scheduled procedure from the same facility. The authors examined sample size requirements for pooling case duration data from several facilities to create a 90% chance of having case duration data for almost all procedures. METHODS: Four academic medical centers provided data, totaling 200,401 cases classified by the scheduled Current Procedural Terminology codes. RESULTS: The 12% of cases in which procedures occurred once or twice accounted for 79% of procedures or combinations of procedures. When a procedure was being performed for the first time at a facility, that same procedure had been performed previously at least once at one or more of the other three facilities only 13-25% of the time. More than 1 million cases would be needed to have a 90% chance of having at least 3 cases for each procedure observed in the original 200,401 cases. However, with N = 200,401 cases in our initial data set, we observed less than one third of the estimated total number of possible procedures. CONCLUSIONS: The lack of historical case duration data for scheduled procedures is an important cause of inaccuracy in predicting case durations. However, millions of cases probably would be required to provide historical case duration data for almost all procedures.

Academic Medical Centers↗