The Lack of Systematic Month-to-Month Variation Over One-Year Periods in Ambulatory Surgery Caseload —Application to Anesthesia Staffing

Abstract

Anesthesia groups forecast future workload so that staffing and future hiring can be adjusted. Statistical methods have been developed to estimate the number of anesthesia providers needed to minimize labor costs during regularly scheduled hours, second-shifts, and weekends. These methods are simple, in that they assume that, on this medium-range (11-mo) basis, workload varies irregularly around a mean workload. To test whether this assumption is likely to hold for many anesthesia groups nationwide, raw data from the 1994 to 1996 National Survey of Ambulatory Surgery were reanalyzed. To assure that month-to-month systematic variation in workload (e.g., seasonal variation) could be detected if it were present, the average number of myringotomy tubes inserted each day in ambulatory surgery centers of the United States was also examined. The average number of ambulatory surgery cases performed with an anesthesia provider each day in the United States per 10,000 population was found to have not varied systematically month to month on a medium-range (11-mo) basis. In contrast, the average number of tubes inserted each day varied systematically among months for all 26 of the overlapping 11-mo periods in the 36 mo of the survey. These findings suggest that the relatively simple statistical methods that are available to estimate future anesthesia workload will work for many anesthesia groups.

Predicting Case Volume from the Accumulating Elective Operating Room Schedule Facilitates Staffing Improvements

“…4,5 In the long run, if the distribution of OR labor costs and surgical demand (both in terms of case volume and procedure type) replicates the historical distributions used to develop the initial staffing parameters, OR efficiency will be maximized. Both the monthly aggregated surgical volume 6 and the individual surgical subspecialty's 4-week volume 7 can be fairly accurately predicted using statistical methods, and these can be used for planning monthly staffing. However, variability in surgical case volume in the short term (weekly and daily time scales) provides an additional opportunity to extract further improvements in matching OR costs to revenue opportunities.…”

Monitoring changes in individual surgeon’s workloads using anesthesia data

“…16 If workloads of all pediatric otolaryngologists varied seasonally (e.g., because young children develop more ear infections during the winter months), 16 a change in the caseload of one surgeon would predict changes in the caseloads of the other pediatric otolaryngologists. Nevertheless, prior analyses from two hospitals suggested that the preceding example 16 using national data does not apply to individual hospitals.…”

“…16 If workloads of all pediatric otolaryngologists varied seasonally (e.g., because young children develop more ear infections during the winter months), 16 a change in the caseload of one surgeon would predict changes in the caseloads of the other pediatric otolaryngologists. Nevertheless, prior analyses from two hospitals suggested that the preceding example 16 using national data does not apply to individual hospitals. 1,10 Hypothesis #2 During relevant (one year) time periods, caseloads of surgeons are uncorrelated or correlated so weakly as to be managerially irrelevant for predicting the caseload of an individual surgeon.…”

Lack of Value of Scheduling Processes to Move Cases from a Heavily Used Main Campus to Other Facilities Within a Health Care System

“…21 However, all the references, cited above, limited consideration to individual facilities (i.e., each facility independently planned staffing and performed case scheduling). Findings may not apply to health systems with the potential to move cases among the various affiliated hospitals.…”