title: 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.
authors.affiliation: Department of Anesthesia, University of Iowa, Iowa City, Iowa, USA. franklin-dexter@uiowa.edu
authors.forename: F
authors.initials: F
authors.lastname: Dexter
authors.forename: R D
authors.initials: RD
authors.lastname: Traub
mesh_terms: D000556:Ambulatory Surgical Procedures / Q000706:statistics & numerical data*; D000761:Anesthesia Department, Hospital; D003625:Data Collection; D009309:National Center for Health Statistics, U.S.; D010561:Personnel Staffing and Scheduling; D012621:Seasons; D014481:United States; D000078329:Workforce