Operating room management and operating room productivity: the case of Germany.
ABSTRACT We examine operating room productivity on the example of hospitals in Germany with independent anesthesiology departments. Linked to anesthesiology group literature, we use the ln(Total Surgical Time/Total Anesthesiologists Salary) as a proxy for operating room productivity. We test the association between operating room productivity and different structural, organizational and management characteristics based on survey data from 87 hospitals. Our empirical analysis links improved operating room productivity to greater operating room capacity, appropriate scheduling behavior and management methods to realign interests. From this analysis, the enforcing jurisdiction and avoiding advance over-scheduling appear to be the implementable tools for improving operating room productivity.
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ABSTRACT: Productivity measurements based on "per operating room (OR) site" and "per case" are not influenced by staffing ratios and have permitted meaningful comparisons among small samples of both academic and private-practice anesthesiology groups. These comparisons have suggested that a larger sample would allow for clinical groups to be compared using a number of different variables (including type of hospital, number of OR sites, type of surgical staff, or other organizational characteristics), which may permit more focused benchmarking. In this study, we used such grouping variables to compare clinical productivity in a broad survey of academic anesthesiology programs. Descriptive, billing, and staffing data were collected for 1 fiscal or calendar year from 37 academic anesthesiology departments representing 58 hospitals. Descriptive data included types of surgical staff (e.g., academic versus private practice) and hospital centers (e.g., academic medical centers and ambulatory surgical centers [ASCs]). Billing and staffing data included total number of cases performed, total American Society of Anesthesiologists units (tASA) billed, total time units billed (15-min units), and daily number of anesthetizing sites staffed (OR sites). Measurements of total productivity (tASA/OR site), billed hours per OR site per day (h/OR/d), surgical duration (h/case), hourly billing productivity (tASA/h), and base units/case were compared. These comparisons were made according to type of hospital, number of OR sites, and type of surgical staff. The ASCs had significantly less tASA/OR site, fewer h/OR/d, and less h/case than non-ASC hospitals. Community hospitals had significantly less h/OR/d and h/case than academic medical centers and indigent hospitals and a larger percentage of private-practice or mixed surgical staff. Academic staffs had significantly less tASA/h and significantly more h/case. tASA/h correlated highly with h/case (r = -0.68). This study showed that the hospitals at which academic anesthesiology groups provide care are not all the same from a clinical productivity perspective. By grouping based on type of hospital, number of OR sites, and type of surgical staff, academic anesthesiology departments (and hospitals) can be better compared by using clinical productivity measurements based on "per OR site" and "per case" measurements (tASA/OR, billed h/OR/d, h/case, tASA/h, and base/case). IMPLICATIONS: Organizational factors, including type of hospital, number of operating rooms, and type of surgical staff, influence the clinical productivity of academic anesthesiology departments. Reporting quartile data by focused grouping variables allows anesthesiology groups to compare their clinical productivity with groups practicing in similar clinical settings.Anesthesia & Analgesia 04/2003; 96(3):802-12, table of contents. · 3.30 Impact Factor
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ABSTRACT: Surgical duration (hours per case; h/case) and type of surgery (ASA base units per case; base/case) determine the hourly clinical productivity (total ASA units per hour of anesthesia care; tASA/h) for anesthesiology groups. In previous studies, h/case negatively influenced tASA/h, but base/case did not differ significantly. However, when cases are grouped by surgical service, the mean base/case varies. In this study we evaluated the effect of h/case and base/case on tASA/h when these are grouped by surgical services. Data from one calendar year were collected from an academic anesthesiology department's billing database. All surgical cases for which the anesthesiology department provided care were included. Cases performed outside the main operating room, e.g., remote sites or obstetrics, were excluded. Any care not billed with ASA units was also excluded. Mean base/case and h/case were determined. For each service, tASA/h was calculated by dividing the sum of base/case and (4 x h/case) by h/case. A total of 12,769 cases were performed by 19 different surgical services. Mean base/case was 6.1 U, with a range of 4.0 U (orthopedics) to 16.0 U (cardiothoracic). Mean h/case was 2.9 h, with a range of 0.9 h (otolaryngology pediatric) to 5.4 h (orthopedic spine). Mean tASA/h was 6.35 U/h, with a range of 5.01 U/h (plastic surgery) to 9.71 U/h (otolaryngology pediatric). The services with high base/case did not necessarily have high tASA/h because of the longer h/case. The services with the shortest h/case had the highest tASA/h. The accurate prediction of both clinical and billing productivity requires inclusion of both base/case and surgical duration data. Anesthesiology groups should consider surgical duration when making strategic decisions.Anesthesia & Analgesia 10/2003; 97(3):833-8. · 3.30 Impact Factor
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ABSTRACT: At many surgical suites, surgeons and patients schedule elective cases on whatever future workday they choose, resulting in there being no limit on the number of cases performed each day. Staff are then scheduled in the manner that satisfies the marketing guarantee to the surgeons, satisfies labor contracts, and minimizes staffing costs. We assessed weekday nurse anesthesia group staffing at nine such suites to determine whether statistical methods can identify staffing solutions whereby all the cases are covered but for which staffing costs are less than those obtained using the staffing plans implemented by anesthesia groups' managers. Two years of operating room information system case duration and staffing data were analyzed. First- and second-shift staffing was assessed using previously published algorithms. The statistical methods identified staffing solutions with significantly decreased labor costs than those currently being used at eight of the nine surgical suites. The statistical methods relied more on overtime than second-shift staffing. The incremental decrease in staffing costs achievable by using overlapping 8-, 10-, and 13-h shifts was negligible. Overall, we found that statistical methods can identify, for some surgical suites, staffing solutions whereby all the cases are covered but for which costs are significantly less and productivity significantly more than those obtained using the plans developed by the managers based on their experience and the data. IMPLICATIONS: Statistical methods can identify, for some surgical suites, anesthesia staffing solutions whereby all the cases are covered but for which labor costs are significantly less than those obtained using the staffing plans developed by the managers based on data and their experience.Anesthesia & Analgesia 07/2001; 92(6):1493-8. · 3.30 Impact Factor