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54 ISE Magazine | www.iise.org/ISEmagazine research Do simple healthcare staffing guidelines help or hurt? As economic pressures in healthcare heighten, hospitals have increased focus on efficiency and eliminating waste. Labor comprises two-thirds of total hospital costs, making optimal staffing a key to operational and finan- cial success. Matching staffing supply to healthcare demand under high variation and un- certainty is not easy. There is little room for error in understaffing, as this could compromise patient safety and create bottlenecks in patient throughput. Fur- ther, inadequate staffing hampers clini- cian job satisfaction and increases burn- out. This increases staff turnover, which carries a high monetary burden through the costs of hiring and training. The guidelines for staffing recom- mended by the Association of peri- Operative Registered Nurses (AORN) are outlined as nurse-to-patient ratios (NPR). While simple to articulate, these ratios are difficult to implement given variability in patient flow and changes in patient acuity and care needs. Even when the ratios consider patient acuity, they can systematically lead to under- staffing for preparation and recovery (PREP/PACU) in perioperative care at certain time-points each day. In "Evaluating nurse staffing levels in perianesthesia care units using discrete event simulation," Sauleh Siddiqui, as- sistant professor in the Departments of Civil Engineering and Applied Math- ematics at Johns Hopkins University, Elizabeth Morse, assistant director of perioperative services at Johns Hopkins Hospital, and Scott Levin, associate pro- fessor in the Department of Emergency Medicine at Johns Hopkins University, used a queuing model coupled with discrete-event simulation to quantify the inefficiencies from using ratios to guide staffing in the PREP/PACU. The authors found that because of the dynamic and uncertain nature of patient flow, using simplistic ratios can lead to understaffing by as much as 20 percent, especially in the afternoon. The authors thus propose an alternative but simple method to provide better staffing esti- mates for PREP/PACU units. PREP/PACU staffing, as part of a larger system, has impacts across the entire hospital. Inadequate PREP staff- ing can lead to delays getting patients into the operating room, while lack of PACU nurse capacity can lead to pa- tients' holding in the operating room. Both these situations tie up operating room resources and create delays down- stream. These delays are not merely an inconvenience – they have significant economic effects through additional man-hours and loss-of-use of operat- ing room facilities. At Johns Hopkins, the authors estimate the cost of a patient holding in the operating room at $30 a minute. While crude increases in nurse staff- ing would improve NPR during peri- ods of peak need, large periods of over- staffing would result in unsustainable inefficiencies and financial waste. This necessitates novel approaches to improv- ing the matching of staffing supply to demand while maintaining safe, high- quality care. This manuscript represents one such effort and is an important step forward using advanced modeling tech- niques to better approximate variability in demand and optimize nurse staffing in PREP/PACU care areas. CONTACT: Sauleh Siddiqui: siddiqui@jhu.edu; (410) 516-6411; 3400 N. Charles St., Baltimore, MD 21218 Dr. Mark Romig researches systems engineering solutions to optimize healthcare delivery at Johns Hopkins University School of Medicine. In the following write-ups, medical professionals examine the impact of two papers from Volume 7, No. 4 of IISE Transactions on Healthcare Systems Engineering. Dr. Mark Romig of Johns Hopkins University School of Medicine discusses the first paper, which investigated coupling discrete event simulation with a queuing model to project nurse staffing levels for Johns Hopkins, all while considering the assignments of nurses to the patients. Dr. Michael J. Beck of Penn State Children's Hospital summarizes the second paper, where the authors developed a data envelopment analysis-based benchmark tool to evaluate the technical and scale efficiencies for emergency departments. Their solution has the potential to help the hospital management team make better decisions on critical resource allocations to improve performance.