Managing the Variability in Hospital Occupancy

Abstract

Source: Fieldston ES, Ragavan M, Jayaraman B, et al. Scheduled admissions and high occupancy at a children’s hospital. J Hosp Med. 2011; 6(2): 81– 87; doi: 10.1002/jhm.819Investigators from the University of Pennsylvania and Children’s Hospital of Philadelphia (CHOP) retrospectively reviewed admission-discharge-transfer data collected at CHOP over one year. The dataset included date and time of all arrivals and departures from all inpatient units including observation stays. Unit clerks entered the data at the time of admission, specifying each admission as emergent or scheduled. A hospital census was calculated for every hour of each calendar day, and peak census figures extracted for each day. Occupancy was calculated as census over number of beds available for use. The investigators calculated patterns of occupancy by day of week and month of year and expressed variability using the coefficient of variation (CV) (standard deviation divided by the mean).Of 22,310 admissions, 22% were scheduled and 78% emergent. Mean length of stay (LOS) for scheduled patients was longer for those admitted on Monday than on any other weekday (2.49 vs 2.08 days; P<.0001). Mean LOS for emergent patients was longer for patients admitted on Friday and Saturday than the rest of the week (2.57 vs 2.44 days; P<.0001). Total admissions per month averaged 1,937 in October through April and 1,751 in May through September (P=.03). Variation in the number of emergent and scheduled patients over months of the year were similar (CV 10%) for each, but emergent admissions decreased in the summer (mean 1,299 for June–September vs 1,520 for the rest of the year; P=.003). Scheduled admissions remained relatively stable all year long. Variation in volume of admissions was large over days of the week, mostly due to the pattern of scheduled admissions (CV 65.3%), which dropped off completely on weekends. There was little variability in emergent admissions across days of the week (CV 12%). More emergent and scheduled patients came in on Mondays than any other day of the week, but this was more pronounced for scheduled admissions. The combined impact of volume and LOS from admissions earlier in the week contributed to midweek crowding, with higher risk of the hospital being over 90% and 95% occupied from Wednesday afternoon to Friday afternoon, especially from November through February (70%–85% of days).The authors conclude that although scheduled patients contributed less to the hospital’s overall occupancy, they conferred most of the variability in occupancy by day of week and the consequent risk of midweek crowding.Dr Garber has disclosed no financial relationship relevant to this commentary. This commentary does not contain a discussion of an unapproved/investigative use of a commercial product/device.Optimizing patient flow improves quality, finances, staff and patient satisfaction, and overall value.1,2 These authors counter the obvious limitations of this study (one year/one hospital) by suggesting that each hospital perform its own analysis using similar methods, which considers both admissions and associated LOS. The CV is the appropriate statistical tool, because it measures variability without regard to baseline. The solutions the authors propose are intriguing, if sometimes impractical. They suggest utilizing weekends as full service days, shifting winter elective procedures to spring and fall, and shifting spring and fall procedures into summer. They suggest that the marginal costs of staffing to provide safe, high quality care on weekends pales compared to the $1–2 million cost of constructing a new bed, and leads to recovery of lost revenue from unused bed capacity.3 They hypothesize that the longer LOS for emergent patients admitted on Friday relates to unavailable services over the weekend, underscoring inefficiencies of the current system.A shibboleth of lean manufacturing is that systems are perfectly designed to deliver the results they produce, good or bad. This study demonstrates that much of the variation in hospital census is predictable and therefore potentially manageable. Leveling the patient load can reduce waste (downtime due to overstaffing, waiting time due to understaffing), improve safety (reduce errors due to staff overload and fatigue), and improve quality (timeliness, efficiency of care). The enormous capital cost of modern hospitals demands 24/7/365 utilization. To level the load, perhaps the time has come to variably price some hospital care by day of week, in the same way that tolls vary by time of day on busy freeways and parking fees vary by time of day in central cities.