PubMed · 10251370
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M G Davidge, J M Yates, L Wainwright. 1981. Midnight magic?. https://pubmed.ncbi.nlm.nih.gov/10251370/
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There is considerable evidence that the distribution of the length of time that a patient occupies a bed in a hospital department is best described by a sum of two or three exponential terms, because of the presence of acute care, rehabilitation, and possibly long term care patients in the department. The patient flow models implied by these mixed exponential distributions are presented and fitting them to observed data when the admission rate fluctuates is discussed. Unlike single exponential distributions, mixed exponential distributions imply that the average length of stay of patients currently resident in the department is much longer than the average length of stay of a group of patients discharged over a period of time, so that the latter way of measuring will not correctly indicate what portion of the resources are being used by rehabilitation and long term care patients. Also, the expected additional length of stay increases dramatically with the time already spent in the department. Applications to predicting the effects of policy changes and to long term monitoring of hospital departments are presented. Two American hospitals are analyzed. The occupancy times in the government supported hospital follow a mixed exponential distribution similar to those found in the United Kingdom, but in the private hospital they fit a single exponential distribution, indicating markedly different management practices.
Pressure is increasing on hospitals to do more with fewer resources. The appropriate management of hospital beds is crucial. The author's practical experience of applying the Harrison and Millard Flow Model (BOMPS) and Sorensen's multi-phased bed model to aspects of the public hospital system in South Australia are detailed. These techniques can provide decision makers with improved bed management information. Modelling enables the effects of decisions to be analyzed before implementation. Further development of these tools, together with other modelling approaches, cannot be ignored as a means of improving the strategic management of hospital beds.
STUDY OBJECTIVE: We sought to determine whether sharing an observation unit with scheduled procedure patients would maintain a more consistent unit census and patient/nurse ratio. A secondary objective was to determine the effect of this model on patient length of stay and discharge rates. METHODS: This retrospective, descriptive study was conducted in a high-volume suburban teaching hospital, using a "before-and-after" study design. A "pure" postprocedure unit became a "hybrid" observation postprocedure unit by displacing specific postprocedure patients to inpatient locations. Subsequently, the displaced patients were returned to the unit. On weekends, the unit operated as a pure observation unit. Hourly unit occupancy and census data were prospectively collected, and hourly patient/nurse ratios were calculated. Patient length of stay and discharge data were collected and compared in different settings. RESULTS: The 2 services showed a complementary census pattern that allowed the hybrid unit to maintain an average hourly patient/nurse ratio of 3.7 compared with the ratio of 2.5 for a pure observation unit. There was no difference in observation patient length of stay (14.8 hours versus 14.7 hours) or discharge rate (20.4% versus 18.1%) between weekdays and weekends. However, scheduled procedure patients experienced significantly shorter lengths of stay in the hybrid unit setting (4.3 hours) than in alternative inpatient locations (9.4 hours). CONCLUSION: The hybrid model showed better hourly census and nurse resource use rates, with no adverse effect on observation patients. However, scheduled procedure patient length of stay was shorter in this setting.