Abstract
Purpose: We describe how the science of analyzing patient arrival and discharge data can be used to determine the optimal number of staffed OB beds to minimize labour costs.
Methods: The number of staffed beds represents a balance between having as few staffed beds as possible to care properly for parturientsvs having enough capacity to assure available staff for new admissions. The times of admission and discharge of patients from the OB unit can be used to calculate an average census. From this average census, and the properties of the Poisson distribution, the optimal number of staffed beds can be estimated. This calculation requires specification of the risk of having all in-house and on-call staff caring for patients, such that additional staff are unavailable should another parturient arrive. As an example, patient admission and discharge times were obtained for 777 successive patients cared for at an obstetrical unit. The numbers of patients present in the OB unit each two-hour period were calculated and analyzed statistically.
Principal findings: There was variation in the average census among hours of the day and days of the week. Poisson distributions fit the data for each of four periods throughout the week. Simply benchmarking the current average occupancy and comparing it to a desired occupancy would have been inadequate as this neglected consideration of the risk of being unable to appropriately care for an additional patient.
Conclusions: The optimal number of beds and occupancy of an OB unit to minimize staffing costs can be determined using straightforward statistical methods.
Résumé
Objectif: Montrer comment l’analyse des données sur l’arrivée et le départ des patientes peut servir à déterminer le nombre optimal de lits à assigner en obstétrique (OB) en vue de réduire le coût du travail.
Méthode: Le nombre de lits attribués représente un équilibre entre le fait d’avoir le moins de lits possibles pour pouvoir répondre aux besoins des patientes,vs avoir suffisamment de personnel disponible pour de nouvelles patientes. On peut utiliser l’heure d’arrivée et de départ pour le calcul du temps moyen passé en OB. À partir de ce séjour moyen, et des propriétés de la distribution de Poisson, le nombre optimal de lits réservés à l’OB peut être estimé. Ce calcul requiert la spécification du risque d’avoir tout le personnel sur place, en plus du personnel sur appel, affecté aux patientes, de sorte que personne ne sera disponible si une autre patiente se présente. Ainsi, les heures d’admission et de congé ont été obtenues pour 777 patientes successives admises à l’unité obstétricale. Le nombre de patientes présentes à l’unité OB à chaque heure a été soumis à un calcul et à une analyse statistiques.
Constatations principales: Le nombre moyen variait selon l’heure du jour et le jour de la semaine. Les distributions de Poisson s’accordaient aux données de chacune des quatre périodes de la semaine. Utiliser le temps moyen d’occupation courante comme référence et le comparer à l’occupation souhaitée serait inadéquat, puisqu’on ne tiendrait pas compte du risque de ne pouvoir assurer un traitement approprié à toute patiente supplémentaire.
Conclusion: On peut, dans le but de réduire le couût du personnel, déterminer le nombre optimal de lits et le meilleur taux d’occupation d’une unité d’OB à l’aide de méthodes statistiques simples.
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Financial disclosure: Franklin Dexter is employed by the University of Iowa, in part as a consultant to anesthesia groups, companies, and hospitals.
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Dexter, F., Macario, A. Optimal number of beds and occupancy to minimize staffing costs in an obstetrical unit?. Can J Anesth 48, 295–301 (2001). https://doi.org/10.1007/BF03019762
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DOI: https://doi.org/10.1007/BF03019762