“Nursevendor Problem”: Personnel Staffing in the Presence of Endogenous Absenteeism

Linda V. Green (), Sergei Savin () and Nicos Savva ()
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Linda V. Green: Graduate School of Business, Columbia University, New York, New York 10027
Sergei Savin: The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104
Nicos Savva: London Business School, London NW1 4SA, United Kingdom

Management Science, 2013, vol. 59, issue 10, 2237-2256

Abstract: The problem of determining nurse staffing levels in a hospital environment is a complex task because of variable patient census levels and uncertain service capacity caused by nurse absenteeism. In this paper, we combine an empirical investigation of the factors affecting nurse absenteeism rates with an analytical treatment of nurse staffing decisions using a novel variant of the newsvendor model. Using data from the emergency department of a large urban hospital, we find that absenteeism rates are consistent with nurses exhibiting an aversion to higher levels of anticipated workload. Using our empirical findings, we analyze a single-period nurse staffing problem considering both the case of constant absenteeism rate (exogenous absenteeism) as well as an absenteeism rate that is a function of the number of nurses scheduled (endogenous absenteeism). We provide characterizations of the optimal staffing levels in both situations and show that the failure to incorporate absenteeism as an endogenous effect results in understaffing. This paper was accepted by Yossi Aviv, operations management.

Keywords: healthcare; hospitals; nursing; newsvendor; econometrics; organizational studies; manpower planning (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:59:y:2013:i:10:p:2237-2256

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