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Daily nurse requirements planning based on simulation of patient flows

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Abstract

Nurses account for approximately 50 % of total hospital budgets and their allocation to medical units and shifts can significantly affect the quality of care provided to patients. The adoption of flexible shift schedules and the assessment of actual nursing time can enable sensible resource planning, balancing the quality of care with efficiency in resource use. Starting from the concept that nurse requirements are triggered by patient needs, which are stochastic in nature both for clinical activities and their duration, this paper proposes an innovative Nurse Requirement Planning model grounded on the concept of the clinical pathway (the “standard” sequence of diagnostic, therapeutic and care activities a patient with certain pathology should undertake over time) with its inner routing probability and patient dependence on nurses, which can be correlated to the time needed to perform nursing tasks. In merging and modelling these two aspects, the method summarizes the best features of acuity-quality and timed-task/activity techniques, well known although not usually applied for reasons of demands on clinicians’ time. Instead, in this paper, for each shift of the day, hospital management is enabled to choose the optimal number of nurses to meet actual requirements according to a desired service level and personnel saturation by means of a tool that simulates the patient flow in a medical unit based on automatic data retrieval from hospital databases. The validation and verification of the proposal were undertaken in a stroke unit.

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Authors and Affiliations

  1. Deparment of Industrial Engineering, University of Salerno, Fisciano, Italy

    Debora Sarno

  2. Deparment of Industrial Engineering, University of Naples Federico II, Naples, Italy

    Maria Elena Nenni

Authors
  1. Debora Sarno
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  2. Maria Elena Nenni
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Correspondence to Debora Sarno.

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Sarno, D., Nenni, M.E. Daily nurse requirements planning based on simulation of patient flows. Flex Serv Manuf J 28, 526–549 (2016). https://doi.org/10.1007/s10696-015-9231-5

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  • DOI: https://doi.org/10.1007/s10696-015-9231-5

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