Exploring trade-offs between staffing levels and turnaround time in a pathology laboratory using discrete event simulation

Kanokporn Pongjetanapong*, Cameron Walker, Michael O'Sullivan, Margaret Lovell-Smith, Nikolaus Furian

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

Many health delivery services have required performance targets. Typically, these targets are presented as percentiles of patients to be seen within specified timeframes. These targets present hospital administrators with a resourcing problem complicated by conflicting objectives: How to minimize costs while maximizing throughput to achieve the performance targets? In this paper, we describe the use of a simulation model to evaluate the effect of changes to staff levels in a cytology department, investigating the trade-off between staff levels and turnaround times in light of performance targets specified by government. Standard practice for determining staffing levels in a cytology department uses average workload estimates and does not take into account target performance measures, task variability, and the interruptive nature of the workload of pathologists. We develop a simulation model for pathologist workload within a cytology department in New Zealand. We describe the model construction process that follows the hierarchical control conceptual modeling (HCCM) framework. We use the resulting simulation model to examine the trade-offs between staffing levels (and associated rosters) and task turnaround time. The results indicate that consideration of variation in task arrivals is important when considering the effect of staffing levels on turnaround time. Furthermore, as the cytology department is required to meet performance targets that involve maximum service times for a percentile of patients, such an approach is necessary in order to estimate the performance level of a staffing roster.

Original languageEnglish
Pages (from-to)e1119-e1134
JournalInternational Journal of Health Planning and Management
Volume34
Issue number2
DOIs
Publication statusPublished - 1 Apr 2019

Keywords

  • discrete event simulation
  • performance targets
  • resource planning
  • staffing levels
  • trade-offs

ASJC Scopus subject areas

  • Health Policy

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