Using discrete-event simulation in strategic capacity planning for an outpatient physical therapy service

Chi Lun Rau, Pei Fang Jennifer Tsai, Sheau Farn Max Liang, Jhih Cian Tan, Hong Cheng Syu, Yue Ling Jheng, Ting Syuan Ciou, Fu Shan Jaw

Research output: Contribution to journalArticlepeer-review

25 Citations (Scopus)

Abstract

This study uses a simulation model as a tool for strategic capacity planning for an outpatient physical therapy clinic in Taipei, Taiwan. The clinic provides a wide range of physical treatments, with 6 full-time therapists in each session. We constructed a discrete-event simulation model to study the dynamics of patient mixes with realistic treatment plans, and to estimate the practical capacity of the physical therapy room. The changes in time-related and space-related performance measurements were used to evaluate the impact of various strategies on the capacity of the clinic. The simulation results confirmed that the clinic is extremely patient-oriented, with a bottleneck occurring at the traction units for Intermittent Pelvic Traction (IPT), with usage at 58.9 %. Sensitivity analysis showed that attending to more patients would significantly increase the number of patients staying for overtime sessions. We found that pooling the therapists produced beneficial results. The average waiting time per patient could be reduced by 45 % when we pooled 2 therapists. We found that treating up to 12 new patients per session had no significantly negative impact on returning patients. Moreover, we found that the average waiting time for new patients decreased if they were given priority over returning patients when called by the therapists.

Original languageEnglish
Pages (from-to)352-365
Number of pages14
JournalHealth Care Management Science
Volume16
Issue number4
DOIs
Publication statusPublished - Dec 1 2013

Keywords

  • Clinic capacity planning
  • Patient mix
  • Terminating simulation
  • Therapist pooling

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Health Professions(all)

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