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

• Published in: Health care management science 2013-12, Vol.16 (4), p.352-365
• Main Authors: Rau, Chi-Lun, Tsai, Pei-Fang Jennifer, Liang, Sheau-Farn Max, Tan, Jhih-Cian, Syu, Hong-Cheng, Jheng, Yue-Ling, Ciou, Ting-Syuan, Jaw, Fu-Shan
• Format: Article
• Language: English
• Subjects: Ambulatory Care Facilities - organization & administration; Appointments and Schedules; Business and Management; Clinics; Computer Simulation; Econometrics; Efficiency, Organizational; Health Administration; Health care industry; Health care management; Health Informatics; Health insurance; Hospitals; Humans; Management; National health insurance; Needs Assessment; Operations Research/Decision Theory; Outpatient care facilities; Overtime; Overtime pay; Patients; Physical therapy; Physical Therapy Specialty - organization & administration; Planning; Planning Techniques; Sensitivity analysis; Simulation; Strategic planning; Studies; Taiwan; Therapists; Time Factors; Waiting Lists; Workflow; Workloads
• ISSN: 1386-9620; 1572-9389
• DOI: 10.1007/s10729-013-9234-2

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.