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

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

doi:10.1007/s10729-013-9234-2

Cited by 42 publications

(20 citation statements)

References 26 publications

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“…Rapid advances in computer technology, software, and application tools have facilitated computer simulation studies in the fields such as hospital management, resource-planning, including those aimed at reduction in outpatient waiting time and optimizing of patient flow. [34][35][36][37][38] However, relatively few studies have focused on pharmacy system. For example, Tan et al used the DES model to evaluate the impact of automated dispensing system on patient waiting time and indicated that the introduction of the system helped reduce the waiting time.…”

Section: Discussionmentioning

confidence: 99%

The Impact of One-Dose Package of Medicines on Patient Waiting Time in Dispensing Pharmacy: Application of a Discrete Event Simulation Model

Furushima

Yamada

Kido

et al. 2018

Biological & Pharmaceutical Bulletin

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Improvement in patient waiting time in dispensing pharmacies is an important element for patient and pharmacists. The One-Dose Package (ODP) of medicines was implemented in Japan to support medicine adherence among elderly patients; however, it also contributed to increase in patient waiting times. Given the projected increase in ODP patients in the near future owing to rapid population aging, development of improved strategies is a key imperative. We conducted a cross-sectional survey at a single dispensing pharmacy to clarify the impact of ODP on patient waiting time. Further, we propose an improvement strategy developed with use of a discrete event simulation (DES) model. A total of 673 patients received pharmacy services during the study period. A two-fold difference in mean waiting time was observed between ODP and non-ODP patients (22.6 and 11.2 min, respectively). The DES model was constructed with input parameters estimated from observed data. Introduction of fully automated ODP (A-ODP) system was projected to reduce the waiting time for ODP patient by 0.5 times (from 23.1 to 11.5 min). Furthermore, assuming that 40% of non-ODP patients would transfer to ODP, the waiting time was predicted to increase to 56.8 min; however, introduction of the A-ODP system decreased the waiting time to 20.4 min. Our findings indicate that ODP is one of the elements that increases the waiting time and that it might become longer in the future. Introduction of the A-ODP system may be an effective strategy to improve waiting time.

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Section: Discussionmentioning

confidence: 99%

The Impact of One-Dose Package of Medicines on Patient Waiting Time in Dispensing Pharmacy: Application of a Discrete Event Simulation Model

Furushima

Yamada

Kido

et al. 2018

Biological & Pharmaceutical Bulletin

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“…In this paper, the discrete event simulation (DES) [10]- [14] technique is implemented, as support of the Business Process Management (BPM) [15] methodology, to study and improve the performances of healthcare facilities.…”

Section: Methodsmentioning

confidence: 99%

New Perspectives for Workflow Analysis in the Health Italian Sector through Discrete Event Simulation: The Case of a Department of Laboratory Medicine

Torri¹,

Tamburis²,

Abbate³

et al. 2015

IIM

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The management systems currently used in the Italian healthcare sector provide fragmented and incomplete information on this system and are generally unlikely to give accurate information on the performances of the healthcare processes. The present paper introduces a combined discrete event simulation (DES)/business process management (BPM) approach as innovative means to study the workflow of the activities within the Department of Laboratory Medicine of the "San Paolo" Hospital in Naples (Italy). After a first "As-Is" analysis to identify the current workflows of the system and to gather information regarding its behaviour, a following DES-based "What-If" analysis is implemented to figure out alternative work hypotheses in order to highlight possible modifications to the system's response under varying operating conditions and improve its overall performances. The structure of the simulation program is explained and the results of the scenario analysis are discussed. The paper starts with a brief exploration of the use of DES in healthcare and ends with general observations on the subject.

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“…The study conducted in Rau et al (2013) uses a simulation model as a tool for strategic capacity planning for an outpatient physical therapy clinic in Taipei, Taiwan. They constructed a discrete event simulation model to study the dynamics of patient mixes with realistic treatment plans to estimate the practical capacity of the physical therapy room.…”

Section: General Applicationsmentioning

confidence: 99%

Computer Simulation Model for Outpatient Clinics in a Brazilian Large Public Hospital Specialized in Cardiology

Chang

Lima

Fernandes

et al. 2019

BJO&PM

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Goal: the main objective of this study is to analyze the behavior of the outpatient department of a large public hospital specialized in cardiology, understanding how the components of this system are related, in order to improve the hospital's performance. Design / Methodology / Approach: a case study was carried out in a public hospital specializing in cardiology with the aid of Modeling and Simulation of System Dynamics. Results: the result showed that variables such as doctor availability and average consultation time have great influence on the service capacity. Limitations of the investigation: the proceedings and times related to the medical staff are particular to each team and they are not standardized. However, in the system dynamics modeling these particularities cannot be included. Practical implications: for theory, there is the state-of-the-art development in terms of how to manage and regarding the methodologies should be applied in a complex referential model composed of several moderating variables, in order to obtain the best use of the available resources (human and material) of the hospital. For practice, the flow of patients in the hospital should be predicted and optimized, adding value to the services provided to its users. Originality / Value: the originality of the work is based on the unprecedented application of quantitative methods for solving problems in Brazilian hospitals.

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

Cited by 42 publications

References 26 publications

The Impact of One-Dose Package of Medicines on Patient Waiting Time in Dispensing Pharmacy: Application of a Discrete Event Simulation Model

The Impact of One-Dose Package of Medicines on Patient Waiting Time in Dispensing Pharmacy: Application of a Discrete Event Simulation Model

New Perspectives for Workflow Analysis in the Health Italian Sector through Discrete Event Simulation: The Case of a Department of Laboratory Medicine

Computer Simulation Model for Outpatient Clinics in a Brazilian Large Public Hospital Specialized in Cardiology

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