A system dynamics-based simulation study for managing clinical governance and pathways in a hospital

Maliapen, M; Dangerfield, BC

Abstract

This paper examines the development of clinical pathways in a hospital in Australia based on empirical clinical data of patient episodes. A system dynamics (SD)-based decision support system (DSS) is developed and analyzed for this purpose.
System dynamics was used as the simulation modeling tool because of its rigorous approach in capturing interrelationships among variables and in handling dynamic aspects of the system behavior in managing healthcare. The study highlights the scenarios that will help hospital administrators to redistribute caseloads amongst admitting clinicians with a focus on multiple Diagnostic Related Groups (DRG’s) as the means to improve the patient turnaround and hospital throughput without compromising quality patient care. DRG’s are the best known classification system used in a casemix funding model. The classification system groups inpatient stays into clinically meaningful categories of similar levels of complexity that consume similar amounts of resources.
Policy explorations reveal various combinations of the dominant policies that hospital management can adopt. The analyses act as a scratch pad for the executives as they understand what can be feasibly achieved by the implementation of clinical pathways given a number of constraints. With the use of visual interfaces, executives can manipulate the DSS to test various scenarios. Experimental evidence based on focus groups demonstrated that the DSS can enhance group learning processes and improve decision making. The simulation model findings support recent studies of CP implementation on various DRG’s published in the medical literature. These studies showed substantial reductions in length of stay, costs and resource utilization.

• Journal Article Type: Article
• Publication Date: Feb 1, 2010
• Deposit Date: Oct 4, 2011
• Publicly Available Date: Apr 5, 2016
• Journal: Journal of the Operational Research Society
• Print ISSN: 0160-5682
• Electronic ISSN: 1476-9360
• Publisher: Palgrave Macmillan
• Peer Reviewed: Peer Reviewed
• Volume: 61
• Issue: 2
• Pages: 255-264
• DOI: https://doi.org/10.1057/jors.2008.134
• Keywords: Clinical pathways, system dynamics, decision support system, diagnostic-related groups (DRG)
• Publisher URL: http://dx.doi.org/10.1057/jors.2008.134