Pathway variation analysis (PVA): Modelling and simulations. (September 2015)

• Record Type: Journal Article
• Authors: Shukla, Nagesh; Lahiri, Sudi; Ceglarek, Darek
• Is Part Of: Operations research for health care. Volume 6(2015:Sep.)
• Page Start: 61
• Page End: 77
• Publication Date: 2015-09
• Subjects: Stroke care pathways -- Simulation -- Process modeling -- Decision making; Medical care -- Mathematical models -- Periodicals; Medical policy -- Mathematical models -- Periodicals; Health services administration -- Mathematical models -- Periodicals; Operations research -- Periodicals; Operations Research -- Periodicals; Health Services Research -- Periodicals; Health Policy -- Periodicals; Delivery of Health Care -- Periodicals; 362.106805
• DOI: 10.1016/j.orhc.2015.09.004
• Languages: English
• ISSNs: 2211-6923

Abstract

Abstract: Maintaining a care pathway within a hospital to provide complex care to patients is associated with challenges related to variations from the pathway. This occurs due to ineffective decision-making processes, unclear process steps, the interactions, conflicting performance measures for speciality units, and the availability of resources. These variations from the care pathway or standard care delivery processes lead to longer patient waiting times and lower patient throughput. Traditional approaches to improve the pathway focus primarily on reducing variations within the care pathway such as bottlenecks or throughput within the pathway rather than examining variations from the care pathway. In this study, we propose a novel methodology, called pathway variation analysis (PVA), to identify, simulate and analyse variations from the patient care pathways. PVA method includes patient ward level journey dataset and qualitative staff interviews to simulate patient variations. The proposed methodology had been applied to the stroke care services of a hospital, which increased their key performance from 73% to 84.97%. A PVA methodology is proposed which simulated patient diversions from the care pathway by modelling hospital operational parameters, assessing the accuracy of clinical decisions and performance measures of speciality units involved. The proposed methodology can be applied to other care pathways settings to reduce patient diversion from the care pathway.