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Pathway variation analysis (PVA): modelling and simulations
SMART Infrastructure Facility - Papers
  • Nagesh Shukla, University of Wollongong
  • Sudi Lahiri, University of Warwick
  • Darek Ceglarek, University of Warwick
RIS ID
103259
Publication Date
1-1-2015
Publication Details

Shukla, N., Lahiri, S. & Ceglarek, D. (2015). Pathway variation analysis (PVA): modelling and simulations. Operations Research for Health Care, In press

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.

Citation Information
Nagesh Shukla, Sudi Lahiri and Darek Ceglarek. "Pathway variation analysis (PVA): modelling and simulations" (2015)
Available at: http://works.bepress.com/nagesh_shukla/34/