ORAHS2025
Abstract Submission

184. Care pathway optimisation using Markov chain modelling

Invited abstract in session FA-3: Elderly care, stream Sessions.

Friday, 9:00-10:30
Room: NTNU, Realfagbygget R9

Authors (first author is the speaker)

1. Maik Overmars
Mathematics of Operations Research, University of Twente
2. Richard Boucherie
Stochastich Operations Research, University of Twente

Abstract

Designing effective care pathways can aid in the standardisation of the care process, and increase the efficiency of the healthcare institution.
An important challenge lies in using Electronic Health Record (EHR) data to accurately model the pathways to gain insight into their effect on resources such as capacity.
Typically, care pathways are multidisciplinary plans that describe the exact sequence of interventions that patients receive.
We consider the setting where a pathway contains regular appointments per discipline over a longer period of time, and the pathway contains decision moments where healthcare professionals determine whether and how to continue treatment.
Each section of the pathway between decision moments is described by the intensity of appointments received per discipline.
In this paper, we propose a Markov chain model, in which the states correspond to sections of the care pathway, that is estimated using EHR data.
With this Markov chain we are able to determine the exact distribution of capacity required given a set of pathways.
We optimise the care pathways by modifying treatment intensities and the parameters of the Markov chain.
We apply our approach to a rehabilitation clinic and show how our method can aid in the design of efficient care pathways.

Keywords

Status: accepted

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