Process mining for healthcare: Characteristics and challenges

Jorge Muñoz-Gama ,Moe Thandar Wynn,Roberto Gatta,Benjamin Dalmas,Vicente Traver,Simon Remy,Claudio Di Ciccio,Emmanuel Helm,Marco Pegoraro,Simon K Poon,Fernando Seoane,Mathias Weske,Ilaria Angela Amantea,Michael Arias,Eric Rojas,Luise Pufahl,Chiara Di Francescomarino,Emilio Sulis,Niels Martin,Daniel Capurro,Iris Beerepoot,Inge Van De Weerd,Josep Carmona,Felix Mannhardt,Xixi Lu,Renata Medeiros De Carvalho,Minseok Song,Elisabetta Benevento,Chiara Ghidini,Stefanie Rinderle-Ma,Francesca Zerbato,Hajo A Reijers,Angelina Prima Kurniati,Davide Aloini,Pieter J Toussaint,Andrea Burattin,Alessandro Stefanini,Fernanda Gonzalez-Lopez,Robert Andrews,Marco Comuzzi,Marcos Sepúlveda,Mar Marcos,Lucia Sacchi,René De La Fuente ,Ronny S Mans ,Wil M P Van Der Aalst ,Rob J B Vanwersch ,Víctor Gálvez ,Owen Johnson ,Antonio Martínez-Millana ,Carlos Fernández-Llatas ,Hilda Klasky ,Gema Ibáñez-Sánchez ,Zoe Valero-Ramón ,Arthur H M Ter Hofstede

doi:10.1016/j.jbi.2022.103994

Abstract

Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.

Highlights

Innovations make healthcare better, affordable and efficient
Healthcare systems are confronted across the world with unprecedented challenges, including the perma nent and rapid adaptation of clinical processes based on the emerging scientific evidence [2] and the provision of high-quality care with limited resources [3,4,5]
Healthcare organisations, such as hospitals, are aware of the need to manage and improve both their clinical processes and their organisational/ administrative processes [6,7]

Summary

Introduction

Innovations make healthcare better, affordable and efficient. De velopments such as new technologies and business models help to move healthcare forward [1]. Healthcare systems are confronted across the world with unprecedented challenges, including the perma nent and rapid adaptation of clinical processes based on the emerging scientific evidence [2] and the provision of high-quality care with limited resources [3,4,5]. Within this context, healthcare organisations, such as hospitals, are aware of the need to manage and improve both their clinical processes (e.g., care pathways describing the treatment of a particular medical condition over the time) and their organisational/ administrative processes (e.g., billing processes) [6,7]. As the event log reflects how a process has been executed in reality, it can support clinicians, healthcare organisa tion’s managers, and other decision-makers with a wide range of process-related questions in the medical domain

Objectives

Methods

Conclusion