Literature DB >> 27544069

A guide for the application of analytics on healthcare processes: A dynamic view on patient pathways.

Jasmien Lismont1, Anne-Sophie Janssens2, Irina Odnoletkova3, Seppe Vanden Broucke2, Filip Caron2, Jan Vanthienen2.   

Abstract

OBJECTIVE: The aim of this study is to guide healthcare instances in applying process analytics on healthcare processes. Process analytics techniques can offer new insights in patient pathways, workflow processes, adherence to medical guidelines and compliance with clinical pathways, but also bring along specific challenges which will be examined and addressed in this paper.
METHODS: The following methodology is proposed: log preparation, log inspection, abstraction and selection, clustering, process mining, and validation. It was applied on a case study in the type 2 diabetes mellitus domain.
RESULTS: Several data pre-processing steps are applied and clarify the usefulness of process analytics in a healthcare setting. Healthcare utilization, such as diabetes education, is analyzed and compared with diabetes guidelines. Furthermore, we take a look at the organizational perspective and the central role of the GP. This research addresses four challenges: healthcare processes are often patient and hospital specific which leads to unique traces and unstructured processes; data is not recorded in the right format, with the right level of abstraction and time granularity; an overflow of medical activities may cloud the analysis; and analysts need to deal with data not recorded for this purpose. These challenges complicate the application of process analytics. It is explained how our methodology takes them into account.
CONCLUSION: Process analytics offers new insights into the medical services patients follow, how medical resources relate to each other and whether patients and healthcare processes comply with guidelines and regulations.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Case study; Electronic healthcare records; Healthcare processes; Patient pathway; Process analytics

Mesh:

Year:  2016        PMID: 27544069     DOI: 10.1016/j.compbiomed.2016.08.007

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  4 in total

1.  Mapping the Flow of Pediatric Trauma Patients Using Process Mining.

Authors:  Ashimiyu B Durojaiye; Nicolette M McGeorge; Lisa L Puett; Dylan Stewart; James C Fackler; Peter L T Hoonakker; Harold P Lehmann; Ayse P Gurses
Journal:  Appl Clin Inform       Date:  2018-08-22       Impact factor: 2.342

2.  Can process mining automatically describe care pathways of patients with long-term conditions in UK primary care? A study protocol.

Authors:  Ian Litchfield; Ciaron Hoye; David Shukla; Ruth Backman; Alice Turner; Mark Lee; Phil Weber
Journal:  BMJ Open       Date:  2018-12-04       Impact factor: 2.692

3.  Modified Needleman-Wunsch algorithm for clinical pathway clustering.

Authors:  Emma Aspland; Paul R Harper; Daniel Gartner; Philip Webb; Peter Barrett-Lee
Journal:  J Biomed Inform       Date:  2021-01-27       Impact factor: 6.317

4.  Towards the Use of Standardized Terms in Clinical Case Studies for Process Mining in Healthcare.

Authors:  Emmanuel Helm; Anna M Lin; David Baumgartner; Alvin C Lin; Josef Küng
Journal:  Int J Environ Res Public Health       Date:  2020-02-19       Impact factor: 3.390

  4 in total

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