Kurniati, AP orcid.org/0000-0002-4747-1067, Rojas, E, Hogg, D orcid.org/0000-0002-6125-9564 et al. (2 more authors) (2019) The assessment of data quality issues for process mining in healthcare using Medical Information Mart for Intensive Care III, a freely available e-health record database. Health Informatics Journal, 25 (4). pp. 1878-1893. ISSN 1460-4582
Abstract
There is a growing body of literature on process mining in healthcare. Process mining of electronic health record systems could give benefit into better understanding of the actual processes happened in the patient treatment, from the event log of the hospital information system. Researchers report issues of data access approval, anonymisation constraints, and data quality. One solution to progress methodology development is to use a high-quality, freely available research dataset such as Medical Information Mart for Intensive Care III, a critical care database which contains the records of 46,520 intensive care unit patients over 12 years. Our article aims to (1) explore data quality issues for healthcare process mining using Medical Information Mart for Intensive Care III, (2) provide a structured assessment of Medical Information Mart for Intensive Care III data quality and challenge for process mining, and (3) provide a worked example of cancer treatment as a case study of process mining using Medical Information Mart for Intensive Care III to illustrate an approach and solution to data quality challenges. The electronic health record software was upgraded partway through the period over which data was collected and we use this event to explore the link between electronic health record system design and resulting process models.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018, The Author(s). This is an author produced version of a journal article published in Health Informatics Journal. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | data quality; healthcare; process mining; Medical Information Mart for Intensive Care III |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 13 Nov 2018 13:55 |
Last Modified: | 26 Sep 2019 10:28 |
Status: | Published |
Publisher: | SAGE Publications |
Identification Number: | 10.1177/1460458218810760 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:138532 |