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Inverse optimization on hierarchical networks: an application to breast cancer clinical pathways.

Authors :
Chan TCY
Forster K
Habbous S
Holloway C
Ieraci L
Shalaby Y
Yousefi N
Source :
Health care management science [Health Care Manag Sci] 2022 Dec; Vol. 25 (4), pp. 590-622. Date of Electronic Publication: 2022 Jul 08.
Publication Year :
2022

Abstract

Clinical pathways are standardized processes that outline the steps required for managing a specific disease. However, patient pathways often deviate from clinical pathways. Measuring the concordance of patient pathways to clinical pathways is important for health system monitoring and informing quality improvement initiatives. In this paper, we develop an inverse optimization-based approach to measuring pathway concordance in breast cancer, a complex disease. We capture this complexity in a hierarchical network that models the patient's journey through the health system. A novel inverse shortest path model is formulated and solved on this hierarchical network to estimate arc costs, which are used to form a concordance metric to measure the distance between patient pathways and shortest paths (i.e., clinical pathways). Using real breast cancer patient data from Ontario, Canada, we demonstrate that our concordance metric has a statistically significant association with survival for all breast cancer patient subgroups. We also use it to quantify the extent of patient pathway discordances across all subgroups, finding that patients undertaking additional clinical activities constitute the primary driver of discordance in the population.<br /> (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Details

Language :
English
ISSN :
1572-9389
Volume :
25
Issue :
4
Database :
MEDLINE
Journal :
Health care management science
Publication Type :
Academic Journal
Accession number :
35802305
Full Text :
https://doi.org/10.1007/s10729-022-09599-z