Frontiers of medical decision-making in the modern age of data analytics
Brian T. Denton
IISE Transactions, 2023, vol. 55, issue 1, 94-105
Abstract:
Recent decades have seen considerable advances in developing Industrial Engineering/Operations Research (IE/OR) models for improving decision-making in healthcare. These approaches span the full range of descriptive, predictive, and prescriptive models for supporting patients' and clinicians' decision-making. The pervasive use of information technology to collect and store electronic health records, insurance claims, genomic information, and other observational data has opened new doors for developing, validating, and applying these types of data-driven IE/OR models. This article describes opportunities at the frontier of medical decision-making, emphasizing the intersection of medicine, data analytics, and operations research. Many of the examples covered intersect the fields of statistics, machine learning, and artificial intelligence. A series of motivating examples illustrate the possibilities and some promising future research directions.
Date: 2023
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/24725854.2022.2092918 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:uiiexx:v:55:y:2023:i:1:p:94-105
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/uiie20
DOI: 10.1080/24725854.2022.2092918
Access Statistics for this article
IISE Transactions is currently edited by Jianjun Shi
More articles in IISE Transactions from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().