Optimisation of logistics operations in healthcare systems using predictive data analytics

Divya Agarwal and Aditi Sharma

International Journal of Logistics Systems and Management, 2024, vol. 49, issue 1, 82-97

Abstract: Healthcare organisations worldwide are under continuous pressure to provide the best treatment to patients yet keeping in mind the cost of treatment. Predictive analysis is an approach towards the efficient management of logistics where algorithms are performed on the data collected from electronic health records, wearable medical devices or from any trusted sources. Later, optimisation can be done by analysing the result. This would result in positive patient outcomes and ensure the smooth functioning of healthcare systems worldwide without putting extra pressure on them. Importance of predictive data analytics in healthcare and various ways to optimise patient outcomes are discussed in this paper.

Keywords: predictive data analytics; logistics; healthcare systems; supply chain; operations management; algorithms; optimisation; patient stay; hospital resources; analysis. (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=141530 (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:ids:ijlsma:v:49:y:2024:i:1:p:82-97

Access Statistics for this article

More articles in International Journal of Logistics Systems and Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().