Cost-Utility Analysis of the Caresyntax Platform to Identify Patients at Risk of Surgical Site Infection Undergoing Colorectal Surgery

Eoin Moloney (), Atefeh Mashayekhi, Mehdi Javanbakht, Mohsen Rezaei Hemami and Michael Branagan-Harris
Additional contact information
Eoin Moloney: Optimax Access Ltd.
Atefeh Mashayekhi: Optimax Access Ltd.
Mehdi Javanbakht: Optimax Access Ltd.
Michael Branagan-Harris: Device Access Ltd.

PharmacoEconomics - Open, 2023, vol. 7, issue 2, No 10, 285-298

Abstract: Abstract Background Surgical site infections (SSIs) account for up to 18% of all healthcare-associated infections (HAIs). The Caresyntax data-driven surgery platform incorporates the most common risk factors for SSI, to identify high-risk surgical patients before they leave the operating theatre and treat them prophylactically with negative pressure wound therapy (NPWT). An economic analysis was performed to assess the costs and health outcomes associated with introduction of the technology in the English healthcare setting. Methods A hybrid decision tree/Markov model was developed to reflect the treatment pathways that patients undergoing colorectal surgery would typically follow, both over the short term (30-day hospital setting) and long term (lifetime). The analysis considered implementation of Caresyntax’s platform-based SSI predictive algorithm in the hospital setting, compared with standard of care, from an English National Health Service (NHS) perspective. The base-case analysis presents results in terms of cost per quality-adjusted life-year (QALY) gained, as well as operational impact. Results The base-case analysis indicates that the intervention leads to a cost saving of £55.52m across the total NHS colorectal surgery patient population in 1 year. In addition, the intervention has a 98.36% probability of being cost effective over a lifetime horizon. The intervention results in the avoidance of 19,744 SSI events, as well 191,911 excess hospital bed days saved. Conclusion Caresyntax’s platform-based SSI predictive algorithm has the potential to result in cost savings and improved patient quality of life. Additionally, operational gains for the healthcare provider, including reduced infection rates and hospital bed days saved, have been shown through the economic modeling.

Date: 2023
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s41669-023-00389-z Abstract (text/html)

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:spr:pharmo:v:7:y:2023:i:2:d:10.1007_s41669-023-00389-z

Ordering information: This journal article can be ordered from
http://www.springer.com/adis/journal/41669

DOI: 10.1007/s41669-023-00389-z

Access Statistics for this article

PharmacoEconomics - Open is currently edited by Timothy Wrightson and Christopher Carswell

More articles in PharmacoEconomics - Open from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().