EconPapers    
Economics at your fingertips  
 

Portfolio frontier analysis: Applying mean-variance analysis to health technology assessment for health systems under pressure

Darrin Baines, Marta Disegna and Christopher Hartwell ()

Social Science & Medicine, 2021, vol. 276, issue C

Abstract: The COVID-19 pandemic is challenging how healthcare technologies are evaluated, as new, more dynamic methods are required to test the cost effectiveness of alternative interventions during use rather than before initial adoption. Currently, health technology assessment (HTA) tends to be static and a priori: alternatives are compared before launch, and little evaluation occurs after implementation. We suggest a method that builds upon the current pre-launch HTA procedures by conceptualizing a mean-variance approach to the continuous evaluation of attainable portfolios of interventions in health systems. Our framework uses frontier analysis to identify the desirability of available health interventions so decision makers can choose diverse portfolios based upon information about expected returns and risks. This approach facilitates the extension of existing methods and assessments beyond the traditional concern with pre-adoption data, a much-needed innovation given the challenges posed by COVID-19.

Keywords: HTA; Portfolio; Mean variance; Health economics; Decision-making (search for similar items in EconPapers)
JEL-codes: G11 I10 I11 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0277953621001623
Full text for ScienceDirect subscribers only

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:eee:socmed:v:276:y:2021:i:c:s0277953621001623

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
http://www.elsevier. ... _01_ooc_1&version=01

DOI: 10.1016/j.socscimed.2021.113830

Access Statistics for this article

Social Science & Medicine is currently edited by Ichiro (I.) Kawachi and S.V. (S.V.) Subramanian

More articles in Social Science & Medicine from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2021-08-14
Handle: RePEc:eee:socmed:v:276:y:2021:i:c:s0277953621001623