EconPapers    
Economics at your fingertips  
 

Integrating decision modeling and machine learning to inform treatment stratification

David Glynn, John Giardina, Julia Hatamyar, Ankur Pandya, Marta Soares and Noemi Kreif

Health Economics, 2024, vol. 33, issue 8, 1772-1792

Abstract: There is increasing interest in moving away from “one size fits all (OSFA)” approaches toward stratifying treatment decisions. Understanding how expected effectiveness and cost‐effectiveness varies with patient covariates is a key aspect of stratified decision making. Recently proposed machine learning (ML) methods can learn heterogeneity in outcomes without pre‐specifying subgroups or functional forms, enabling the construction of decision rules (‘policies’) that map individual covariates into a treatment decision. However, these methods do not yet integrate ML estimates into a decision modeling framework in order to reflect long‐term policy‐relevant outcomes and synthesize information from multiple sources. In this paper, we propose a method to integrate ML and decision modeling, when individual patient data is available to estimate treatment‐specific survival time. We also propose a novel implementation of policy tree algorithms to define subgroups using decision model output. We demonstrate these methods using the SPRINT (Systolic Blood Pressure Intervention Trial), comparing outcomes for “standard” and “intensive” blood pressure targets. We find that including ML into a decision model can impact the estimate of incremental net health benefit (INHB) for OSFA policies. We also find evidence that stratifying treatment using subgroups defined by a tree‐based algorithm can increase the estimates of the INHB.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/hec.4834

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:wly:hlthec:v:33:y:2024:i:8:p:1772-1792

Access Statistics for this article

Health Economics is currently edited by Alan Maynard, John Hutton and Andrew Jones

More articles in Health Economics from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2025-03-20
Handle: RePEc:wly:hlthec:v:33:y:2024:i:8:p:1772-1792