Maximizing Intervention Effectiveness

59 Pages Posted: 29 Aug 2017 Last revised: 13 Sep 2019

See all articles by Vishal Gupta

Vishal Gupta

University of Southern California - Marshall School of Business

Brian Rongqing Han

Gies College of Business, UIUC

Song-Hee Kim

Seoul National University - Business School

Hyung Paek

Yale University - Yale New Haven Hospital (YNHH)

Date Written: August 26, 2017

Abstract

Frequently, policymakers seek to roll out an intervention previously proven effective in a research study, perhaps subject to resource constraints. However, since different subpopulations may respond differently to the same treatment, there is no a priori guarantee that the intervention will be as effective in the targeted population as it was in the study. How then should policymakers target individuals to maximize intervention effectiveness? We propose a novel robust optimization approach that leverages evidence typically available in a published study. Our approach is tractable -- real-world instances are easily optimized in minutes with off-the-shelf software -- and flexible enough to accommodate a variety of resource and fairness constraints. We compare our approach with current practice by proving tight, performance guarantees for both approaches which emphasize their structural differences. We also prove an intuitive interpretation of our model in terms of regularization, penalizing differences in the demographic distribution between targeted individuals and the study population. Although the precise penalty depends on the choice of uncertainty set, we show for special cases that we can recover classical penalties from the covariate matching literature on causal inference. Finally, using real data from a large teaching hospital, we compare our approach to current practice in the particular context of reducing emergency department utilization by Medicaid patients through case management. We find that our approach can offer significant benefits over current practice, particularly when the heterogeneity in patient response to the treatment is large.

Keywords: analytics, robust optimization, intervention effectiveness, healthcare

Suggested Citation

Gupta, Vishal and Han, Brian Rongqing and Kim, Song-Hee and Paek, Hyung, Maximizing Intervention Effectiveness (August 26, 2017). Available at SSRN: https://ssrn.com/abstract=3026913 or http://dx.doi.org/10.2139/ssrn.3026913

Vishal Gupta

University of Southern California - Marshall School of Business ( email )

701 Exposition Blvd
Los Angeles, CA California 90089
United States

Brian Rongqing Han (Contact Author)

Gies College of Business, UIUC ( email )

1206 South Sixth Street
Champaign, IL 61820
United States

Song-Hee Kim

Seoul National University - Business School ( email )

Seoul
Korea, Republic of (South Korea)

Hyung Paek

Yale University - Yale New Haven Hospital (YNHH) ( email )

New Haven, CT 06520
United States

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