Evidence generation, decision making, and consequent growth in health disparities

Anirban Basu () and Kritee Gujral
Additional contact information
Anirban Basu: The Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute, University of Washington, Seattle, WA 98195; Health Care Program, The National Bureau of Economic Research, Cambridge, MA 02138
Kritee Gujral: The Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute, University of Washington, Seattle, WA 98195

Proceedings of the National Academy of Sciences, 2020, vol. 117, issue 25, 14042-14051

Abstract: Evidence is valuable because it informs decisions to produce better outcomes. However, the same evidence that is complete for some individuals or groups may be incomplete for others, leading to inefficiencies in decision making and growth in disparities in outcomes. Specifically, the presence of treatment effect heterogeneity across some measure of baseline risk, and noisy information about such heterogeneity, can induce self-selection into randomized clinical trials (RCTs) by patients with distributions of baseline risk different from that of the target population. Consequently, average results from RCTs can disproportionately affect the treatment choices of patients with different baseline risks. Using economic models for these sequential processes of RCT enrollment, information generation, and the resulting treatment choice decisions, we show that the dynamic consequences of such information flow and behaviors may lead to growth in disparities in health outcomes across racial and ethnic categories. These disparities arise due to either the differential distribution of risk across those categories at the time RCT results are reported or the different rate of change of baseline risk over time across race and ethnicity, even though the distribution of risk within the RCT matched that of the target population when the RCT was conducted. We provide evidence on how these phenomena may have contributed to the growth in racial disparity in diabetes incidence.

Keywords: evidence-based medicine; health disparity; diabetes incidence; treatment effect heterogeneity (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.pnas.org/content/117/25/14042.full (application/pdf)

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:nas:journl:v:117:y:2020:p:14042-14051

Access Statistics for this article

More articles in Proceedings of the National Academy of Sciences from Proceedings of the National Academy of Sciences
Bibliographic data for series maintained by PNAS Product Team ().