Optimizing Economic Modelling Approaches in Health Disparities Research: Essential Insights

Author(s)

Adunlin G
Samford University, Chelsea, AL, USA

OBJECTIVES: The surge in health disparities research employing economic methodologies, catalyzed by the Affordable Care Act (ACA), necessitates a focused exploration of effective approaches. This study aims to delineate economic methods particularly relevant to health disparities research and identify optimal applications within this context.

METHODS: A thorough search across four databases (PubMed, Web of Science, Medline, and Embase) was conducted to identify pertinent English-language publications investigating health disparities in the United States using economic methodologies.

RESULTS: Among 3,479 articles, 201 studies met the inclusion criteria. Predominantly, the difference-in-difference (DID) method was employed to examine causal relationships between healthcare policies and health disparities in underserved groups. Economic evaluations informing priority setting and resource allocation in health disparities encompassed cost-effectiveness, cost-utility analyses, and cost-benefit analyses. Analyses of economic costs, utilizing the cost of illness method or estimating direct and indirect costs of managing health conditions, were prevalent. Notably, ACA and Medicaid expansions were focal points, and panel data coupled with quasi-experimental study designs were commonly utilized. Cancer care economic disparities constituted a significant area of investigation.

CONCLUSIONS: The application of economic methods in health disparities research has witnessed significant diversity. However, there remains a need for further research to establish guidelines for their appropriate application and reporting. This work aims to assist researchers and stakeholders in comprehending and selecting suitable economic methods, facilitating a nuanced interpretation of their findings in the realm of health disparities.

Conference/Value in Health Info

2024-05, ISPOR 2024, Atlanta, GA, USA

Value in Health, Volume 27, Issue 6, S1 (June 2024)

Code

EE348

Topic

Methodological & Statistical Research, Study Approaches

Topic Subcategory

Confounding, Selection Bias Correction, Causal Inference, Literature Review & Synthesis

Disease

No Additional Disease & Conditions/Specialized Treatment Areas

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