Gender Differences in Healthcare Utilisation - Evidence from Unexpected Adverse Health Shocks

2025-09-01

AI Summary

This study investigates the healthcare utilization mechanisms underlying the “female longevity–poorer health” paradox, focusing on gender disparities in medical resource use following acute non-fatal myocardial infarction or stroke. Leveraging Denmark’s nationwide administrative health registry, we implement a staggered difference-in-differences (DID) design—exploiting exogenous variation in diagnosis timing across conditions—to identify causal effects while controlling for individual fixed effects and time trends to enhance estimation precision. Results show that, following comparable health shocks, men utilize significantly more outpatient and inpatient services than women over time. This finding identifies differential healthcare utilization as a key behavioral pathway explaining gender disparities in health outcomes. It provides the first large-scale, real-world causal evidence linking gender-specific treatment responses to the longevity–health paradox, thereby filling a critical empirical gap in gender health economics—particularly regarding behavioral responses to acute morbidity.

Technology Category

• Game Theory and Economic Paradigms: Behavioral Game Theory
• Application Domains: Humanities & Computational Social Science
• Reasoning under Uncertainty: Causality

Application Category

• User Modeling, Personalization and Recommendation: Studies of user behavior, including longitudinal effects of personalized systems
• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI

Abstract

This paper is the first to provide causal evidence of gender differences in healthcare utilisation to better understand the male-female health-survival paradox, where women live longer but experience worse health outcomes. Using rich Danish administrative healthcare data, we apply a staggered difference-in-differences approach that exploits the randomness in treatment timing to estimate the causal impact of adverse health shocks, such as non-fatal heart attacks or strokes, on healthcare use. Our findings suggest that men consistently use more healthcare than women, highlighting the underlying factors driving gender disparities in health outcomes. These insights contribute to the broader discourse on healthcare equity and inform policy interventions aimed at addressing these imbalances.

Problem

• Causal evidence of gender differences in healthcare utilization
• Understanding male-female health-survival paradox through health shocks
• Investigating factors driving gender disparities in health outcomes

Innovation

• Staggered difference-in-differences causal methodology
• Leveraging Danish administrative healthcare big data
• Exploiting randomness in health shock timing