From test to rest: evaluating socioeconomic differences along the COVID-19 care pathway in the Netherlands

Iris Meulman; Ellen Uiters; Mariëlle Cloin; Jeroen Struijs; Johan Polder; Niek Stadhouders

doi:10.1007/s10198-024-01680-4

From test to rest: evaluating socioeconomic differences along the COVID-19 care pathway in the Netherlands

Eur J Health Econ. 2024 Mar 18. doi: 10.1007/s10198-024-01680-4. Online ahead of print.

Authors

Iris Meulman^{1

2}, Ellen Uiters³, Mariëlle Cloin⁴, Jeroen Struijs^{5

6}, Johan Polder^{4

5}, Niek Stadhouders⁷

Affiliations

¹ Tranzo, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, The Netherlands. iris.meulman@rivm.nl.
² Center for Public Health, Healthcare & Society, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, The Netherlands. iris.meulman@rivm.nl.
³ Center for Prevention, Lifestyle and Health, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
⁴ Tranzo, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, The Netherlands.
⁵ Center for Public Health, Healthcare & Society, National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA, Bilthoven, The Netherlands.
⁶ Department of Public Health and Primary Care, Leiden University Medical Center-Health Campus The Hague, The Hague, The Netherlands.
⁷ Scientific Center for Quality of Healthcare, Radboud University Medical Center, Nijmegen, The Netherlands.

PMID: 38499952
DOI: 10.1007/s10198-024-01680-4

Abstract

Introduction: The COVID-19 pandemic exacerbated healthcare needs and caused excess mortality, especially among lower socioeconomic groups. This study describes the emergence of socioeconomic differences along the COVID-19 pathway of testing, healthcare use and mortality in the Netherlands.

Methodology: This retrospective observational Dutch population-based study combined individual-level registry data from June 2020 to December 2020 on personal socioeconomic characteristics, COVID-19 administered tests, test results, general practitioner (GP) consultations, hospital admissions, Intensive Care Unit (ICU) admissions and mortality. For each outcome measure, relative differences between income groups were estimated using log-link binomial regression models. Furthermore, regression models explained socioeconomic differences in COVID-19 mortality by differences in ICU/hospital admissions, test administration and test results.

Results: Among the Dutch population, the lowest income group had a lower test probability (RR = 0.61) and lower risk of testing positive (RR = 0.77) compared to the highest income group. However, among individuals with at least one administered COVID-19 test, the lowest income group had a higher risk of testing positive (RR = 1.40). The likelihood of hospital admissions and ICU admissions were higher for low income groups (RR = 2.11 and RR = 2.46, respectively). The lowest income group had an almost four times higher risk of dying from COVID-19 (RR = 3.85), which could partly be explained by a higher risk of hospitalization and ICU admission, rather than differences in test administration or result.

Discussion: Our findings indicated that socioeconomic differences became more pronounced at each step of the care pathway, culminating to a large gap in mortality. This underlines the need for enhancing social security and well-being policies and incorporation of health equity in pandemic preparedness plans.

Keywords: COVID-19 healthcare utilization; COVID-19 mortality; COVID-19 testing; Socioeconomic inequality.