The Findings Establish the Existence of Disparity in the Covariates Needed to Utilize Healthcare: After Matching These Background Characteristics, Aging Increases Healthcare Utilization by 5.2%
Author(s)
ABSTRACT WITHDRAWN
OBJECTIVES: Ageing reduces health stock which must be replaced through healthcare utilization. The paper investigates the inequality in covariates between aged and not aged persons, and then later assesses the effect of ageing on healthcare utilization and the type of provider, when all covariates are distributed equally between aged and not aged persons.
METHODS: The source of data for the study is the seventh round of the Ghana Living Standards Survey (GLSS 7) which was conducted in 2016/2017 and employs the estimation method of Propensity Score Matching (PSM), within the framework of the Capability Approach.
RESULTS: The findings establish the existence of disparity in the capability set, endowments, and conversion factors needed to utilize healthcare. Compared to not aged persons, aged persons are more likely to earn higher monthly income, and pay more to receive treatment even though they are more likely to have a health insurance. The aged are more likely to be disabled, female, less educated, and live in rural areas. They are also likely to spend less time to travel to the health facility but wait longer hours to receive treatment. After matching these background characteristics, ageing increases healthcare utilization by 5.2%.
CONCLUSIONS: Persons aged 65+ years are more likely to suffer ill-health and are more likely to seek treatment. This is understandable since there is a disparity in the resources and conversion factors needed to utilize healthcare from different providers. However, after matching these background characteristics, just being aged increases healthcare utilization. The paper uses Sen’s Capability Approach Framework.
Conference/Value in Health Info
Code
HSD29
Topic
Health Policy & Regulatory, Health Technology Assessment, Methodological & Statistical Research, Study Approaches
Topic Subcategory
Confounding, Selection Bias Correction, Causal Inference, Decision & Deliberative Processes, Decision Modeling & Simulation, Health Disparities & Equity
Disease
No Additional Disease & Conditions/Specialized Treatment Areas