Predictors of Health Care Service Quality among Women Insured Under Ghana’s National Health Insurance Scheme

Background: Insured women in Ghana are more likely to use maternity care services than their uninsured counterparts. To improve service quality among insured women in Ghana, better understanding of the factors that predict quality standards of primary health care services is essential. Objective: To...

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Bibliographic Details
Main Authors: Martin Amogre Ayanore, Richard Ofori-Asenso, Amos Laar
Format: Article
Language:English
Published: Levy Library Press 2018-11-01
Series:Annals of Global Health
Online Access:https://annalsofglobalhealth.org/articles/2371
Description
Summary:Background: Insured women in Ghana are more likely to use maternity care services than their uninsured counterparts. To improve service quality among insured women in Ghana, better understanding of the factors that predict quality standards of primary health care services is essential. Objective: To examine predictors of health care service quality among insured women under the National Health Insurance Scheme (NHIS) in Ghana. Methods: Data from the 2014 Ghana Demographic Health Survey was analysed. Cluster analysis was applied to construct a dependent variable; service care quality. Socio-demographic/background characteristics were used as independent variables. Descriptive and inferential analyses were performed followed by multiple regression to predict service quality among the insured population of women aged 15–49 years. SPSS version 21 was used during the clustering while STATA version 14 was used to perform the inferential and regression analyses. Findings: Overall, geographical region of respondents was significant to expressions of insured service quality (χ2=495.4, p ≤ 0.001). Literacy levels were significant at χ2=69.232 and p ≤ 0.001 for service quality. On place of residence, the estimation show urban residency was more positively correlated with indicating quality ratings of health services compared to rural residency (χ2=70.29, p ≤ 0.001). Highest educational level had the highest predictive influence with a coefficient of 0.15. Conclusions:A more supportive health insurance system approach that shifts towards introducing valued-based care models for patients, insurers and health care providers could be supportive in improving quality standards among insured population groups in Ghana.
ISSN:2214-9996