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Predictors of Health Insurance Enrollment among HIV Positive Pregnant Women in Kenya: Potential for Adverse Selection and Implications for HIV Treatment and Prevention

Author

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  • Lawrence P.O. Were

    (Department of Health Sciences, Boston University’s College of Health and Rehabilitation Sciences: Sargent College & Department of Global Health, Boston University School of Public Health, Boston, MA 02215, USA)

  • Joseph W Hogan

    (School of Public Health, Brown University, Providence, RI 02912, USA)

  • Omar Galárraga

    (School of Public Health, Brown University, Providence, RI 02912, USA)

  • Richard Wamai

    (Department of Cultures, Societies and Global Studies, Northeastern University, Boston, MA 02115, USA)

Abstract

Background : The global push to achieve the 90-90-90 targets designed to end the HIV epidemic has called for the removing of policy barriers to prevention and treatment, and ensuring financial sustainability of HIV programs. Universal health insurance is one tool that can be used to this end. In sub-Saharan Africa, where HIV prevalence and incidence remain high, the use of health insurance to provide comprehensive HIV care is limited. This study looked at the factors that best predict social health insurance enrollment among HIV positive pregnant women using data from the Academic Model Providing Access to Healthcare (AMPATH) in western Kenya. Methods : Cross-sectional clinical encounter data were extracted from the electronic medical records (EMR) at AMPATH. We used univariate and multivariate logistic regressions to estimate the predictors of health insurance enrollment among HIV positive pregnant women. The analysis was further stratified by HIV disease severity (based on CD4 cell count <350 and 350>) to test the possibility of differential enrollment given HIV disease state. Results : Approximately 7% of HIV infected women delivering at a healthcare facility had health insurance. HIV positive pregnant women who deliver at a health facility had twice the odds of enrolling in insurance [2.46 Adjusted Odds Ratio (AOR), Confidence Interval (CI) 1.24–4.87]. They were 10 times more likely to have insurance if they were lost to follow-up to HIV care during pregnancy [9.90 AOR; CI 3.42–28.67], and three times more likely to enroll if they sought care at an urban clinic [2.50 AOR; 95% CI 1.53–4.12]. Being on HIV treatment was negatively associated with health insurance enrollment [0.22 AOR; CI 0.10–0.49]. Stratifying the analysis by HIV disease severity while statistically significant did not change these results. Conclusions : The findings indicated that health insurance enrollment among HIV positive pregnant women was low mirroring national levels. Additionally, structural factors, such as access to institutional delivery and location of healthcare facilities, increased the likelihood of health insurance enrollment within this population. However, behavioral aspects, such as being lost to follow-up to HIV care during pregnancy and being on HIV treatment, had an ambiguous effect on insurance enrollment. This may potentially be because of adverse selection and information asymmetries. Further understanding of the relationship between insurance and HIV is needed if health insurance is to be utilized for HIV treatment and prevention in limited resource settings.

Suggested Citation

  • Lawrence P.O. Were & Joseph W Hogan & Omar Galárraga & Richard Wamai, 2020. "Predictors of Health Insurance Enrollment among HIV Positive Pregnant Women in Kenya: Potential for Adverse Selection and Implications for HIV Treatment and Prevention," IJERPH, MDPI, vol. 17(8), pages 1-14, April.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:8:p:2892-:d:348874
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    References listed on IDEAS

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