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. 2023 Sep 18;20(1):279-291.
doi: 10.1515/ijb-2023-0031. eCollection 2024 May 1.

Assessing HIV-infected patient retention in a program of differentiated care in sub-Saharan Africa: a G-estimation approach

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Assessing HIV-infected patient retention in a program of differentiated care in sub-Saharan Africa: a G-estimation approach

Constantin T Yiannoutsos et al. Int J Biostat. .

Abstract

Differentiated care delivery aims to simplify care of people living with HIV, reflect their preferences, reduce burdens on the healthcare system, maintain care quality and preserve resources. However, assessing program effectiveness using observational data is difficult due to confounding by indication and randomized trials may be infeasible. Also, benefits can reach patients directly, through enrollment in the program, and indirectly, by increasing quality of and accessibility to care. Low-risk express care (LREC), the program under evaluation, is a nurse-centered model which assigns patients stable on ART to a nurse every two months and a clinician every third visit, reducing annual clinician visits by two thirds. Study population is comprised of 16,832 subjects from 15 clinics in Kenya. We focus on patient retention in care based on whether the LREC program is available at a clinic and whether the patient is enrolled in LREC. We use G-estimation to assess the effect on retention of two "strategies": (i) program availability but no enrollment; (ii) enrollment at an available program; versus no program availability. Compared to no availability, LREC results in a non-significant increase in patient retention, among patients not enrolled in the program (indirect effect), while enrollment in LREC is associated with a significant extension of the time retained in care (direct effect). G-estimation provides an analytical framework useful to the assessment of similar programs using observational data.

Keywords: G-estimation; HIV/AIDS; observational data; program evaluation.

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Conflict of interest statement

Competing interests: None.

Figures

Figure 1:
Figure 1:
Study data setup.
Figure 2:
Figure 2:
Cumulative incidence of enrollment in LREC after eligibility.
Figure 3:
Figure 3:
Contour plot of chi-square test statistic with two degrees of freedom showing the outer edges of a bivariate 95 % confidence interval.
Figure 4:
Figure 4:
Kaplan–Meier plots of the counterfactual survival time when unexposed to the program throughout the follow-up versus program availability without enrollment or program availability and program enrollment from day one (program eligibility).

References

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