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Global Health Action Volume 13, 2020 - Issue 1
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Research Article

Evaluation of an integrated HIV and hypertension management model in rural South Africa: a mixed methods approach

Soter Ameha Department of Community Medicine, Faculty of Medicine, College of Medical Sciences, University of Calabar, Calabar, Nigeria;b Medical Research Council/Wits University Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa;c Department of Gobal Health and Population, Harvard T. H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USACorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-8449-6423View further author information
ORCID Icon
Article: 1750216 | Received 31 Aug 2019, Accepted 27 Mar 2020, Published online: 22 Apr 2020

Figures & data

Figure 1. Framework for assessing the integrated model for HIV and non-communicable diseases in South Africa. Adapted from the WHO’s innovative care for chronic conditions (ICCC) framework [Citation1]

Figure 1. Framework for assessing the integrated model for HIV and non-communicable diseases in South Africa. Adapted from the WHO’s innovative care for chronic conditions (ICCC) framework [Citation1]

Table 1. The themes and research objectives in the Vunene study

Figure 2. Pathways used to operationalise Avedis Donabedian’s theory of quality of medical care in the intergrated model

Figure 2. Pathways used to operationalise Avedis Donabedian’s theory of quality of medical care in the intergrated model

Figure 3. Map of the agincourt health and socio-demographic surveillance system site

Figure 3. Map of the agincourt health and socio-demographic surveillance system site

Figure 4. A flow chart of sampling of the study participants in the Vunene study

Figure 4. A flow chart of sampling of the study participants in the Vunene study

Figure 5. The domains of care in the integrated model assessed under the structure, process and outcome constructs. NB: The domains in red colour indicate the priority areas of the vertical HIV programme leveraged for chronic disease care in the integrated model

Figure 5. The domains of care in the integrated model assessed under the structure, process and outcome constructs. NB: The domains in red colour indicate the priority areas of the vertical HIV programme leveraged for chronic disease care in the integrated model

Table 2. The socio-demographic characteristics of patients in the ICDM pilot and comparison facilities in the Bushbuckridge municipality

Figure 6. Satisfaction scores of service users and providers with structural domains of care in the integrated model

* Priority domains of care in the integrated model.† Statistically significant differences in the satisfaction scores of service users and providers
Figure 6. Satisfaction scores of service users and providers with structural domains of care in the integrated model

Figure 7. Satisfaction scores of service users and providers with process-related domains of care in the integrated model

* Priority domains of care in the integrated model.† Statistically significant differences in the satisfaction scores of service users and providers
Figure 7. Satisfaction scores of service users and providers with process-related domains of care in the integrated model

Figure 8. Satisfaction scores of service users and providers with outcome-related domains of care in the integrated model

* Priority domains of care in the integrated model.
Figure 8. Satisfaction scores of service users and providers with outcome-related domains of care in the integrated model

Figure 9. Assessment of correlation between structure, process and outcome constructs

* Relationships between the constructs represented by the Pearson correlation valuesNB: The domains in red colour are the priority areas in the integrated model.RMSEA- Root Meon Square Error of Approximation (≤0.06 is a good fit)CFI – Comparative Fit Index (CFI≥ 0.90 is a good fit)TLI – Tucker-Lewis Index (TLI≥ 0.90 is a good fit)CD – Coefficient of determination (range 0–1. There is a perfect fit of the data with the model if CD = 1)Cronbach’s alphac coefficient of reliability (≥0.6 is acceptable)
Figure 9. Assessment of correlation between structure, process and outcome constructs

Table 3. Goodness of fit of the specified pathways used to evaluate the quality of care in the integrated model

Table 4. The autoregressive moving average model for CD4 count in health facilities in the Bushbuckridge municipality from January 2011 to June 2013

Figure 10. Monthly probabilites of controlling CD4 count (>350 cells/mm3) by study groups after propensity score matching

*Dotted gray line shows the month the integrated model was commenced.
Figure 10. Monthly probabilites of controlling CD4 count (>350 cells/mm3) by study groups after propensity score matching

Table 5. The autoregressive moving average model for blood pressure control in health facilities in the Bushbuckridge municipality from January 2011 to June 2013

Figure 11. Monthly probabilites of controlling blood pressure (<140/90 mmHg) by study groups after propensity score matching

*Dotted gray line shows the month the integrated model was commenced.
Figure 11. Monthly probabilites of controlling blood pressure (<140/90 mmHg) by study groups after propensity score matching

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