A novel surveilance framework for tracking and predicting health outcomes of cardiovascular diseases risk factors among people living with HIV initiated on art in Khomas region, Namibia
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Date
2021
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University of Namibia
Abstract
Cardiovascular diseases (CVDs), the leading cause of death in Africa (57%), has recently been recognised as an essential cause of morbidity and mortality among People Living with HIV (PLHIV). Multiple opportunities exist to address the challenges currently encountered with the epidemiological transition and managing the double burden of CVDs and HIV/AIDS. However, there is no documented link between patients’ previous visits to antiretroviral therapy (ART) clinics and subsequent meaningful interpretation and analysis of data in Namibia. Critical data on the leading causes of death, notably, CVDs, injuries, drug and alcohol use, and risk factor exposures are lacking. Therefore, the study’s purpose was to develop a surveillance framework to enhance the tracking and prediction of health outcomes of cardiovascular diseases risks among PLHIV initiated on ART at health facilities in the Khomas region. The researcher adopted a mixed-methods approach which was conducted in four sequential phases during this study. In Phase I, a qualitative approach with phenomenological study design was implemented to explore current data management practices of CVDs risk factors among PLHIV on ART. Thirteen key informants selected purposively were interviewed, and data were analysed with ATLAS.ti. The qualitative findings informed the retrospective, cross-sectional, quantitative data collection process. Risk factors data captured between 2004 until 2017 were extracted from 529 patient care booklets (PCB) and matched with the electronic Patient Monitoring System (ePMS) of sampled PLHIV initiated on ART. These data elements were entered and analysed in SPSS version 25 using descriptive statistics with bivariate and multivariate analysis. Fragmented data management practices for CVDs preventative care among PLHIV initiated on ART were one of the major findings of the study. Phase II involved the process of concept analysis and the development of the conceptual framework based on the findings of Phase I. Schwartz and Kim’s hybrid model of concept development was used to identify and analyse main concepts of enabling environment, sound data management practices, and evidence-based health outcomes. The Population Health Surveillance theory and Donabedian’s model were used as a basis for the development of the conceptual framework. The novel surveillance framework was developed in Phase III. This phase was primarily guided by the outcome of the study findings and Arthur Samuel’s seminal work on the machine learning model of 1959 such as identifying CVDs risk factors; monitoring calculated risks and measuring health outcomes. The framework was evaluated by experts in health, epidemiology, and health informatics to validate its applicability whilst ensuring that the overall study objectives are met. In Phase IV the guidelines to operationalise the framework was developed based on the core elements as listed in Phase III above.
The study concluded that the development of the surveillance framework is effective in enhancing the tracking and prediction of health outcomes of cardiovascular diseases (CVDs) risks among PLHIV initiated on ART in the Khomas region. The study made recommendations for policy and operational level health care workers of the Ministry of Health and Social Services, the public health arena, and future research.
Description
A research dissertation submitted in fulfillment of the requirements for the Degree of Doctor of Public Health