This thesis examines the structure and flow of public funding between the public and private sectors in the South African health system and the consequences thereof for the achievement of equity. The conceptual framework used to undertake the analysis derives from Richard Titmuss’ core theoretical framework, the Social Division of Welfare. The application of the Social Division of Welfare applied to the South African health care context demonstrates how state resources end up benefitting the non-poor and, as a result, reproduce inequality. Those who access public institutions such as public health care are assumed to be ‘dependent’ on the state, whilst those who access private health facilities claim to be ‘independent’ of the state. However, this thesis shows that these assumptions are flawed. Access to the formal labour market, and subsequently the paying of taxes, authorises one to access state subsidies not available to those who do not. The application of the Social Division of Welfare shows that tax-paying private health care patients benefit considerably from state resources. This thesis argues that due to cost escalation in the private health sector, a consequence of the commodification of health care, these private health care ‘consumers’ as well as the private health industry in general are dependent upon state resources. This thesis analyses the role played by the profit motive present in the private health industry and the consequences for equity, quality, access and efficiency in health care provision

The research aimed to pro-activeiy embark in an internal transformation process, in order to improve efficiency of the Social Work Department of Gauteng Medical Command of the South African Military Health Service. Participatory action research as a qualitative research design was- used. The intervention identification process was implemented as a problem-solving technique to direct the process of transformation-change. The research was conducted by a research group often social workers from the South African National Defence Force. The results of the research were the implementation of interventions on identified systems, namely the service delivery system and the performance management system of the Social Work Department of Gauteng Medical Command. The use of particpatorv action research as a process to address problems in an organisation was confirmed. The contribution of the participatory action process to process outcomes, such as empowerment and learning, was also indicated in the findings. / Social Work / MA(SS) (Mental Health)

The research aimed to pro-activeiy embark in an internal transformation process, in order to improve efficiency of the Social Work Department of Gauteng Medical Command of the South African Military Health Service. Participatory action research as a qualitative research design was- used. The intervention identification process was implemented as a problem-solving technique to direct the process of transformation-change. The research was conducted by a research group often social workers from the South African National Defence Force. The results of the research were the implementation of interventions on identified systems, namely the service delivery system and the performance management system of the Social Work Department of Gauteng Medical Command. The use of particpatorv action research as a process to address problems in an organisation was confirmed. The contribution of the participatory action process to process outcomes, such as empowerment and learning, was also indicated in the findings. / Social Work / MA(SS) (Mental Health)

Despite the availability of numerous models for knowledge translation into practice and policy, research uptake remains low in resource-limited countries. This study was aimed at developing a model to facilitate research uptake in healthcare practice and policy development. The study used a two-phase exploratory sequential approach (QUAL→QUAN). Qualitative data were collected through semi-structured interviews with a total of 21 participants, categorised as researchers (6), frontline workers/practitioners (7), programme/policy managers (4), and directors/senior managers (4) from government, private sector and academic institutions of higher learning (universities and colleges). Quantitative data were collected through an online cross-sectional survey, administered to 212 respondents who conducted research studies in the Mpumalanga Province between 2014 to 2019. The most significant findings seem to be lack of awareness of research findings and champions to lead engagements among research stakeholders on research uptake. In addition, the research has established a failure by researchers to align public health research projects to existing local contexts and available resources. Conversely, there is a growing propensity of using informal research without consideration of data quality issues. It was further observed that establishing and sustaining beneficial collaboration between all research stakeholders is required to promote effective research uptake for practice and policy development. The survey results established a total of 13 components: four individual factors (support, experience, motivation & time factor); four organisational factors (research agenda, funding, resources & partnerships), and five research characteristics factors (gatekeeping, local research committees, accessibility of evidence, quality of evidence & critical appraisal skills). However, the Spearman’s correlation coefficient revealed that of the 13 factors, only six factors had a significant positive correlation with research uptake, namely: support, experience, motivation, time factor, resources, and critical appraisal skills. Consequently, a model for institutionalising research uptake is proposed. The roles of local research committees have been clarified, and a logical framework has been incorporated with pathways and channels of engagements to enable successful implementation of the research uptake model. / Health Studies / Ph. D. (Public Health)

Indiana University-Purdue University Indianapolis (IUPUI) / A study design has been developed that employs a dual modeling approach to identify factors associated with facility-level cancer screening improvement and how this is mediated by the use of clinical decision support. This dual modeling approach combines principles of (1) Health Informatics, (2) Cancer Prevention and Control, (3) Health Services Research, and (4) Organizational Change/Theory. The study design builds upon the constructs of a conceptual framework developed by Jane Zapka, namely, (1) organizational and/or practice settings, (2) provider characteristics, and (3) patient population characteristics. These constructs have been operationalized as measures in a 2005 HRSA/NCI Health Disparities Cancer Collaborative inventory of 44 community health centers. The first, statistical models will use: sequential, multivariable regression models to test for the organizational determinants that may account for the presence and intensity-of-use of clinical decision support (CDS) and information systems (IS) within community health centers for use in colorectal, breast, and cervical cancer screening. A subsequent test will assess the impact of CDS/IS on provider reported cancer screening improvement rates. The second, computational models will use a multi-agent model of network evolution called CONSTRUCT® to identify the agents, tasks, knowledge, groups, and beliefs associated with cancer screening practices and CDS/IS use to inform both CDS/IS implementation and cancer screening intervention strategies. This virtual experiment will facilitate hypothesis-generation through computer simulation exercises. The outcome of this research will be to identify barriers and facilitators to improving community health center facility-level cancer screening performance using CDS/IS as an agent of change. Stakeholders for this work include both national and local community health center IT leadership, as well as clinical managers deploying IT strategies to improve cancer screening among vulnerable patient populations.