Factors affecting health-care seeking behaviour, and assessment of the population's perception of the major health problems in Gauteng province, South Africa 2013

A research report submitted to the Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, in partial fulfillment of the requirements for the degree of Master of Science in Epidemiology. Johannesburg, June 2016Background: More than a billion people, mainly in low- and middle-income countries (LMICs), are unable to access needed health care services for a variety of reasons. Possible factors influencing health-care seeking behaviour are socio-demographic and economic factors such as age, sex, ethnicity, religion, education and employment; and income and expenditure levels, and other cultural or political factors. There are limited studies on health-care seeking behaviour especially of vulnerable populations such as immigrants in South Africa. Aim of the study: To assess factors associated with health care seeking behaviour, and to assess the population’s perception of major health problems and its determinants in Gauteng Province, South Africa in 2013. Methods: We conducted secondary data analysis of data from a Quality of Life (QoL) survey carried out by Gauteng City-Region Observatory (GCRO) to determine factors associated with health care seeking behaviour and perception of major health problems among adults living in Gauteng province. We used Coarsened Exact matching (CEM) to improve estimation of causal effects. A multiple logistic regression model was used to identify factors associated with health care seeking behaviour and multinomial logistic regression was employed to determine factors associated with perception of major health problems. Results: From a total of 27 490 participants interviewed, a total of 26 318 (95.7%) participants reported usually utilizing health care services while the remaining 4.3% reported not having sought health care services of any type, when they needed. In addition 141 (0.5%) reported having visited traditional healers when they are ill. Higher odds of reported health care seeking was associated with being white compared to being African (Odds Ratio (OR) =2.28 95% CI: 1.84 - 2.74; p<0.001); with having medical insurance compared to not having any (OR=5.41 95% CI: 4.06 - 7.23; p<0.001). In contrast, lower odds of seeking health care was associated with being an immigrant compared to being a citizen of Republic of South Africa (OR=0.61 95% CI: 0.53 - 0.70; p<0.001) and being employed compared to being unemployed (OR=0.84 95% CI: 0.72 - 0.97; p=0.02). the perception of major health problems was significantly associated with age, sex, population group and educational status. Conclusion: Age and sex of participants, population group, immigration status and presence/absence of health insurance were associated with health care seeking behaviour. There is a need to improve the quality of public health care services and perception towards them as improved IV health care quality increases the choice of health care provider relative to either going to traditional healers or self-treatment. Furthermore, health education and health promotion campaigns should focus on creating continuous awareness especially about chronic diseases and their risk factors.MB201

Health-care utilization and associated factors in Gauteng province, South Africa

Background: More than a billion people, mainly in low- and middle-income countries, are unable to access needed health-care services for a variety of reasons. Possible factors influencing health-care utilization include socio-demographic and economic factors such as age, sex, education, employment and income. However, different studies have showed mixed results. Moreover, there are limited studies on health-care utilization. Objective: This study aimed to determine health-care utilization and associated factors among all residents aged 18 or over in Gauteng province, South Africa. Methods: A cross-sectional study was conducted from data collected for a Quality of Life survey which was carried out by Gauteng City-Region Observatory in 2013. Simple random sampling was used to select participants. A total of 27,490 participants have been interviewed. Data were collected via a digital data collection instrument using an open source system called Formhub. Coarsened Exact Matching (CEM) was used to improve estimation of causal effects. Stepwise multiple logistic regression was employed to identify factors associated with health-care utilization. Results: Around 95.7% reported usually utilizing health-care services while the other 4.3% reported not having sought health-care services of any type. Around 75% of participants reported reduced quality of public health services as a major reason not to visit them. Higher odds of reported health-care utilization were associated with being female (OR = 2.18, 95% CI: 1.88–2.53; p < 0.001), being White compared to being African (OR = 2.28, 95% CI: 1.84–2.74; p < 0.001), and having medical insurance (OR = 5.41, 95% CI: 4.06–7.23; p < 0.001). Lower odds of seeking health-care were associated with being an immigrant (OR = 0.61, 95% CI: 0.53–0.70; p < 0.001). Conclusions: The results indicated that there is a need to improve the quality of public health-care services and perception towards them as improved health-care quality increases the choice of health-care providers

Predictors of pediatric tuberculosis in public health facilities of Bale zone, Oromia region, Ethiopia: a case control study

Abstract Background Tuberculosis is among the top ten cause of death (9th) from a single infectious agent worldwide. It even ranks above HIV/AIDS. It is among the top 10 causes of death among children. Globally there are estimates of one million cases of TB in children, 76% occur in 22 high-burden countries among which Ethiopia ranked 8th. Despite this fact, children with TB are given low priority in most national health programs. Moreover reports on childhood TB and its predictors are very limited. Therefore this study aimed to assess predictors of pediatric Tuberculosis in Public Health Facilities. Methods Unmatched case control study among a total samples of 432 (144 cases and 288 controls) were done from August to December 2016 in Bale zone, South East Ethiopia. Pediatric TB patients who attended health facilities for DOTS and those who attended health facilities providing DOTS service for any health problem except for TB were the study population for cases and controls, respectively. For each case two consecutive controls were sampled systematically. Data were collected using pretested and structured questionnaire through face to face interview with parents. Binary and multivariable logistic regression analyses were employed to identify predictors of Tuberculosis. Result Among cases there were equal number of male and female 71(50%). However among control 136 (47.9%) were male and the rest were female. The mean (standard deviation) of age among cases was 8.4 (±4.3) and controls were 7.3 (±4.1). The odds of TB were 2 times (AOR, 95% CI = 1.94(1.02–3.77)) more likely among 11–15 age group children when compared with children of age group ≤5. HIV status of the child, children who were fed raw milk and absence of BCG vaccination were the other predictors of pediatric TB with AOR 13.6(3.45–53.69), 4.23(2.26–7.88), and 5.46(1.82–16.32) respectively. Conclusion Children who were not BCG Vaccinated were at risk of developing TB. Furthermore, HIV status, age of the child and family practice of feeding children raw milk are the independent predicators of pediatric TB in the study area

Barriers to healthcare data quality and recommendations in public health facilities in Dire Dawa city administration, eastern Ethiopia: a qualitative study

BackgroundMaintaining good quality of healthcare data at various levels is a critical challenge in developing countries. The barriers to healthcare data quality remain largely unexplored in eastern Ethiopia.ObjectiveThis study aimed to assess the barriers to quality of healthcare data in urban public health facilities in the Dire Dawa city administration from 7 April to 7 May 2019.MethodsAn institutional-based qualitative exploratory approach was used among 17 purposefully selected key informants. In-depth interviews were inductively coded using the ATLAS.ti 7.5.4 version software. Inductive analysis was used by semantically analyzing the explicit content of the data to determine our themes.ResultsSeveral key themes and subthemes with different barriers, some of which are mutually non-exclusive, were identified. These include: Organizational Barriers: Lack of an adequate health management information system and data clerk staff, poor management commitment, lack of post-training follow-up, work overload, frequent duty rotation, lack of incentives for good performers, lack of targeted feedback, and poor culture of information use. Behavioral/Individual Barriers: Gaps in the skill of managers and health professionals, lack of adequate awareness of each indicator and its definitions, inadequate educational competence, lack of feeling of ownership, poor commitment, lack of daily tallying, and lack of value for data. Technical Barriers: Lack of a standard form, diverse and too many data entry formats, manual data collection, shortage of supplies, failure to repair system break down in a timely manner, interruption in electricity and network, delay in digitizing health information systems, lack of post-training follow-up, and inadequate supervision. External Barriers: Poor collaboration between stakeholders, dependence on the software program of non-governmental organizations, and very hot weather conditions.ConclusionDiverse and complex barriers to maintenance of data quality were identified. Developing standardized health management information system implementation plans, providing advanced supervisory-level training, supportive supervision, and site-level mentorship may be very effective in identifying and resolving bottleneck data quality issues. Healthcare managers should understand the imperative of data quality and accept responsibility for its improvement and maintenance. Interventions targeted only at supplies will not fully overcome limitations to data quality. Motivation of staff and recognition of best performance can motivate others and can create cooperation among staff