ABSTRACT
BACKGROUND: Long waiting times are a major source of dissatisfaction for patients attending public healthcare facilities in South Africa (SA). The National Department of Health has identified this as one of six priority areas for improvement. Health system-strengthening (HSS) interventions to improve patient waiting time are being implemented in public health facilities across SA as part of the 'Ideal Clinic' model. The effect of these interventions on patient waiting time needs to be assessed and evidence generated for system improvement. OBJECTIVES: To determine the effect of Ideal Clinic HSS intervention on patient waiting time in public health facilities in Amajuba District, KwaZulu-Natal Province, SA. METHODS: We implemented 12 months of HSS activity, including facility reorganisation and patient appointment scheduling. The major outcome of interest was the total time spent by patients in a facility during a visit. This was calculated as the median time spent, obtained through a 'before-and-after' intervention survey. Univariate and multivariate factors associated with waiting time were determined. RESULTS: A total of 1 763 patients from nine clinics were surveyed before and after the intervention (n=860 at baseline and n=903 at follow-up). The median overall waiting time after the intervention was 122 minutes (interquartile range (IQR) 81â-â204), compared with 116 minutes (IQR 66â-â168) before (p<0.05). Individual facility results after the intervention were mixed. Two facilities recorded statistically significant reductions in patient waiting time, while three recorded significant increases (p<0.05). Patient load per nurse, type of service received and time of arrival in facilities were all independently associated with waiting time. Patients' arrival patterns, which were determined by appointment scheduling, played a significant role in the results obtained. CONCLUSIONS: Implementation of the Ideal Clinic model in the selected facilities led to changes in patient waiting time. Observed changes were positive when a clinic appointment system was successfully implemented and negative when this was unsuccessful. We recommend strengthening of the appointment system component of the Ideal Clinic model to improve patient waiting time. Assessing facility waiting time performance in terms of average time spent by patients during a clinic visit was shown to be inadequate, and we suggest the inclusion of 'proportion of clients who spent above the national waiting time threshold during their visit' as a sensitive measure of performance.
ABSTRACT
Background. Cardiovascular diseases (CVDs) are a challenge to populations and health systems worldwide. It is projected that by 2020 about a third of all deaths globally will be caused by CVDs; and that they will become the single leading cause of death by 2030. Empirical evidence suggests that there is socioeconomic patterning in the distribution and prevalence of risk factors for CVD; but the exact nature of this relationship in South Africa remains unclear. Objective. To examine the association between socioeconomic status (SES) and risk factors for CVD in a cohort of adult South Africans living in rural and urban communities.Method. This was a cross-sectional analytical study of baseline data on a population-based cohort of 1 976 SA men and women aged 35 - 70 years who were part of the Cape Town arm of the Prospective Urban and Rural Epidemiology (PURE) Study.Results. We found a complex association between SES and CVD risk factors; its pattern differing between urban and rural participants. Marital status showed the most consistent association with CVD risk in both groups: widowed participants living in urban communities were more likely to be hypertensive as well as diabetic; while single participants in both locations were more likely to use alcohol and tobacco products. Level of education was the only SES variable that had no significant association with any CVD risk factor in either study group. All measured SES variables were significantly different between urban and rural participants (p0.05); with diabetes; obesity and alcohol use significantly more prevalent in urban than in rural participants (p0.05) while hypertension and tobacco use were not (p?0.05). Conclusions. In this cohort of South Africans; there were significant associations between SES and CVD risk; with marked differences in these associations between rural and urban locations. These findings highlight the need to consider SES and area of residence when designing interventions for CVD prevention and control
