Impact of ‘Ideal Clinic’ implementation on patient waiting time in primary healthcare clinics in KwaZulu-Natal Province, South Africa: A before-and-after evaluation

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) 81 - 204), compared with 116 minutes (IQR 66 - 168) 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.

Household, community, sub-national and country-level predictors of primary cooking fuel switching in nine countries from the PURE study

Introduction. Switchingfrom polluting (e.g. wood, crop waste, coal)to clean (e.g. gas, electricity) cooking fuels can reduce household air pollution exposures and climate-forcing emissions.While studies have evaluated specific interventions and assessed fuel-switching in repeated cross-sectional surveys, the role of different multilevel factors in household fuel switching, outside of interventions and across diverse community settings, is not well understood. Methods.We examined longitudinal survey data from 24 172 households in 177 rural communities across nine countries within the Prospective Urban and Rural Epidemiology study.We assessed household-level primary cooking fuel switching during a median of 10 years offollow up (∼2005–2015).We used hierarchical logistic regression models to examine the relative importance of household, community, sub-national and national-level factors contributing to primary fuel switching. Results. One-half of study households(12 369)reported changing their primary cookingfuels between baseline andfollow up surveys. Of these, 61% (7582) switchedfrom polluting (wood, dung, agricultural waste, charcoal, coal, kerosene)to clean (gas, electricity)fuels, 26% (3109)switched between different polluting fuels, 10% (1164)switched from clean to polluting fuels and 3% (522)switched between different clean fuels

Impact of ‘Ideal Clinic’ implementation on patient waiting time in primary healthcare clinics in KwaZuluNatal Province South Africa: A beforeandafter evaluation

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) 81 - 204), compared with 116 minutes (IQR 66 - 168) 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.Â

Availability and affordability of blood pressure-lowering medicines and the effect on blood pressure control in high-income, middle-income, and low-income countries: an analysis of the PURE study data

Background: Hypertension is considered the most important risk factor for cardiovascular diseases, but its control is poor worldwide. We aimed to assess the availability and affordability of blood pressure-lowering medicines, and the association with use of these medicines and blood pressure control in countries at varying levels of economic development. Methods: We analysed the availability, costs, and affordability of blood pressure-lowering medicines with data recorded from 626 communities in 20 countries participating in the Prospective Urban Rural Epidemiological (PURE) study. Medicines were considered available if they were present in the local pharmacy when surveyed, and affordable if their combined cost was less than 20% of the households' capacity to pay. We related information about availability and affordability to use of these medicines and blood pressure control with multilevel mixed-effects logistic regression models, and compared results for high-income, upper-middle-income, lower-middle-income, and low-income countries. Data for India are presented separately because it has a large generic pharmaceutical industry and a higher availability of medicines than other countries at the same economic level. Findings: The availability of two or more classes of blood pressure-lowering drugs was lower in low-income and middle-income countries (except for India) than in high-income countries. The proportion of communities with four drug classes available was 94% in high-income countries (108 of 115 communities), 76% in India (68 of 90), 71% in upper-middle-income countries (90 of 126), 47% in lower-middle-income countries (107 of 227), and 13% in low-income countries (nine of 68). The proportion of households unable to afford two blood pressure-lowering medicines was 31% in low-income countries (1069 of 3479 households), 9% in middle-income countries (5602 of 65 471), and less than 1% in high-income countries (44 of 10 880). Participants with known hypertension in communities that had all four drug classes available were more likely to use at least one blood pressure-lowering medicine (adjusted odds ratio [OR] 2·23, 95% CI 1·59–3·12); p<0·0001), combination therapy (1·53, 1·13–2·07; p=0·054), and have their blood pressure controlled (2·06, 1·69–2·50; p<0·0001) than were those in communities where blood pressure-lowering medicines were not available. Participants with known hypertension from households able to afford four blood pressure-lowering drug classes were more likely to use at least one blood pressure-lowering medicine (adjusted OR 1·42, 95% CI 1·25–1·62; p<0·0001), combination therapy (1·26, 1·08–1·47; p=0·0038), and have their blood pressure controlled (1·13, 1·00–1·28; p=0·0562) than were those unable to afford the medicines. Interpretation: A large proportion of communities in low-income and middle-income countries do not have access to more than one blood pressure-lowering medicine and, when available, they are often not affordable. These factors are associated with poor blood pressure control. Ensuring access to affordable blood pressure-lowering medicines is essential for control of hypertension in low-income and middle-income countries. Funding: Population Health Research Institute, the Canadian Institutes of Health Research, Heart and Stroke Foundation of Ontario, Canadian Institutes of Health Research Strategy for Patient Oriented Research through the Ontario SPOR Support Unit, the Ontario Ministry of Health and Long-Term Care, pharmaceutical companies (with major contributions from AstraZeneca [Canada], Sanofi Aventis [France and Canada], Boehringer Ingelheim [Germany amd Canada], Servier, and GlaxoSmithKline), Novartis and King Pharma, and national or local organisations in participating countries