Hospital-provision of essential primary care in 56 countries: determinants and quality.

OBJECTIVE: To estimate the use of hospitals for four essential primary care services offered in health centres in low- and middle-income countries and to explore differences in quality between hospitals and health centres. METHODS: We extracted data from all demographic and health surveys conducted since 2010 on the type of facilities used for obtaining contraceptives, routine antenatal care and care for minor childhood diarrhoea and cough or fever. Using mixed-effects logistic regression models we assessed associations between hospital use and individual and country-level covariates. We assessed competence of care based on the receipt of essential clinical actions during visits. We also analysed three indicators of user experience from countries with available service provision assessment survey data. FINDINGS: On average across 56 countries, public hospitals were used as the sole source of care by 16.9% of 126 012 women who obtained contraceptives, 23.1% of 418 236 women who received routine antenatal care, 19.9% of 47 677 children with diarrhoea and 18.5% of 82 082 children with fever or cough. Hospital use was more common in richer countries with higher expenditures on health per capita and among urban residents and wealthier, better-educated women. Antenatal care quality was higher in hospitals in 44 countries. In a subset of eight countries, people using hospitals tended to spend more, report more problems and be somewhat less satisfied with the care received. CONCLUSION: As countries work towards achieving ambitious health goals, they will need to assess care quality and user preferences to deliver effective primary care services that people want to use.

Assessment of health facility quality improvements, United Republic of Tanzania.

OBJECTIVE: To identify contextual factors associated with quality improvements in primary health-care facilities in the United Republic of Tanzania between two star rating assessments, focusing on local district administration and proximity to other facilities. METHODS: Facilities underwent star rating assessments in 2015 and between 2017 and 2018; quality was rated from zero to five stars. The consolidated framework for implementation research, adapted to a low-income context, was used to identify variables associated with star rating improvements between assessments. Facility data were obtained from several secondary sources. The proportion of the variance in facility improvement observed at facility and district levels and the influence of nearby facilities and district administration were estimated using multilevel regression models and a hierarchical spatial autoregressive model, respectively. FINDINGS: Star ratings improved at 4028 of 5595 (72%) primary care facilities. Factors associated with improvement included: (i) star rating in 2015; (ii) facility type (e.g. hospital) and ownership (e.g. public); (iii) participation in, or eligibility for, a results-based financing programme; (iv) local population density; and (v) distance from a major road. Overall, 20% of the variance in facility improvement was associated with district administration. Geographical clustering indicated that improvement at a facility was also associated with improvements at nearby facilities. CONCLUSION: Although the majority of facilities improved their star rating, there were substantial variations between facilities. Both district administration and proximity to high-performing facilities influenced improvements. Quality improvement interventions should take advantage of factors operating above the facility level, such as peer learning and peer pressure.

Expectations of healthcare quality: A cross-sectional study of internet users in 12 low- and middle-income countries.

BACKGROUND: High satisfaction with healthcare is common in low- and middle-income countries (LMICs), despite widespread quality deficits. This may be due to low expectations because people lack knowledge about what constitutes good quality or are resigned about the quality of available services. METHODS AND FINDINGS: We fielded an internet survey in Argentina, China, Ghana, India, Indonesia, Kenya, Lebanon, Mexico, Morocco, Nigeria, Senegal, and South Africa in 2017 (N = 17,996). It included vignettes describing poor-quality services-inadequate technical or interpersonal care-for 2 conditions. After applying population weights, most of our respondents lived in urban areas (59%), had finished primary school (55%), and were under the age of 50 (75%). Just over half were men (51%), and the vast majority reported that they were in good health (73%). Over half (53%) of our study population rated the quality of vignettes describing poor-quality services as good or better. We used multilevel logistic regression and found that good ratings were associated with less education (no formal schooling versus university education; adjusted odds ratio [AOR] 2.22, 95% CI 1.90-2.59, P < 0.001), better self-reported health (excellent versus poor health; AOR 5.19, 95% CI 4.33-6.21, P < 0.001), history of discrimination in healthcare (AOR 1.47, 95% CI 1.36-1.57, P < 0.001), and male gender (AOR 1.32, 95% CI 1.23-1.41, P < 0.001). The survey did not reach nonusers of the internet thus only representing the internet-using population. CONCLUSIONS: Majorities of the internet-using public in 12 LMICs have low expectations of healthcare quality as evidenced by high ratings given to poor-quality care. Low expectations of health services likely dampen demand for quality, reduce pressure on systems to deliver quality care, and inflate satisfaction ratings. Policies and interventions to raise people's expectations of the quality of healthcare they receive should be considered in health system quality reforms.

Status of countrywide laboratory services quality and capacity in primary healthcare facilities in Tanzania: Findings from Star Rating Assessment.

Accurate disease diagnosis relies on a well-organized and reliable laboratory system. This study assesses the quality of laboratory services in Tanzania based on the nationwide Star Rating Assessment (SRA) of Primary Healthcare (PHC) facilities conducted in 2017/18. This cross-sectional study utilized secondary data from all the country's PHC facilities stored in the SRA database. Laboratory service quality was assessed by aggregating scores as percentages of the maximum achievable score across various indicators: dedicated laboratory department/room, adequate equipment, staffing levels, adherence to testing protocols, establishment of turnaround times, internal and external quality controls, and safety and supplies management. Scores equal to or exceeding 80% were deemed compliant. Multiple linear regression was used to determine the influence of facility characteristics (level, ownership, location, staffing) on quality scores, with statistical significance set at p < 0.05. The study included 6,663 PHC facilities (85.9% dispensaries, 11% health centers, 3.2% hospital-level-1), with the majority being public (82.3% vs. 17.7%) and located in rural areas (77.1% vs. 22.9%). On average, facilities scored 30.8% (SD = 35.7), and only 26.6% met staffing requirements. Compliance with quality standards was higher in private (63% vs. 19%, p<0.001) and urban facilities (62% vs. 16%, p<0.001). More than half of the facilities did not meet either of the eight quality indicators. Quality was positively linked to staffing compliance (Beta = 5.770) but negatively impacted by dispensaries (Beta = -6.342), rural locations (Beta = -0.945), and public ownership (Beta = -1.459). A score of 30% falls significantly short of the national target of 80%. Improving laboratory staffing levels at PHC facilities could improve the quality of laboratory services, especially in public facilities that are based in rural areas. There is a need to further strengthen laboratory services in PHC facilities to ensure the quality of laboratory services and clients' satisfaction.

Clients satisfaction at primary healthcare facilities and its association with implementation of client service charter in Tanzania.

BACKGROUND: Client service charter (CSC) provides information about what people can expect in a facility's services; what is expected of clients and service providers. Tanzania implemented Star Rating Assessment (SRA) of primary health care (PHC) facilities in 2015/16 and 2017/18 using SRA tools with 12 service areas. This paper assesses the status of service area 7, namely client focus that checked if client was satisfied with services provided and implementation of CSC through three indicators-if: CSC was displayed; CSC was monitored; client feedback mechanism and complaints handling was in place. METHODS: We extracted and performed a cross-sectional secondary data analysis of data related to clients' focus that are found in national SRA database of 2017/2018 using STATA version 15. Client satisfaction was regarded as dependent variable while facility characteristics plus three indicators of CSC as independent variables. Multivariate logistic regression with p-value of 5% and 95% confidence interval (CI) were applied. RESULTS: A total of 4,523 facilities met our inclusion criteria; 3,987 (88.2%) were dispensaries, 408 (9.0%) health centres and 128 (2.8%) hospitals. CSC was displayed in 69.1% facilities, monitored in 32.4% facilities, and 32.5% of the facilities had mechanisms for clients' feedback and handling complaints. The overall prevalence of clients' satisfaction was 72.8%. Clients' satisfaction was strongly associated with all implementation indicators of CSC. Clients from urban-based facilities had 21% increased satisfaction compared rural-based facilities (AOR 1.21; 95%CI: 1.00-1.46); and clients from hospitals had 39% increased satisfaction compared to dispensaries (AOR 1.39; 95%CI: 1.10-1.77). CONCLUSION: The implementation of CSC is low among Tanzanian PHC facilities. Clients are more satisfied if received healthcare services from facilities that display the charter, monitor its implementation, have mechanisms to obtain clients feedback and handle complaints. Clients' satisfaction at PHC could be improved through adoption and implementation of CSC.

Social accountability in primary health care facilities in Tanzania: Results from Star Rating Assessment.

BACKGROUND: Star Rating Assessment (SRA) was initiated in 2015 in Tanzania aiming at improving the quality of services provided in Primary Healthcare (PHC) facilities. Social accountability (SA) is among the 12 assessment areas of SRA tools. We aimed to assess the SA performance and its predictors among PHC facilities in Tanzania based on findings of a nationwide reassessment conducted in 2017/18. METHODS: We used the SRA database with results of 2017/2018 to perform a cross-sectional secondary data analysis on SA dataset. We used proportions to determine the performance of the following five SA indicators: functional committees/boards, display of information on available resources, addressing local concerns, health workers' engagement with local community, and involvement of community in facility planning process. A facility needed four indicators to be qualified as socially accountable. Adjusted odds ratios (AOR) with 95% confidence intervals (CI) were used to determine facilities characteristics associated with SA, namely location (urban or rural), ownership (private or public) and level of service (hospital, health centre or dispensary). RESULTS: We included a total of 3,032 PHC facilities of which majority were dispensaries (86.4%), public-owned (76.3%), and located in rural areas (76.0%). On average, 30.4% of the facilities were socially accountable; 72.0% engaged with local communities; and 65.5% involved communities in facility planning process. Nevertheless, as few as 22.5% had functional Health Committees/Boards. A facility was likely to be socially-accountable if public-owned [AOR 5.92; CI: 4.48-7.82, p = 0.001], based in urban areas [AOR 1.25; 95% CI: 1.01-1.53, p = 0.038] or operates at a level higher than Dispensaries (Health centre or Hospital levels). CONCLUSION: Most of the Tanzanian PHC facilities are not socially accountable and therefore much effort in improving the situation should be done. The efforts should target the lower-level facilities, private-owned and rural-based PHC facilities. Regional authorities must capacitate facility committees/boards and ensure guidelines on SA are followed.

Status of Infection Prevention and Control in Tanzanian Primary Health Care Facilities: Learning From Star Rating Assessment.

BACKGROUND: The WHO estimates 10-30% of hospital admissions are associated with poor infection prevention and control (IPC). There are no reliable data on IPC status in Tanzanian healthcare facilities; hence the Star Rating Assessment (SRA) was established to address this. This study compared the health facility performances on adherence to IPC principles using baseline and reassessment data of SRA. METHODS: A retrospective analysis of data from eight randomly selected regions across Tanzania. Data was gathered from an SRA database in which records of baseline assessments (2015/16) and reassessments (2017/18) were documented. Each healthcare facility's ownership and service level were investigated as independent variables. RESULTS: A total of 2,131 healthcare facilities at baseline and 2,185 at reassessment were analysed. Median adherence to IPC principles increased from 31% (IQR: 20%, 46%) to 57% (IQR: 41.4%, 73.2%) after interventions (p<0.001).Privately-owned facilities had higher adherence to IPC principles compared to publicly-owned facilities during baseline (p<0.001) however, the difference was not significant after intervention (p=0.751). On average, hospitals scored highest followed by health centres and then dispensaries during both assessments.Being a privately-owned facility was a predictor of attaining a recommended IPC score of 80% at baseline (POR=1.92 CI=1.06-3.48) but not after the intervention. Facility level was not a predictor during baseline assessment; however after intervention hospitals were twice as likely to attain the recommended score compared to dispensaries (POR=2.27 CI=1.15-4.45). CONCLUSION: Assessment and rating of quality and organization of health services plus management support to healthcare facilities, leads to improved adherence to IPC principles.

Level of confidence in and endorsement of the health system among internet users in 12 low-income and middle-income countries.

INTRODUCTION: People's confidence in and endorsement of the health system are key measures of system performance, yet are undermeasured in low-income and middle-income countries (LMICs). We explored the prevalence and predictors of these measures in 12 countries. METHODS: We conducted an internet survey in Argentina, China, Ghana, India, Indonesia, Kenya, Lebanon, Mexico, Morocco, Nigeria, Senegal and South Africa collecting demographics, ratings of quality, and confidence in and endorsement of the health system. We used multivariable logistic regression to assess the association between confidence/endorsement and self-reported quality of recent healthcare. RESULTS: Of 13 489 respondents, 62% reported a health visit in the past year. Applying population weights, 32% of these users were very confident that they could receive effective care if they were to 'become very sick tomorrow'; 30% endorsed the health system, that is, agreed that it 'works pretty well and only needs minor changes'. Reporting high quality in the last visit was associated with 4.48 and 2.69 greater odds of confidence (95% CI 3.64 to 5.52) and endorsement (95% CI 2.33 to 3.11). Having health insurance was positively associated with confidence and endorsement (adjusted odds ratio (AOR) 1.68, 95% CI 1.49 to 1.90 and AOR 1.34, 95% CI 1.22 to 1.48), while experiencing discrimination in healthcare was negatively associated (AOR 0.67, 95% CI 0.56 to 0.80 and AOR 0.63, 95% CI 0.53 to 0.76). CONCLUSION: Confidence and endorsement of the health system were low across 12 LMICs. This may hinder efforts to gain support for universal health coverage. Positive patient experience was strongly associated with confidence in and endorsement of the health system.

In Low- And Middle-Income Countries, Is Delivery In High-Quality Obstetric Facilities Geographically Feasible?

Delivery in a health facility is a key strategy for reducing maternal and neonatal mortality, yet increasing use of facilities has not consistently translated into reduced mortality in low- and middle-income countries. In such countries, many deliveries occur at primary care facilities, where the quality of care is poor. We modeled the geographic feasibility of service delivery redesign that shifted deliveries from primary care clinics to hospitals in six countries: Haiti, Kenya, Malawi, Namibia, Nepal, and Tanzania. We estimated the proportion of women within two hours of the nearest delivery facility, both currently and under redesign. Today, 83-100 percent of pregnant women in the study countries have two-hour access to a delivery facility. A policy of redesign would reduce two-hour access by at most 10 percent, ranging from 0.6 percent in Malawi to 9.9 percent in Tanzania. Relocating delivery services to hospitals would not unduly impede geographic access to care in the study countries. This policy should be considered in low- and middle-income countries, as it may be an effective approach to reducing maternal and newborn deaths.