BACKGROUND: In Peru, a majority of individuals bypass primary care facilities even for routine services. Efforts to strengthen primary care must be informed by understanding of current practice. We conducted a time motion assessment in primary care facilities in Lima with the goals of assessing the feasibility of this method in an urban health care setting in Latin America and of providing policy makers with empirical evidence on the use of health care provider time in primary care. METHODS: This cross-sectional continuous observation time motion study took place from July - September 2019. We used two-stage sampling to draw a sample of shifts for doctors, nurses, and midwives in primary health facilities and applied the Work Observation Method by Activity Timing tool to capture type and duration of provider activities over a 6-h shift. We summarized time spent on patient care, paper and electronic record-keeping, and non-work (personal and inactive) activities across provider cadres. Observations are weighted by inverse probability of selection. RESULTS: Two hundred seventy-five providers were sampled from 60 facilities; 20% could not be observed due to provider absence (2% schedule error, 8% schedule change, 10% failure to appear). One hundred seventy-four of the 220 identified providers consented (79.1%) and were observed for a total of 898 h of provider time comprising 30,312 unique tasks. Outpatient shifts included substantial time on patient interaction (110, 82, and 130 min for doctors, nurses, and midwives respectively) and on paper records (132, 97, and 141 min) on average. Across all shifts, 1 in 6 h was spent inactive or on personal activities. Two thirds of midwives used computers compared to half of nurses and one third of doctors. CONCLUSIONS: The time motion study is a feasible method to capture primary care operations in Latin American countries and inform health system strengthening. In the case of Lima, absenteeism undermines health worker availability in primary care facilities, and inactive time further erodes health workforce availability. Productive time is divided between patient-facing activities and a substantial burden of paper-based record keeping for clinical and administrative purposes. Electronic health records remain incompletely integrated within routine care, particularly beyond midwifery.
BACKGROUND: Quality of care depends on system, facility, provider, and client-level factors. We aimed at examining structural and process quality of services for sick children and its association with client satisfaction at health facilities in Ethiopia. METHODS: Data from the Ethiopia Service Provision Assessment Plus (SPA+) survey 2014 were used. Measures of quality were assessed based on the Donabedian framework: structure, process, and outcome. A total of 1908 mothers or caretakers were interviewed and their child consultations were observed. Principal component analysis was used to construct quality of care indices including a structural composite score, a process composite score, and a client satisfaction score. Multilevel mixed linear regression was used to analyze the association between structural and process factors with client satisfaction. RESULT: Among children diagnosed with suspected pneumonia, respiratory rate was counted in 56% and temperature was checked in 77% of the cases. A majority of children (92%) diagnosed with fever had their temperature taken. Only 3% of children with fever were either referred or admitted, and 60% received antibiotics. Among children diagnosed with malaria, 51% were assessed for all three Integrated Management of Childhood Illnesses (IMCI) main symptoms, and 4% were assessed for all three general danger signs. Providers assessed dehydration in 54% of children with diarrhea with dehydration, 17% of these children were admitted or referred to another facility, and Oral Rehydration Solution was prescribed for 67% while none received intravenous fluids. The number of basic amenities in the facility was negatively associated with the clients' satisfaction. Private facilities, when the providers had got training for care of sick children in the past 2 years, had higher client satisfaction. There was no statistical association between structure, process composite indicators and client satisfaction. CONCLUSION: The assessment of sick children was of low quality, with many missing procedures when comparing with IMCI guidelines. In spite of this, most clients were satisfied with the services they received. Structural and process composite indicators were not associated with client's satisfaction. These findings highlight the need to assess other dimensions of quality of care besides structure and process that may influence client satisfaction.
INTRODUCTION: Ethiopia successfully reduced mortality in children below 5 years of age during the past few decades, but the utilisation of child health services was still low. Optimising the Health Extension Programme was a 2-year intervention in 26 districts, focusing on community engagement, capacity strengthening of primary care workers and reinforcement of district accountability of child health services. We report the intervention's effectiveness on care utilisation for common childhood illnesses. METHODS: We included a representative sample of 5773 households with 2874 under-five children at baseline (December 2016 to February 2017) and 10 788 households and 5639 under-five children at endline surveys (December 2018 to February 2019) in intervention and comparison areas. Health facilities were also included. We assessed the effect of the intervention using difference-in-differences analyses. RESULTS: There were 31 intervention activities; many were one-off and implemented late. In eight districts, activities were interrupted for 4 months. Care-seeking for any illness in the 2 weeks before the survey for children aged 2-59 months at baseline was 58% (95% CI 47 to 68) in intervention and 49% (95% CI 39 to 60) in comparison areas. At end-line it was 39% (95% CI 32 to 45) in intervention and 34% (95% CI 27 to 41) in comparison areas (difference-in-differences -4 percentage points, adjusted OR 0.49, 95% CI 0.12 to 1.95). The intervention neither had an effect on care-seeking among sick neonates, nor on household participation in community engagement forums, supportive supervision of primary care workers, nor on indicators of district accountability for child health services. CONCLUSION: We found no evidence to suggest that the intervention increased the utilisation of care for sick children. The lack of effect could partly be attributed to the short implementation period of a complex intervention and implementation interruption. Future funding schemes should take into consideration that complex interventions that include behaviour change may need an extended implementation period. TRIAL REGISTRATION NUMBER: ISRCTN12040912.
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.
BACKGROUND: Evidence for the effectiveness of continuous quality improvement (CQI) in resource-poor settings is very limited. We aimed to establish the effects of CQI on quality of antenatal HIV care in primary care clinics in rural South Africa. METHODS AND FINDINGS: We conducted a stepped-wedge cluster-randomised controlled trial (RCT) comparing CQI to usual standard of antenatal care (ANC) in 7 nurse-led, public-sector primary care clinics-combined into 6 clusters-over 8 steps and 19 months. Clusters randomly switched from comparator to intervention on pre-specified dates until all had rolled over to the CQI intervention. Investigators and clusters were blinded to randomisation until 2 weeks prior to each step. The intervention was delivered by trained CQI mentors and included standard CQI tools (process maps, fishbone diagrams, run charts, Plan-Do-Study-Act [PDSA] cycles, and action learning sessions). CQI mentors worked with health workers, including nurses and HIV lay counsellors. The mentors used the standard CQI tools flexibly, tailored to local clinic needs. Health workers were the direct recipients of the intervention, whereas the ultimate beneficiaries were pregnant women attending ANC. Our 2 registered primary endpoints were viral load (VL) monitoring (which is critical for elimination of mother-to-child transmission of HIV [eMTCT] and the health of pregnant women living with HIV) and repeat HIV testing (which is necessary to identify and treat women who seroconvert during pregnancy). All pregnant women who attended their first antenatal visit at one of the 7 study clinics and were ≥18 years old at delivery were eligible for endpoint assessment. We performed intention-to-treat (ITT) analyses using modified Poisson generalised linear mixed effects models. We estimated effect sizes with time-step fixed effects and clinic random effects (Model 1). In separate models, we added a nested random clinic-time step interaction term (Model 2) or individual random effects (Model 3). Between 15 July 2015 and 30 January 2017, 2,160 participants with 13,212 ANC visits (intervention n = 6,877, control n = 6,335) were eligible for ITT analysis. No adverse events were reported. Median age at first booking was 25 years (interquartile range [IQR] 21 to 30), and median parity was 1 (IQR 0 to 2). HIV prevalence was 47% (95% CI 42% to 53%). In Model 1, CQI significantly increased VL monitoring (relative risk [RR] 1.38, 95% CI 1.21 to 1.57, p < 0.001) but did not improve repeat HIV testing (RR 1.00, 95% CI 0.88 to 1.13, p = 0.958). These results remained essentially the same in both Model 2 and Model 3. Limitations of our study include that we did not establish impact beyond the duration of the relatively short study period of 19 months, and that transition steps may have been too short to achieve the full potential impact of the CQI intervention. CONCLUSIONS: We found that CQI can be effective at increasing quality of primary care in rural Africa. Policy makers should consider CQI as a routine intervention to boost quality of primary care in rural African communities. Implementation research should accompany future CQI use to elucidate mechanisms of action and to identify factors supporting long-term success. TRIAL REGISTRATION: This trial is registered at ClinicalTrials.gov under registration number NCT02626351.
BACKGROUND: Accessibility and utilization of antenatal care (ANC) service varies depending on different geographical locations, sociodemographic characteristics, political and other factors. A geographically linked data analysis using population and health facility data is valuable to map ANC use, and identify inequalities in service access and provision. Thus, this study aimed to assess the spatial patterns of ANC use, and to identify associated factors among pregnant women in Ethiopia. METHOD: A secondary data analysis of the 2016 Ethiopia Demographic and Health Survey linked with the 2014 Ethiopian Service Provision Assessment was conducted. A multilevel analysis was carried out using the SAS GLIMMIX procedure. Furthermore, hot spot analysis and spatial regressions were carried out to identify the hot spot areas of and factors associated with the spatial variations in ANC use using ArcGIS and R softwares. RESULTS: A one-unit increase in the mean score of ANC service availability in a typical region was associated with a five-fold increase in the odds of having more ANC visits. Moreover, every one-kilometre increase in distance to the nearest ANC facility in a typical region was negatively associated with having at least four ANC visits. Twenty-five percent of the variability in having at least four ANC visits was accounted for by region of living. The spatial analysis found that the Southern Nations, Nationalities and Peoples region had high clusters of at least four ANC visits. Furthermore, the coefficients of having the first ANC visit during the first trimester were estimated to have spatial variations in the use of at least four ANC visits. CONCLUSION: There were significant variations in the use of ANC services across the different regions of Ethiopia. Region of living and distance were key drivers of ANC use underscoring the need for increased ANC availability, particularly in the cold spot regions.
OBJECTIVES: Recent studies have identified large and systematic deficits in clinical care in low-income countries that are likely to limit health gains. This has focused attention on effectiveness of pre-service education. One approach to assessing this is observation of clinical performance among recent graduates providing care. However, no studies have assessed performance in a standard manner across countries. We analysed clinical performance among recently graduated providers in nine low- or middle-income countries. METHODS: Service Provision Assessments from Haiti, Kenya, Malawi, Namibia, Nepal, Rwanda, Senegal, Tanzania, and Uganda were used. We constructed a Good Medical Practice Index that assesses completion of essential clinical actions using direct observations of care (range 0-1), calculated index scores by country and clinical cadre, and assessed the role of facility and clinical characteristics using regression analysis. RESULTS: Our sample consisted of 2223 clinicians with at least one observation of care. The Good Medical Practice score for the sample was 0.50 (SD = 0.20). Nurses and midwives had the highest score at 0.57 (SD = 0.20), followed by associate clinicians at 0.43 (SD = 0.18), and physicians at 0.42 (SD = 0.16). The average national performance varied from 0.63 (SD = 0.18) in Uganda to 0.39 (SD = 0.17) in Nepal, persisting after adjustment for facility and clinician characteristics. CONCLUSIONS: These results show substantial gaps in clinical performance among recently graduated clinicians, raising concerns about models of clinical education. Competency-based education should be considered to improve quality of care in LMICs. Observations of care offer important insight into the quality of clinical education.
High-performing primary health care (PHC) is essential for achieving universal health coverage. However, in many countries, PHC is weak and unable to deliver on its potential. Improvement is often limited by a lack of actionable data to inform policies and set priorities. To address this gap, the Primary Health Care Performance Initiative (PHCPI) was formed to strengthen measurement of PHC in low-income and middle-income countries in order to accelerate improvement. PHCPI's Vital Signs Profile was designed to provide a comprehensive snapshot of the performance of a country's PHC system, yet quantitative information about PHC systems' capacity to deliver high-quality, effective care was limited by the scarcity of existing data sources and metrics. To systematically measure the capacity of PHC systems, PHCPI developed the PHC Progression Model, a rubric-based mixed-methods assessment tool. The PHC Progression Model is completed through a participatory process by in-country teams and subsequently reviewed by PHCPI to validate results and ensure consistency across countries. In 2018, PHCPI partnered with five countries to pilot the tool and found that it was feasible to implement with fidelity, produced valid results, and was highly acceptable and useful to stakeholders. Pilot results showed that both the participatory assessment process and resulting findings yielded novel and actionable insights into PHC strengths and weaknesses. Based on these positive early results, PHCPI will support expansion of the PHC Progression Model to additional countries to systematically and comprehensively measure PHC system capacity in order to identify and prioritise targeted improvement efforts.
BACKGROUND: Despite the almost universal adoption of Integrated Management of Childhood Illness (IMCI) guidelines for the diagnosis and treatment of sick children under the age of five in low- and middle-income countries, child mortality remains high in many settings. One possible explanation of the continued high mortality burden is lack of compliance with diagnostic and treatment protocols. We test this hypothesis in a sample of children with severe illness in the Democratic Republic of the Congo (DRC). METHODS: One thousand one hundred eighty under-five clinical visits were observed across a regionally representative sample of 321 facilities in the DRC. Based on a detailed list of disease symptoms observed, patients with severe febrile disease (including malaria), severe pneumonia, and severe dehydration were identified. For all three disease categories, treatments were then compared to recommended case management following IMCI guidelines. RESULTS: Out of 1180 under-five consultations observed, 332 patients (28%) had signs of severe febrile disease, 189 patients (16%) had signs of severe pneumonia, and 19 patients (2%) had signs of severe dehydration. Overall, providers gave the IMCI-recommended treatment in 42% of cases of these three severe diseases. Less than 15% of children with severe disease were recommended to receive in-patient care either in the facility they visited or in a higher-level facility. CONCLUSIONS: These results suggest that adherence to IMCI protocols for severe disease remains remarkably low in the DRC. There is a critical need to identify and implement effective approaches for improving the quality of care for severely ill children in settings with high child mortality.
OBJECTIVES: To assess input and process capacity for basic delivery and newborn (intrapartum care hereafter) care in the Indian public health system and to describe differences in facility capacity between rural and urban areas and across states. DESIGN: Cross-sectional study. SETTING: Data from the nationally representative 2012-2014 District Level Household and Facility Survey, which includes a census of community health centres (CHC) and sample of primary health centres (PHC) across 30 states and union territories in India. PARTICIPANTS: 8536 PHCs and 4810 CHCs. OUTCOME MEASURES: We developed a summative index of 33 structural and process capacity items matching the Indian Public Health Standards for PHCs as a metric of minimum facility capacity for intrapartum care. We assessed differences in performance on this index across facility type and location. RESULTS: About 30% of PHCs and 5% of CHCs reported not offering any intrapartum care. Among those offering services, volumes were low: median monthly delivery volume was 8 (IQR=13) in PHCs and 41 (IQR=73) in CHCs. Both PHCs and CHCs failed to meet the national standards for basic intrapartum care capacity. Mean facility capacity was low in PHCs in both urban (0.64) and rural (0.63) areas, while in CHCs, capacity was slightly higher in urban areas (0.77vs0.74). Gaps were most striking in availability of skilled human resources and emergency obstetric services. Poor capacity facilities were more concentrated in the more impoverished states, with 37% of districts from these states receiving scores in the lowest third of the facility capacity index (<0.70), compared with 21% of districts otherwise. CONCLUSIONS: Basic intrapartum care capacity in Indian public primary care facilities is weak in both rural and urban areas, especially lacking in the poorest states with worst health outcomes. Improving maternal and newborn health outcomes will require focused attention to quality measurement, accountability mechanisms and quality improvement. Policies to address deficits in skilled providers and emergency service availability are urgently required.
BACKGROUND: Expanding coverage of primary healthcare services such as antenatal care and vaccinations is a global health priority; however, many Haitians do not utilize these services. One reason may be that the population avoids low quality health facilities. We examined how facility infrastructure and the quality of primary health care service delivery were associated with community utilization of primary health care services in Haiti. METHODS: We constructed two composite measures of quality for all Haitian facilities using the 2013 Service Provision Assessment survey. We geographically linked population clusters from the Demographic and Health Surveys to nearby facilities offering primary health care services. We assessed the cross-sectional association between quality and utilization of four primary care services: antenatal care, postnatal care, vaccinations and sick child care, as well as one more complex service: facility delivery. RESULTS: Facilities performed poorly on both measures of quality, scoring 0.55 and 0.58 out of 1 on infrastructure and service delivery quality respectively. In rural areas, utilization of several primary cares services (antenatal care, postnatal care, and vaccination) was associated with both infrastructure and quality of service delivery, with stronger associations for service delivery. Facility delivery was associated with infrastructure quality, and there was no association for sick child care. In urban areas, care utilization was not associated with either quality measure. CONCLUSIONS: Poor quality of care may deter utilization of beneficial primary health care services in rural areas of Haiti. Improving health service quality may offer an opportunity not only to improve health outcomes for patients, but also to expand coverage of key primary health care services.
BACKGROUND: Despite the substantial attention to primary care (PC), few studies have addressed the relationship between patients' experience with PC and their health status in low-and middle-income countries. This study aimed to (1) test the association between overall patient-centered PC experience (OPCE) and self-rated health (SRH) and (2) identify specific features of patient-centered PC associated with better SRH (i.e., excellent or very good SRH) in 6 Latin American and Caribbean countries. METHODS AND FINDINGS: We conducted a secondary analysis of a 2013 public opinion cross-sectional survey on perceptions and experiences with healthcare systems in Brazil, Colombia, El Salvador, Jamaica, Mexico, and Panama; the data were nationally representative for urban populations. We analyzed 9 features of patient-centered PC. We calculated OPCE score as the arithmetic mean of the PC features. OPCE score ranged from 0 to 1, where 0 meant that the participant did not have any of the 9 patient-centered PC experiences, while 1 meant that he/she reported having all these experiences. After testing for interaction on the additive scale, we analyzed countries pooled for aim 1, with an interaction term for Mexico, and each country separately for aim 2. We used multiple Poisson regression models double-weighted by survey and inverse probability weights to deal with the survey design and missing data. The study included 6,100 participants. The percentage of participants with excellent or very good SRH ranged from 29.5% in Mexico to 52.4% in Jamaica. OPCE was associated with reporting excellent or very good SRH in all countries: adjusting for socio-demographic and health covariates, patients with an OPCE score of 1 in Brazil, Colombia, El Salvador, Jamaica, and Panama were more likely to report excellent or very good SRH than those with a score of 0 (adjusted prevalence ratio [aPR] 1.61, 95% CI 1.37-1.90, p < 0.001); in Mexico, this association was even stronger (aPR 4.27, 95% CI 2.34-7.81, p < 0.001). The specific features of patient-centered PC associated with better SRH differed by country. The perception that PC providers solve most health problems was associated with excellent or very good SRH in Colombia (aPR 1.38, 95% CI 1.01-1.91, p = 0.046) and Jamaica (aPR 1.21, 95% CI 1.02-1.43, p = 0.030). Having a provider who knows relevant medical history was positively associated with better SRH in Mexico (aPR 1.47, 95% CI 1.03-2.12, p = 0.036) but was negatively associated with better SRH in Brazil (aPR 0.71, 95% CI 0.56-0.89, p = 0.003). Finally, easy contact with PC facility (Mexico: aPR 1.35, 95% CI 1.04-1.74, p = 0.023), coordination of care (Mexico: aPR 1.53, 95% CI 1.19-1.98, p = 0.001), and opportunity to ask questions (Brazil: aPR 1.42, 95% CI 1.11-1.83, p = 0.006) were each associated with better SRH. The main study limitation consists in the analysis being of cross-sectional data, which does not allow making causal inferences or identifying the direction of the association between the variables. CONCLUSIONS: Overall, a higher OPCE score was associated with better SRH in these 6 Latin American and Caribbean countries; associations between specific characteristics of patient-centered PC and SRH differed by country. The findings underscore the importance of high-quality, patient-centered PC as a path to improved population health.
Introduction: Measurement of effective coverage (quality-corrected coverage) of essential health services is critical to monitoring progress towards the Sustainable Development Goal for health. We combine facility and household surveys from eight low-income and middle-income countries to examine effective coverage of maternal and child health services. Methods: We developed indices of essential clinical actions for antenatal care, family planning and care for sick children from existing guidelines and used data from direct observations of clinical visits conducted in Haiti, Kenya, Malawi, Namibia, Rwanda, Senegal, Tanzania and Uganda between 2007 and 2015 to measure quality of care delivered. We calculated healthcare coverage for each service from nationally representative household surveys and combined quality with utilisation estimates at the subnational level to quantify effective coverage. Results: Health facility and household surveys yielded over 40 000 direct clinical observations and over 100 000 individual reports of healthcare utilisation. Coverage varied between services, with much greater use of any antenatal care than family planning or sick-child care, as well as within countries. Quality of care was poor, with few regions demonstrating more than 60% average performance of basic clinical practices in any service. Effective coverage across all eight countries averaged 28% for antenatal care, 26% for family planning and 21% for sick-child care. Coverage and quality were not strongly correlated at the subnational level; effective coverage varied by as much as 20% between regions within a country. Conclusion: Effective coverage of three primary care services for women and children in eight countries was substantially lower than crude service coverage due to major deficiencies in care quality. Better performing regions can serve as examples for improvement. Systematic increases in the quality of care delivered-not just utilisation gains-will be necessary to progress towards truly beneficial universal health coverage.