Quality of routine health data at the onset of the COVID-19 pandemic in Ethiopia, Haiti, Laos, Nepal, and South Africa.

BACKGROUND: During the COVID-19 pandemic, governments and researchers have used routine health data to estimate potential declines in the delivery and uptake of essential health services. This research relies on the data being high quality and, crucially, on the data quality not changing because of the pandemic. In this paper, we investigated those assumptions and assessed data quality before and during COVID-19. METHODS: We obtained routine health data from the DHIS2 platforms in Ethiopia, Haiti, Lao People's Democratic Republic, Nepal, and South Africa (KwaZulu-Natal province) for a range of 40 indicators on essential health services and institutional deaths. We extracted data over 24 months (January 2019-December 2020) including pre-pandemic data and the first 9 months of the pandemic. We assessed four dimensions of data quality: reporting completeness, presence of outliers, internal consistency, and external consistency. RESULTS: We found high reporting completeness across countries and services and few declines in reporting at the onset of the pandemic. Positive outliers represented fewer than 1% of facility-month observations across services. Assessment of internal consistency across vaccine indicators found similar reporting of vaccines in all countries. Comparing cesarean section rates in the HMIS to those from population-representative surveys, we found high external consistency in all countries analyzed. CONCLUSIONS: While efforts remain to improve the quality of these data, our results show that several indicators in the HMIS can be reliably used to monitor service provision over time in these five countries.

Tracking health system performance in times of crisis using routine health data: lessons learned from a multicountry consortium.

COVID-19 has prompted the use of readily available administrative data to track health system performance in times of crisis and to monitor disruptions in essential healthcare services. In this commentary we describe our experience working with these data and lessons learned across countries. Since April 2020, the Quality Evidence for Health System Transformation (QuEST) network has used administrative data and routine health information systems (RHIS) to assess health system performance during COVID-19 in Chile, Ethiopia, Ghana, Haiti, Lao People's Democratic Republic, Mexico, Nepal, South Africa, Republic of Korea and Thailand. We compiled a large set of indicators related to common health conditions for the purpose of multicountry comparisons. The study compiled 73 indicators. A total of 43% of the indicators compiled pertained to reproductive, maternal, newborn and child health (RMNCH). Only 12% of the indicators were related to hypertension, diabetes or cancer care. We also found few indicators related to mental health services and outcomes within these data systems. Moreover, 72% of the indicators compiled were related to volume of services delivered, 18% to health outcomes and only 10% to the quality of processes of care. While several datasets were complete or near-complete censuses of all health facilities in the country, others excluded some facility types or population groups. In some countries, RHIS did not capture services delivered through non-visit or nonconventional care during COVID-19, such as telemedicine. We propose the following recommendations to improve the analysis of administrative and RHIS data to track health system performance in times of crisis: ensure the scope of health conditions covered is aligned with the burden of disease, increase the number of indicators related to quality of care and health outcomes; incorporate data on nonconventional care such as telehealth; continue improving data quality and expand reporting from private sector facilities; move towards collecting patient-level data through electronic health records to facilitate quality-of-care assessment and equity analyses; implement more resilient and standardized health information technologies; reduce delays and loosen restrictions for researchers to access the data; complement routine data with patient-reported data; and employ mixed methods to better understand the underlying causes of service disruptions.

Service delivery reform for maternal and newborn health in Kakamega County, Kenya: study protocol for a prospective impact evaluation and implementation science study.

BACKGROUND: Maternal and neonatal mortality remain elevated in low and middle income countries, and progress is slower than needed to achieve the Sustainable Development Goals. Existing strategies appear to be insufficient. One proposed alternative strategy, Service Delivery Redesign for Maternal and Neonatal Health (SDR), centers on strengthening higher level health facilities to provide rapid, definitive care in case of delivery and post-natal complications, and then promoting delivery in these hospitals, rather than in primary care facilities. However to date, SDR has not been piloted or evaluated. METHODS: We will use a prospective, non-randomized stepped-wedge design to evaluate the effectiveness and implementation of Service Delivery Redesign for Maternal and Neonatal Health in Kakamega County, Kenya. DISCUSSION: This protocol describes a hybrid effectiveness/implementation evaluation study with an adaptive design. The impact evaluation ("effectiveness") study focuses on maternal and newborn health outcomes, and will be accompanied by an implementation evaluation focused on program reach, adoption, and fidelity.

Hospital delivery and neonatal mortality in 37 countries in sub-Saharan Africa and South Asia: An ecological study.

BACKGROUND: Widespread increases in facility delivery have not substantially reduced neonatal mortality in sub-Saharan Africa and South Asia over the past 2 decades. This may be due to poor quality care available in widely used primary care clinics. In this study, we examine the association between hospital delivery and neonatal mortality. METHODS AND FINDINGS: We used an ecological study design to assess cross-sectional associations between the share of hospital delivery and neonatal mortality across country regions. Data were from the Demographic and Health Surveys from 2009 to 2018, covering 682,239 births across all regions. We assess the association between the share of facility births in a region that occurred in hospitals (versus lower-level clinics) and early (0 to 7 days) neonatal mortality per 1,000 births, controlling for potential confounders including the share of facility births, small at birth, maternal age, maternal education, urbanicity, antenatal care visits, income, region, and survey year. We examined changes in this association in different contexts of country income, global region, and urbanicity using interaction models. Across the 1,143 regions from 37 countries in sub-Saharan Africa and South Asia, 42%, 29%, and 28% of births took place in a hospital, clinic, and at home, respectively. A 10-percentage point higher share of facility deliveries occurring in hospitals was associated with 1.2 per 1,000 fewer deaths (p-value < 0.01; 95% CI: 0.82 to 1.60), relative to mean mortality of 22. Associations were strongest in South Asian countries, middle-income countries, and urban regions. The study's limitations include the inability to control for all confounding factors given the ecological and cross-sectional design and potential misclassification of facility levels in our data. CONCLUSIONS: Regions with more hospital deliveries than clinic deliveries have reduced neonatal mortality. Increasing delivery in hospitals while improving quality across the health system may help to reduce high neonatal mortality.

Variation in HIV care and treatment outcomes by facility in South Africa, 2011-2015: A cohort study.

BACKGROUND: Despite widespread availability of HIV treatment, patient outcomes differ across facilities. We propose and evaluate an approach to measure quality of HIV care at health facilities in South Africa's national HIV program using routine laboratory data. METHODS AND FINDINGS: Data were extracted from South Africa's National Health Laboratory Service (NHLS) Corporate Data Warehouse. All CD4 counts, viral loads (VLs), and other laboratory tests used in HIV monitoring were linked, creating a validated patient identifier. We constructed longitudinal HIV care cascades for all patients in the national HIV program, excluding data from the Western Cape and very small facilities. We then estimated for each facility in each year (2011 to 2015) the following cascade measures identified a priori as reflecting quality of HIV care: median CD4 count among new patients; retention 12 months after presentation; 12-month retention among patients established in care; viral suppression; CD4 recovery; monitoring after an elevated VL. We used factor analysis to identify an underlying measure of quality of care, and we assessed the persistence of this quality measure over time. We then assessed spatiotemporal variation and facility and population predictors in a multivariable regression context. We analyzed data on 3,265 facilities with a median (IQR) annual size of 441 (189 to 988) lab-monitored HIV patients. Retention 12 months after presentation increased from 42% to 47% during the study period, and viral suppression increased from 66% to 79%, although there was substantial variability across facilities. We identified an underlying measure of quality of HIV care that correlated with all cascade measures except median CD4 count at presentation. Averaging across the 5 years of data, this quality score attained a reliability of 0.84. Quality was higher for clinics (versus hospitals), in rural (versus urban) areas, and for larger facilities. Quality was lower in high-poverty areas but was not independently associated with percent Black. Quality increased by 0.49 (95% CI 0.46 to 0.53) standard deviations from 2011 to 2015, and there was evidence of geospatial autocorrelation (p < 0.001). The study's limitations include an inability to fully adjust for underlying patient risk, reliance on laboratory data which do not capture all relevant domains of quality, potential for errors in record linkage, and the omission of Western Cape. CONCLUSIONS: We observed persistent differences in HIV care and treatment outcomes across South African facilities. Targeting low-performing facilities for additional support could reduce overall burden of disease.

The price of quality care: cross-sectional associations between out-of-pocket payments and quality of care in six low-income countries.

OBJECTIVE: To assess the relationship between out-of-pocket (OOP) payments and primary health care quality in six low-income countries: Afghanistan, the Democratic Republic of the Congo (DRC), Haiti, Nepal, Senegal and Tanzania. METHODS: We examined the association between OOP payments and quality of care during antenatal care and sick child care visits using Service Provision Assessments data. We defined four process quality outcomes from observations of clinical care: visit duration, history-taking items asked, exam items performed, and counselling items delivered. The outcome is the total amount paid for services. We used multilevel models to test the relationship between OOP payments and each quality measure in public, private non-profit and private for-profit facilities controlling for patient, provider, and facility characteristics. RESULTS: Across the six countries, an average of 42% of the 29 677 observed clients paid for their visit. In the adjusted models, OOP payments were positively associated with the visit duration during sick child visits, with history-taking and exam items during antenatal care visits, and with counselling in private for-profit facilities for both visit types. These associations were strong particularly in Afghanistan, the DRC and Haiti; for example, a high-quality antenatal care visit in the DRC would cost approximately USD 1.12 more than a visit with median quality. CONCLUSION: Provider effort was associated with higher OOP payments for sick child and antenatal care services in the six countries studied. While many families are already spending high amounts on care, they must often spend even more to receive higher quality care.

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.

Mortality due to low-quality health systems in the universal health coverage era: a systematic analysis of amenable deaths in 137 countries.

BACKGROUND: Universal health coverage has been proposed as a strategy to improve health in low-income and middle-income countries (LMICs). However, this is contingent on the provision of good-quality health care. We estimate the excess mortality for conditions targeted in the Sustainable Development Goals (SDG) that are amenable to health care and the portion of this excess mortality due to poor-quality care in 137 LMICs, in which excess mortality refers to deaths that could have been averted in settings with strong health systems. METHODS: Using data from the 2016 Global Burden of Disease study, we calculated mortality amenable to personal health care for 61 SDG conditions by comparing case fatality between each LMIC with corresponding numbers from 23 high-income reference countries with strong health systems. We used data on health-care utilisation from population surveys to separately estimate the portion of amenable mortality attributable to non-utilisation of health care versus that attributable to receipt of poor-quality care. FINDINGS: 15·6 million excess deaths from 61 conditions occurred in LMICs in 2016. After excluding deaths that could be prevented through public health measures, 8·6 million excess deaths were amenable to health care of which 5·0 million were estimated to be due to receipt of poor-quality care and 3·6 million were due to non-utilisation of health care. Poor quality of health care was a major driver of excess mortality across conditions, from cardiovascular disease and injuries to neonatal and communicable disorders. INTERPRETATION: Universal health coverage for SDG conditions could avert 8·6 million deaths per year but only if expansion of service coverage is accompanied by investments into high-quality health systems. FUNDING: Bill & Melinda Gates Foundation.

Effect of a maternal and newborn health system quality improvement project on the use of facilities for childbirth: a cluster-randomised study in rural Tanzania.

OBJECTIVES: Reduction in maternal and newborn mortality requires that women deliver in high quality health facilities. However, many facilities provide sub-optimal quality of care, which may be a reason for less than universal facility utilisation. We assessed the impact of a quality improvement project on facility utilisation for childbirth. METHODS: In this cluster-randomised experiment in four rural districts in Tanzania, 12 primary care clinics and their catchment areas received a quality improvement intervention consisting of in-service training, mentoring and supportive supervision, infrastructure support, and peer outreach, while 12 facilities and their catchment areas functioned as controls. We conducted a census of all deliveries within the catchment area and used difference-in-differences analysis to determine the intervention's effect on facility utilisation for childbirth. We conducted a secondary analysis of utilisation among women whose prior delivery was at home. We further investigated mechanisms for increased facility utilisation. RESULTS: The intervention led to an increase in facility births of 6.7 percentage points from a baseline of 72% (95% Confidence Interval: 0.6, 12.8). The intervention increased facility delivery among women with past home deliveries by 18.3 percentage points (95% CI: 10.1, 26.6). Antenatal quality increased in intervention facilities with providers performing an additional 0.5 actions across the full population and 0.8 actions for the home delivery subgroup. CONCLUSIONS: We attribute the increased use of facilities to better antenatal quality. This increased utilisation would lead to lower maternal mortality only in the presence of improvement in care quality.

OBJECTIFS: La réduction de la mortalité maternelle et néonatale exige que les femmes accouchent dans des établissements de santé de haute qualité. Cependant, de nombreux établissements offrent une qualité de soins sous-optimale, ce qui peut expliquer l'utilisation moins généralisée des établissements. Nous avons évalué l'impact d'un projet d'amélioration de la qualité sur l'utilisation des établissements pour l'accouchement. MÉTHODES: Dans cet essai randomisé en grappes mené dans quatre districts ruraux de Tanzanie, 12 cliniques de soins primaires et leurs zones de recrutement ont bénéficié d'une intervention d'amélioration de la qualité consistant en une formation au cours du service, une supervision par un encadrement et un accompagnement, un appui en infrastructure et des relations avec les pairs tandis que 12 établissements et leur zone de recrutement ont servi de contrôles. Nous avons procédé à un recensement de tous les accouchements dans la zone de recrutement et utilisé une analyse de la différence des différences pour déterminer l'effet de l'intervention sur l'utilisation des établissements pour l'accouchement. Nous avons effectué une analyse secondaire de l'utilisation chez les femmes dont l'accouchement précédent avait eu lieu à domicile. Nous avons également investigué les mécanismes permettant d'accroître l'utilisation des établissements. RÉSULTATS: L'intervention a entraîné une augmentation du nombre de naissances dans les établissements de 6,7 points de pourcentage par rapport à une de référence base de 72% (intervalle de confiance à 95%: 0.6-12.8). L'intervention a augmenté de 18.3 points de pourcentage l'accouchement dans un établissement pour les femmes ayant accouché à domicile précédemment (IC 95%: 10.1-26.6). La qualité prénatale a augmenté dans les établissements d'intervention, les prestataires effectuant 0.5 action supplémentaire sur l'ensemble de la population et 0.8 action pour le sous-groupe des accouchements à domicile. CONCLUSIONS: Nous attribuons l'utilisation accrue des établissements à une meilleure qualité prénatale. Cette utilisation accrue ne ferait baisser la mortalité maternelle que si la qualité des soins s'améliorait.

Correction to: Malaria control across borders: quasi-experimental evidence from the Trans-Kunene malaria initiative (TKMI).

Following publication of the original article [1], the authors flagged an error in Addition file 6.

Low effective coverage of family planning and antenatal care services in Ethiopia.

OBJECTIVE: To assess the quality and effective coverage (EC) of family planning (FP) and antenatal care (ANC) services in Ethiopia. DESIGN: Secondary analyses of the 2014 Ethiopia Service Provision Assessment Plus Survey and 2016 Ethiopia Demographic and Health Survey data. SETTING AND PARTICIPANTS: Women using FP and ANC. MAIN OUTCOME MEASURES: Quality indices are created as a proportion of recommended clinical actions done in observations of ANC and FP visits. We adjust the crude coverage of ANC and of FP by the quality to estimate EC for both services. RESULTS: The crude coverage of FP was 61% and 62% for ANC in Ethiopia in 2016. On average, quality was 35.8% during FP visits and 86% of women received <50% of the recommended clinical actions. When adjusting the crude coverage to account for the quality of service, Ethiopia's FP services EC was 22%. On average, ANC quality was 34% and 81% received <50% of the recommended ANC clinical actions. When adjusting the crude coverage by the service quality, the mean EC of ANC services was 22% in Ethiopia. CONCLUSIONS: The quality of both FP and ANC services is low in Ethiopia, with women obtaining only a fraction of the standard clinical actions during their visits. In addition, there is considerable variation in EC across Ethiopia's regions, with variation driven largely by variations in crude coverage. To improve EC, actions are needed to improve the quality of ANC and FP care.

Malaria control across borders: quasi-experimental evidence from the Trans-Kunene malaria initiative (TKMI).

BACKGROUND: The transmission of malaria through population inflows from highly endemic areas with limited control efforts poses major challenges for national malaria control programmes. Several multilateral programmes have been launched in recent years to address cross-border transmission. This study assesses the potential impact of such a programme at the Angolan-Namibian border. METHODS: Community-based malaria prevention programmes involving bed net distribution and behaviour change home visits were rolled-out using a controlled, staggered (stepped wedge) design between May 2014 and July 2016 in a 100 × 40 km corridor along the Angolan-Namibian border. Three rounds of survey data were collected. The primary outcome studied was fever among children under five in the 2 weeks prior to the survey. Multivariable linear and logistic regression models were used to assess overall programme impact and the relative impact of unilateral versus coordinated bilateral intervention programmes. RESULTS: A total of 3844 child records were analysed. On average, programme rollout reduced the odds of child fever by 54% (aOR: 0.46, 95% CI 0.29 to 0.73) over the intervention period. In Namibia, the programme reduced the odds of fever by 30% in areas without simultaneous Angolan efforts (aOR: 0.70, 95% CI 0.34 to 1.44), and by an additional 62% in areas with simultaneous Angolan programmes. In Angola, the programme was highly effective in areas within 5 km of Namibian programmes (OR: 0.37, 95% CI 0.22 to 0.62), but mostly ineffective in areas closer to inland Angolan areas without concurrent anti-malarial efforts. CONCLUSIONS: The impact of malaria programmes depends on programme efforts in surrounding areas with differential control efforts. Coordinated malaria programming within and across countries will be critical for achieving the vision of a malaria free world.

Does quality influence utilization of primary health care? Evidence from Haiti.

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.

Assessing the quality of primary care in Haiti.

OBJECTIVE: To develop a composite measure of primary care quality and apply it to Haiti's primary care system. METHODS: Using the Primary Health Care Performance Initiative's framework, we defined four domains of primary care service delivery: (i) accessible care; (ii) effective service delivery; (iii) management and organization; and (iv) primary care functions. We gave each primary care facility in Haiti a quality score for each domain and overall, with poor, fair and good quality indicated by scores of 0.00-0.49, 0.50-0.74 and 0.75-1.00, respectively. We quantified access and effective access to primary care as the proportions of the population within 5 km of any primary care facility and a good facility, respectively. FINDINGS: Of the 786 primary care facilities in Haiti in 2013, only 332 (43%) facilities were classified as good for accessible care. Fewer facilities were classified as good in the domains of effective service delivery (30; 4%), management and organization (91; 12%) and primary care functions (43; 5%). Although about 91% of the population lived within 5 km of a primary care facility, only an estimated 23% of the entire population - including just 5% of the rural population - had access to primary care of good quality. CONCLUSION: Despite an extensive network of health facilities, a minority of Haitians had access to a primary care facility of good quality. Such facilities were especially scarce in rural areas. Similar systematic analyses of the quality of primary care could inform national efforts to strengthen health systems.

Catastrophic health expenditure during the COVID-19 pandemic in five countries: a time-series analysis.

BACKGROUND: The COVID-19 pandemic disrupted health systems in 2020, but it is unclear how financial hardship due to out-of-pocket (OOP) health-care costs was affected. We analysed catastrophic health expenditure (CHE) in 2020 in five countries with available household expenditure data: Belarus, Mexico, Peru, Russia, and Viet Nam. In Mexico and Peru, we also conducted an analysis of drivers of change in CHE in 2020 using publicly available data. METHODS: In this time-series analysis, we defined CHE as when OOP health-care spending exceeds 10% of consumption expenditure. Data for 2004-20 were obtained from individual and household level survey microdata (available for Mexico and Peru only), and tabulated data from the National Statistical Committee of Belarus and the World Bank Health Equity and Financial Protection Indicator database (for Viet Nam and Russia). We compared 2020 CHE with the CHE predicted from historical trends using an ensemble model. This method was also used to assess drivers of CHE: insurance coverage, OOP expenditure, and consumption expenditure. Interrupted time-series analysis was used to investigate the role of stay-at-home orders in March, 2020 in changes in health-care use and sector (ie, private vs public). FINDINGS: In Mexico, CHE increased to 5·6% (95% uncertainty interval [UI] 5·1-6·2) in 2020, higher than predicted (3·2%, 2·5-4·0). In Belarus, CHE was 13·5% (11·8-15·2) in 2020, also higher than predicted (9·7%, 7·7-11·3). CHE was not different than predicted by past trends in Russia, Peru, and Viet Nam. Between March and April, 2020, health-care visits dropped by 4·6 (2·6-6·5) percentage points in Mexico and by 48·3 (40·6-56·0) percentage points in Peru, and the private share of health-care visits increased by 7·3 (4·3-10·3) percentage points in Mexico and by 20·7 (17·3-24·0) percentage points in Peru. INTERPRETATION: In three of the five countries studied, health systems either did not protect people from the financial risks of health care or did not maintain health-care access in 2020, an indication of health systems failing to maintain basic functions. If the 2020 response to the COVID-19 pandemic accelerated shifts to private health-care use, policies to cover costs in that sector or motivate patients to return to the public sector are needed to maintain financial risk protection. FUNDING: The Bill & Melinda Gates Foundation.

The influence of Continuous Quality Improvement on healthcare quality: A mixed-methods study from Zimbabwe.

In an effort to improve the poor quality of maternal, newborn, and child health services, the Zimbabwe Ministry of Health and Child Care implemented a Continuous Quality Improvement (CQI) pilot in 2016. Health workers and district managers were trained and supported to implement cycles of quality target setting, developing and implementing action plans, and tracking outcomes. The pilot was implemented in district hospitals and primary health centers in five districts as an arm of the performance-based health financing (PBF) program. This study uses mixed methods to estimate the effect of the CQI model on quality of care for various services and to identify factors that enabled or impeded quality improvements. We assessed changes in quality of care for seven services over a two-year implementation period and compared these changes against other PBF districts. We also conducted focus group discussions and in-depth interviews with district and facility-level health workers and managers after implementation to explore enabling and impeding factors affecting program performance. Among the seven services assessed, CQI was associated with quality improvement in primary health centers for two: postnatal care and maternal delivery care. Enabling factors included strengthened leadership, teamwork and joint decision-making at facilities; and supportive supervision. Impeding factors included fragmentation of quality assurance policies; staff shortages and turnover; and gaps in the CQI training. Improvements were limited when considering the full breadth of potential outcomes but arise in certain areas of core focus of the CQI program. In order to see large scale improvement in the quality of healthcare in Zimbabwe, CQI should be seen as one potential tool in a broader health systems quality improvement strategy.

The role of teams in shaping quality of obstetrical care: a cross-sectional study in Dire Dawa, Ethiopia.

OBJECTIVES: To examine how characteristics of clinical colleagues influence quality of care. DESIGN: We conducted a cross-sectional observational study examining the associations between quality of care and a provider's coworkers, controlling for individual provider's characteristics and contextual factors. SETTING: Nine health facilities in Dire Dawa Administration, Ethiopia, from December 2020 to February 2021. PARTICIPANTS: 824 clients and 95 unique providers were observed across the 9 health facilities. OUTCOME MEASURES: We examine the quality of processes of intrapartum and immediate postpartum care during five phases of the delivery (first examination, first stage of labour, third stage of labour, immediate newborn care and immediate maternal postpartum care). RESULTS: For the average client, 50% of the recommended routine clinical actions were completed during the delivery overall, with immediate maternal postpartum care being the least well performed (17% of recommended actions). Multiple healthcare providers were involved in 55% of deliveries. The number of providers contributing to a delivery was unassociated with the quality of care, but a one standard deviation increase in the coworker's performance was associated with a 2% point increase in quality of care (p<0.01); this association was largest among providers in the middle quartiles of performance. CONCLUSIONS: A provider's typical performance had a modest positive association with quality of delivery care given by their coworker. As delivery care is often provided by multiple healthcare providers, examining the dynamics of how they influence one another can provide important insights for quality improvement.

Effect of the COVID-19 pandemic on health service utilization across regions of Ethiopia: An interrupted time series analysis of health information system data from 2019-2020.

The spread of COVID-19 and associated deaths have remained low in Ethiopia. However, the pandemic could pose a public health crisis indirectly through disruptions in essential health services. The aim of this study was to examine disruptions in health service utilization during the first nine months of the COVID-19 pandemic across 10 regions in Ethiopia. We analyzed utilization of 21 different health services across all of Ethiopia (except the Tigray region) for the period of January 2019 to December 2020. Data were extracted from the Ethiopian district health information system (DHIS2). Monthly visits in 2020 were graphed relative to the same months in 2019. Interrupted time series analysis was used to estimate the effect of the pandemic on service utilization in each region. We found that disruptions in health services were generally higher in urban regions which were most affected by COVID. Outpatient visits declined by 52%, 54%, and 58%, specifically in Dire Dawa, Addis Ababa and Harari, the three urban regions. Similarly, there was a 47% reduction in inpatient admissions in Addis Ababa. In agrarian regions, the pandemic caused an 11% to 17% reduction in outpatient visits and a 10% to 27% decline in inpatient admissions. Visits for children with diarrhea, pneumonia and malnutrition also declined substantially while maternal health services were less affected. Our study indicates that disruptions in health services were more pronounced in areas that were relatively harder hit by the pandemic. Our results show that the Ethiopian health system has a limited capacity to absorb shocks. During future waves of COVID or future pandemics, the Ethiopian health system must be better prepared to maintain essential services and mitigate the indirect impact of the pandemic on public health, particularly in urban areas.

COVID-19 and resilience of healthcare systems in ten countries.

Declines in health service use during the Coronavirus Disease 2019 (COVID-19) pandemic could have important effects on population health. In this study, we used an interrupted time series design to assess the immediate effect of the pandemic on 31 health services in two low-income (Ethiopia and Haiti), six middle-income (Ghana, Lao People's Democratic Republic, Mexico, Nepal, South Africa and Thailand) and high-income (Chile and South Korea) countries. Despite efforts to maintain health services, disruptions of varying magnitude and duration were found in every country, with no clear patterns by country income group or pandemic intensity. Disruptions in health services often preceded COVID-19 waves. Cancer screenings, TB screening and detection and HIV testing were most affected (26-96% declines). Total outpatient visits declined by 9-40% at national levels and remained lower than predicted by the end of 2020. Maternal health services were disrupted in approximately half of the countries, with declines ranging from 5% to 33%. Child vaccinations were disrupted for shorter periods, but we estimate that catch-up campaigns might not have reached all children missed. By contrast, provision of antiretrovirals for HIV was not affected. By the end of 2020, substantial disruptions remained in half of the countries. Preliminary data for 2021 indicate that disruptions likely persisted. Although a portion of the declines observed might result from decreased needs during lockdowns (from fewer infectious illnesses or injuries), a larger share likely reflects a shortfall of health system resilience. Countries must plan to compensate for missed healthcare during the current pandemic and invest in strategies for better health system resilience for future emergencies.