Regional determinants of quality of care for sick children: A multilevel analysis in four countries.

Background: The limited impact of increased access to care on improvements in health outcomes during the Millennium Development Goal era has been attributed, in part, to inadequate quality of care. We identified regional factors associated with health service quality for sick child care in low-income countries and examined whether provider factors interact with regional factors to affect the quality of care. Methods: We conducted cross-sectional random intercept four-level linear regression using the most recent Service Provision Assessment and Demographic Health Survey data from four countries (467 from the Democratic Republic of Congo 2018, 2425 from Afghanistan 2018, 2072 from Nepal 2015, and 813 from Senegal 2017). The outcome variable was the service quality score for sick child care, which was measured as the percentage of clinically recommended tasks completed in the integrated management of childhood illness (ranging from 0 to 100). Regional factors were selected based on the High-Quality Health System Framework. Results: The service quality score was found to be positively associated with the proportion of large facilities (ß = 8.61; P = 0.004) and the proportion of providers ranked in the top fifth for service quality score (ß = 30.15; P < 0.001) in the region. We identified significant cross-level interactions between provider qualifications (ß = -16.6; P < 0.001) or job descriptions (ß = 12.01; P = 0.002) and the proportion of providers in the top fifth for service quality scores within the region. As the proportion of top-performing providers in a region increased, the increase in the service quality score was more pronounced among providers who were nonmedical doctors or did not have job descriptions than among their counterparts. Conclusions: Our findings indicate that the quality of care for sick children in a region improves with a greater proportion of high-performing providers or larger facilities. Providers who are not medical doctors, or those who have specific job descriptions, tend to benefit more from the presence of these top-performing providers.

Population confidence in the health system in 15 countries: results from the first round of the People's Voice Survey.

Population confidence is essential to a well functioning health system. Using data from the People's Voice Survey-a novel population survey conducted in 15 low-income, middle-income, and high-income countries-we report health system confidence among the general population and analyse its associated factors. Across the 15 countries, fewer than half of respondents were health secure and reported being somewhat or very confident that they could get and afford good-quality care if very sick. Only a quarter of respondents endorsed their current health system, deeming it to work well with no need for major reform. The lowest support was in Peru, the UK, and Greece-countries experiencing substantial health system challenges. Wealthy, more educated, young, and female respondents were less likely to endorse the health system in many countries, portending future challenges for maintaining social solidarity for publicly financed health systems. In pooled analyses, the perceived quality of the public health system and government responsiveness to public input were strongly associated with all confidence measures. These results provide a post-COVID-19 pandemic baseline of public confidence in the health system. The survey should be repeated regularly to inform policy and improve health system accountability.

User-reported quality of care: findings from the first round of the People's Voice Survey in 14 countries.

High-quality care is essential for improving health outcomes, although many health systems struggle to maintain good quality. We use data from the People's Voice Survey-a nationally representative survey conducted in 14 high-income, middle-income, and low-income countries-to describe user-reported quality of most recent health care in the past 12 months. We described ratings for 14 measures of care competence, system competence, and user experience and assessed the relationship between visit quality factors and user recommendation of the facility. We disaggregated the data by high-need and underserved groups. The proportion of respondents rating their most recent visit as high quality ranged from 25% in Laos to 74% in the USA. The mean facility recommendation score was 7·7 out of 10. Individuals with high needs or who are underserved reported lower-quality services on average across countries. Countries with high health expenditure per capita tended to have better care ratings than countries with low health expenditure. Visit quality factors explained a high proportion of variation in facility recommendations relative to facility or demographic factors. These results show that user-reported quality is low but increases with high national health expenditure. Elevating care quality will require monitoring and improvements on multiple dimensions of care quality, especially in public systems.

Health system quality and COVID-19 vaccination: a cross-sectional analysis in 14 countries.

The social and behavioural determinants of COVID-19 vaccination have been described previously. However, little is known about how vaccinated people use and rate their health system. We used surveys conducted in 14 countries to study the health system correlates of COVID-19 vaccination. Country-specific logistic regression models were adjusted for respondent age, education, income, chronic illness, history of COVID-19, urban residence, and minority ethnic, racial, or linguistic group. Estimates were summarised across countries using random effects meta-analysis. Vaccination coverage with at least two or three doses ranged from 29% in India to 85% in Peru. Greater health-care use, having a regular and high-quality provider, and receiving other preventive health services were positively associated with vaccination. Confidence in the health system and government also increased the odds of vaccination. By contrast, having unmet health-care needs or experiencing discrimination or a medical mistake decreased the odds of vaccination. Associations between health system predictors and vaccination tended to be stronger in high-income countries and in countries with the most COVID-19-related deaths. Access to quality health systems might affect vaccine decisions. Building strong primary care systems and ensuring a baseline level of quality that is affordable for all should be central to pandemic preparedness strategies.

The path to universal health coverage in five African and Asian countries: examining the association between insurance status and health-care use.

Despite major efforts to achieve universal health coverage (UHC), progress has lagged in many African and Asian countries. A key strategy pursued by many countries is the use of health insurance to increase access and affordability. However, evidence on insurance coverage and on the association between insurance and UHC is mixed. We analysed nationally representative cross-sectional data collected between 2022 and 2023 in Ethiopia, Kenya, South Africa, India, and Laos. We described public and private insurance coverage by sociodemographic factors and used logistic regression to examine the associations between insurance status and seven health-care use outcomes. Health insurance coverage ranged from 25% in India to 100% in Laos. The share of private insurance ranged from 1% in Ethiopia to 13% in South Africa. Relative to the population with private insurance, the uninsured population had reduced odds of health-care use (adjusted odds ratio 0·68, 95% CI 0·50-0·94), cardiovascular examinations (0·63, 0·47-0·85), eye and dental examinations (0·54, 0·42-0·70), and ability to get or afford care (0·64, 0·48-0·86); private insurance was not associated with unmet need, mental health care, and cancer screening. Relative to private insurance, public insurance was associated with reduced odds of health-care use (0·60, 0·43-0·82), mental health care (0·50, 0·31-0·80), cardiovascular examinations (0·62, 0·46-0·84), and eye and dental examinations (0·50, 0·38-0·65). Results were highly heterogeneous across countries. Public health insurance appears to be only weakly associated with access to health services in the countries studied. Further research is needed to improve understanding of these associations and to identify the most effective financing strategies to achieve UHC.

Primary health care in practice: usual source of care and health system performance across 14 countries.

Primary health care (PHC) is central to attainment of the Sustainable Development Goals, yet comparable cross-country data on key aspects of primary care have not been widely available. This study analysed data from the People's Voice Survey, which was conducted in 2022 and 2023 in 14 countries. We documented usual source of care across countries and examined associations of usual source of care with core PHC services, quality ratings, and health system confidence. We found that 75% of respondents had a usual source of care, and that 40% of respondents accessed usual care in the public sector at primary level. 44% rated their usual source of care as very good or excellent. Access to PHC-linked screenings and treatments varied widely within and across countries. Having any usual source of care was associated with higher take-up of preventive services, greater access to treatment including mental health services, and greater health system endorsement. Strengthening links between health system users and primary care providers could improve take-up of preventive care and increase user satisfaction with health system performance.

What are the determinants of variation in caretaker satisfaction with sick child consultations? A cross-sectional analysis in five low-income and middle-income countries.

OBJECTIVES: The objective of this study was to explore determinants of variation in overall caretaker satisfaction with curative care for sick children under the age of 5 in five low-income and middle-income countries. DESIGN: A pooled cross-sectional analysis was conducted using data from the Service Provision Assessment. SETTING: We used data collected in five countries (Afghanistan, Democratic Republic of the Congo, Haiti, Malawi and Tanzania) between 2013 and 2018. PARTICIPANTS: Respondents were 13 149 caretakers of children under the age of 5 who consulted for a sick child visit. PRIMARY OUTCOMES MEASURED: The outcome variable was whether the child's caretaker was very satisfied versus more or less satisfied or not satisfied overall. Predictors pertained to child and caretaker characteristics, health system foundations and process of care (eg, care competence, user experience). Two-level logistic regression models were used to assess the extent to which these categories of variables explained variation in satisfaction. The main analyses used pooled data; country-level analyses were also performed. RESULTS: Process of care, including user experience, explained the largest proportion of variance in caretaker satisfaction (13.8%), compared with child and caretaker characteristics (0.9%) and health system foundations (3.8%). The odds of being very satisfied were lower for caretakers who were not given adequate explanation (OR: 0.56, 95% CI 0.46 to 0.67), who had a problem with medication availability (OR: 0.31, 95% CI 0.27 to 0.35) or who encountered a problem with the cost of services (OR: 0.57, 95% CI 0.48 to 0.66). The final model explained only 21.8% of the total variance. Country-level analyses showed differences in variance explained and in associations with predictors. CONCLUSIONS: Better process of care, especially user experience, should be prioritised for its benefit regarding caretaker satisfaction. Unmeasured factors explained the majority of variation in caretaker satisfaction and should be explored in future studies.

Measuring people's views on health system performance: Design and development of the People's Voice Survey.

Todd Lewis and co-authors discuss development and use of the People's Voice Survey for health system assessment.

Adverse birth outcomes among women with 'low-risk' pregnancies in India: findings from the Fifth National Family Health Survey, 2019-21.

Background: Despite substantial progress in improving maternal and newborn health, India continues to experience high rates of newborn mortality and stillbirths. One reason may be that many births happen in health facilities that lack advanced services-such as Caesarean section, blood transfusion, or newborn intensive care. Stratification based on pregnancy risk factors is used to guide 'high-risk' women to advanced facilities. To assess the utility of risk stratification for guiding the choice of facility, we estimated the frequency of adverse newborn outcomes among women classified as 'low risk' in India. Methods: We used the 2019-21 Fifth National Family Health Survey (NFHS-5)-India's Demographic and Health Survey-which includes modules administered to women aged 15-49 years. In addition to pregnancy history and outcomes, the survey collected a range of risk factors, including biomarkers. We used national obstetric risk guidelines to classify women as 'high risk' versus 'low risk' and assessed the frequency of stillbirths, newborn deaths, and unplanned Caesarean sections for the respondent's last pregnancy lasting 7 or more months in the past five years. We calculated the proportion of deliveries occurring at non-hospital facilities in all the Indian states. Findings: Using data from nearly 176,699 recent pregnancies, we found that 46.6% of India's newborn deaths and 56.3% of stillbirths were among women who were 'low risk' according to national guidelines. Women classified as 'low risk' had a Caesarean section rate of 8.4% (95% CI 8.1-8.7%), marginally lower than the national average of 10.0% (95% CI 9.8-10.3%). In India as a whole, 32.0% (95% CI 31.5-32.5%) of deliveries occurred in facilities that were likely to lack advanced services. There was substantial variation across the country, with less than 5% non-hospital public facility deliveries in Punjab, Kerala, and Delhi compared to more than 40% in Odisha, Madhya Pradesh, and Rajasthan. Newborn mortality tended to be lower in states with highest hospital delivery rates. Interpretation: Individual risk stratification based on factors identified in pregnancy fails to accurately predict which women will have delivery complications and experience stillbirth and newborn death in India. Thus a determination of 'low risk' should not be used to guide women to health facilities lacking key life saving services, including Caesarean section, blood transfusion, and advanced newborn resuscitation and care. Funding: Bill and Melinda Gates Foundation and the World Bank. The findings, interpretations and conclusions expressed in the paper are entirely those of the authors, and do not represent the views of the Gates Foundation or of the World Bank, its Executive Directors, or the countries they represent.

Health service quality in 2929 facilities in six low-income and middle-income countries: a positive deviance analysis.

BACKGROUND: Primary care is of insufficient quality in many low-income and middle-income countries. Some health facilities perform better than others despite operating in similar contexts, although the factors that characterise best performance are not well known. Existing best-performance analyses are concentrated in high-income countries and focus on hospitals. We used the positive deviance approach to identify the factors that differentiate best from worst primary care performance among health facilities across six low-resource health systems. METHODS: This positive deviance analysis used nationally representative samples of public and private health facilities from Service Provision Assessments of the Democratic Republic of the Congo, Haiti, Malawi, Nepal, Senegal, and Tanzania. Data were collected starting June 11, 2013, in Malawi and ending Feb 28, 2020, in Senegal. We assessed facility performance through completion of the Good Medical Practice Index (GMPI) of essential clinical actions (eg, taking a thorough history, conducting an adequate physical examination) according to clinical guidelines and measured with direct observations of care. We identified hospitals and clinics in the top decile of performance (defined as best performers) and conducted a quantitative, cross-national positive deviance analysis to compare them with facilities performing below the median (defined as worst performers) and identify facility-level factors that explain the gap between best and worst performance. FINDINGS: We identified 132 best-performing and 664 worst-performing hospitals, and 355 best-performing and 1778 worst-performing clinics based on clinical performance across countries. The mean GMPI score was 0·81 (SD 0·07) for the best-performing hospitals and 0·44 (0·09) for the worst-performing hospitals. Among clinics, mean GMPI scores were 0·75 (0·07) for the best performers and 0·34 (0·10) for the worst performers. High-quality governance, management, and community engagement were associated with best performance compared with worst performance. Private facilities out-performed government-owned hospitals and clinics. INTERPRETATION: Our findings suggest that best-performing health facilities are characterised by good management and leaders who can engage staff and community members. Governments should look to best performers to identify scalable practices and conditions for success that can improve primary care quality overall and decrease quality gaps between health facilities. FUNDING: Bill & Melinda Gates Foundation.

Associations between the stringency of COVID-19 containment policies and health service disruptions in 10 countries.

BACKGROUND: Disruptions in essential health services during the COVID-19 pandemic have been reported in several countries. Yet, patterns in health service disruption according to country responses remain unclear. In this paper, we investigate associations between the stringency of COVID-19 containment policies and disruptions in 31 health services in 10 low- middle- and high-income countries in 2020. METHODS: Using routine health information systems and administrative data from 10 countries (Chile, Ethiopia, Ghana, Haiti, Lao People's Democratic Republic, Mexico, Nepal, South Africa, South Korea, and Thailand) we estimated health service disruptions for the period of April to December 2020 by dividing monthly service provision at national levels by the average service provision in the 15 months pre-COVID (January 2019-March 2020). We used the Oxford COVID-19 Government Response Tracker (OxCGRT) index and multi-level linear regression analyses to assess associations between the stringency of restrictions and health service disruptions over nine months. We extended the analysis by examining associations between 11 individual containment or closure policies and health service disruptions. Models were adjusted for COVID caseload, health service category and country GDP and included robust standard errors. FINDINGS: Chronic disease care was among the most affected services. Regression analyses revealed that a 10% increase in the mean stringency index was associated with a 3.3 percentage-point (95% CI -3.9, -2.7) reduction in relative service volumes. Among individual policies, curfews, and the presence of a state of emergency, had the largest coefficients and were associated with 14.1 (95% CI -19.6, 8.7) and 10.7 (95% CI -12.7, -8.7) percentage-point lower relative service volumes, respectively. In contrast, number of COVID-19 cases in 2020 was not associated with health service disruptions in any model. CONCLUSIONS: Although containment policies were crucial in reducing COVID-19 mortality in many contexts, it is important to consider the indirect effects of these restrictions. Strategies to improve the resilience of health systems should be designed to ensure that populations can continue accessing essential health care despite the presence of containment policies during future infectious disease outbreaks.

Population Preferences for Primary Care Models for Hypertension in Karnataka, India.

Importance: Hypertension contributes to more than 1.6 million deaths annually in India, with many individuals being unaware they have the condition or receiving inadequate treatment. Policy initiatives to strengthen disease detection and management through primary care services in India are not currently informed by population preferences. Objective: To quantify population preferences for attributes of public primary care services for hypertension. Design, Setting, and Participants: This cross-sectional study involved administration of a household survey to a population-based sample of adults with hypertension in the Bengaluru Nagara district (Bengaluru City; urban setting) and the Kolar district (rural setting) in the state of Karnataka, India, from June 22 to July 27, 2021. A discrete choice experiment was designed in which participants selected preferred primary care clinic attributes from hypothetical alternatives. Eligible participants were 30 years or older with a previous diagnosis of hypertension or with measured diastolic blood pressure of 90 mm Hg or higher or systolic blood pressure of 140 mm Hg or higher. A total of 1422 of 1927 individuals (73.8%) consented to receive initial screening, and 1150 (80.9%) were eligible for participation, with 1085 (94.3%) of those eligible completing the survey. Main Outcomes and Measures: Relative preference for health care service attributes and preference class derived from respondents selecting a preferred clinic scenario from 8 sets of hypothetical comparisons based on wait time, staff courtesy, clinician type, carefulness of clinical assessment, and availability of free medication. Results: Among 1085 adult respondents with hypertension, the mean (SD) age was 54.4 (11.2) years; 573 participants (52.8%) identified as female, and 918 (84.6%) had a previous diagnosis of hypertension. Overall preferences were for careful clinical assessment and consistent availability of free medication; 3 of 5 latent classes prioritized 1 or both of these attributes, accounting for 85.1% of all respondents. However, the largest class (52.4% of respondents) had weak preferences distributed across all attributes (largest relative utility for careful clinical assessment: ß = 0.13; 95% CI, 0.06-0.20; 36.4% preference share). Two small classes had strong preferences; 1 class (5.4% of respondents) prioritized shorter wait time (85.1% preference share; utility, ß = -3.04; 95% CI, -4.94 to -1.14); the posterior probability of membership in this class was higher among urban vs rural respondents (mean [SD], 0.09 [0.26] vs 0.02 [0.13]). The other class (9.5% of respondents) prioritized seeing a physician (the term doctor was used in the survey) rather than a nurse (66.2% preference share; utility, ß = 4.01; 95% CI, 2.76-5.25); the posterior probability of membership in this class was greater among rural vs urban respondents (mean [SD], 0.17 [0.35] vs 0.02 [0.10]). Conclusions and Relevance: In this study, stated population preferences suggested that consistent medication availability and quality of clinical assessment should be prioritized in primary care services in Karnataka, India. The heterogeneity observed in population preferences supports considering additional models of care, such as fast-track medication dispensing to reduce wait times in urban settings and physician-led services in rural areas.

Health system adaptions to improve care for people living with non-communicable diseases during COVID-19 in low-middle income countries: A scoping review.

Background: During the COVID-19 pandemic, access to health care for people living with non-communicable diseases (NCDs) has been significantly disrupted. Calls have been made to adapt health systems and innovate service delivery models to improve access to care. We identified and summarized the health systems adaptions and interventions implemented to improve NCD care and their potential impact on low- and middle-income countries (LMICs). Methods: We comprehensively searched Medline/PubMed, Embase, CINAHL, Global Health, PsycINFO, Global Literature on coronavirus disease, and Web of Science for relevant literature published between January 2020 and December 2021. While we targeted articles written in English, we also included papers published in French with abstracts written in English. Results: After screening 1313 records, we included 14 papers from six countries. We identified four unique health systems adaptations/interventions for restoring, maintaining, and ensuring continuity of care for people living with NCDs: telemedicine or teleconsultation strategies, NCD medicine drop-off points, decentralization of hypertension follow-up services and provision of free medication to peripheral health centers, and diabetic retinopathy screening with a handheld smartphone-based retinal camera. We found that the adaptations/interventions enhanced continuity of NCD care during the pandemic and helped bring health care closer to patients using technology and easing access to medicines and routine visits. Telephonic aftercare services appear to have saved a significant amount of patients' time and funds. Hypertensive patients recorded better blood pressure controls over the follow-up period. Conclusions: Although the identified measures and interventions for adapting health systems resulted in potential improvements in access to NCD care and better clinical outcomes, further exploration is needed to establish the feasibility of these adaptations/interventions in different settings given the importance of context in their successful implementation. Insights from such implementation studies are critical for ongoing health systems strengthening efforts to mitigate the impact of COVID-19 and future global health security threats for people living with NCDs.

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.

Equitable Distribution of Poor Quality of Care? Equity in Quality of Reproductive Health Services in Ethiopia.

The Ethiopian health system faces persistent inequities in health-care utilization and outcomes, despite continued efforts to expand health service coverage. There is little evidence in the literature describing the status of equity in the quality of healthcare. This paper aims to understand the disparities in quality of antenatal care (ANC) and family planning (FP) among the poor and non-poor communities. We used the 2016 Ethiopia Demographic and Health Survey (DHS) data to compute a Multidimensional Poverty Index (MPI), and the 2014 Service Provision Assessment (SPA) data to assess quality of ANC and FP services-defined as the level of adherence to World Health Organization (WHO) clinical and service guidelines. We merged the two datasets using geographical coordinates, and aggregated service users into facility catchment area clusters using a 2-km radius for urban and 10-km radius for rural facilities. We computed ANC and FP quality and MPI indices for each facility and assigned these to catchment areas. Using the international cutoff point for deprivation (MPI = 33.3%), we evaluated whether the quality of ANC and FP services varies by poor and non-poor catchment areas. We found that most of catchment areas (75.7%) were deprived. While the overall quality of ANC and FP services are low (33% and 34% respectively), we found little variation in the distribution of the quality of these services between poor and non-poor areas, urban and rural settings, or regionally. The short-term focus needs to be on improving the overall quality of services rather than on its distribution.

Effect of lifting COVID-19 restrictions on utilisation of primary care services in Nepal: a difference-in-differences analysis.

INTRODUCTION: An increasing number of studies have reported disruptions in health service utilisation due to the COVID-19 pandemic and its associated restrictions. However, little is known about the effect of lifting COVID-19 restrictions on health service utilisation. The objective of this study was to estimate the effect of lifting COVID-19 restrictions on primary care service utilisation in Nepal. METHODS: Data on utilisation of 10 primary care services were extracted from the Health Management Information System across all health facilities in Nepal. We used a difference-in-differences design and linear fixed effects regressions to estimate the effect of lifting COVID-19 restrictions. The treatment group included palikas that had lifted restrictions in place from 17 August 2020 to 16 September 2020 (Bhadra 2077) and the control group included palikas that had maintained restrictions during that period. The pre-period included the 4 months of national lockdown from 24 March 2020 to 22 July 2020 (Chaitra 2076 to Ashar 2077). Models included month and palika fixed effects and controlled for COVID-19 incidence. RESULTS: We found that lifting COVID-19 restrictions was associated with an average increase per palika of 57.5 contraceptive users (95% CI 14.6 to 100.5), 15.6 antenatal care visits (95% CI 5.3 to 25.9) and 1.6 child pneumonia visits (95% CI 0.2 to 2.9). This corresponded to a 9.4% increase in contraceptive users, 34.2% increase in antenatal care visits and 15.6% increase in child pneumonia visits. Utilisation of most other primary care services also increased after lifting restrictions, but coefficients were not statistically significant. CONCLUSIONS: Despite the ongoing pandemic, lifting restrictions can lead to an increase in some primary care services. Our results point to a causal link between restrictions and health service utilisation and call for policy makers in low- and middle-income countries to carefully consider the trade-offs of strict lockdowns during future COVID-19 waves or future pandemics.

Resilience learning from the COVID-19 pandemic and its relevance for routine immunization programs.

INTRODUCTION: The COVID-19 pandemic represents a threat that has posed a challenge to public health response and threatens immunization programs globally. Despite recommendations to continue routine immunization services, disruptions have been observed to these and mass vaccination campaigns. This may result in setbacks to immunization initiative successes and a rise in cases of vaccine-preventable diseases. AREAS COVERED: We conducted a systematic literature review to identify studies globally that described how indicators of health system resilience, defined using the Resilient Health System Framework, enabled routine immunizations to continue during the COVID-19 pandemic. A systematic search was conducted in Embase, Web of Science, PsychInfo, medRxiv, bioRxiv, and the gray literature between 1 January 2020, and 12 November 2021. Information was extracted from the studies identified describing how the specific elements of resiliency (being aware, diverse, self-regulating, integrated, and adaptive) were applied to their routine immunization programs. EXPERT OPINION: Our study demonstrates the use of tools that contributed to immunization program resilience during the COVID-19 pandemic in all geographic regions and for countries with different income levels. These tools may help inform preparations for other immunization programs to catch up from the COVID-19 pandemic or mitigate the impact of future threats.

Best and worst performing health facilities: A positive deviance analysis of perceived drivers of primary care performance in Nepal.

Primary care services are on average of low quality in Nepal. However, there is marked variation in performance of basic clinical and managerial functions between primary health care centers. The determinants of variation in primary care performance in low- and middle-income countries have been understudied relative to the prominence of primary care in national health plans. We used the positive deviance approach to identify best and worst performing primary health care centers in Nepal and investigated perceived drivers of best performance. We selected eight primary health care centers in Province 1, Nepal, using an index of basic clinical and operational activities to identify four best and four worst performing primary health care centers. We conducted semi-structured, in-depth interviews with managers and clinical staff from each of the eight primary health care centers for a total of 32 interviews. We identified the following factors that distinguished best from worst performers: 1) Managing the facility effectively, 2) engaging local leadership, 3) building active community accountability, 4) assessing and responding to facility performance, 5) developing sources of funding, 6) compensating staff fairly, 7) managing clinical staff performance, and 8) promoting uninterrupted availability of supplies and equipment. These findings can be used to inform quality improvement efforts and health system reforms in Nepal and other similarly under-resourced health systems.