Explore the vast range of titles available.

IntroductionOver 46 million people are living with rheumatic heart disease (RHD) globally, resulting in 380 000 premature deaths each year. Effective RHD prevention strategies are known but their implementation in low-resource settings has lagged. This study evaluated the feasibility and effectiveness of integrating secondary antibiotic prophylaxis into primary health centres to improve access and adherence to RHD care.MethodsWe conducted a hybrid type III study using a mixed-method, pre–post design to evaluate a package of implementation strategies centred on decentralised RHD care and use of an electronic medical record in Gulu and Lira, Uganda. We combined clinical and programmatic data with provider and patient interviews to assess effectiveness, adoption and acceptability. The mean difference in the annualised percentage of days adherent to benzathine penicillin G (BPG) monthly injections predecentralisation and postdecentralisation was calculated using linear mixed effect regression. Thematic analysis was used to analyse qualitative data.ResultsWe decentralised 151 patients (median age 17.9 years, 64% female) from district hospitals to eight primary health centres. The percentage of days adherent to BPG was 77.2% predecentralisation and 80.5% postdecentralisation (mean difference 3.25, (95% CI −0.72 to 6.86), p=0.081), which was statistically non-inferior at the −10% non-inferiority margin. Interview data identified knowledge, confidence and intrinsic motivation as major determinants of provider adoption. Patients expressed mixed feelings towards pain control and provider services, but convenience and financial savings resulted in a high level of acceptability. The electronic registry presented challenges in a naive environment but showed a strong potential as an oversight tool at the district level.DiscussionThis study is the first to demonstrate that decentralised RHD care is effective in sub-Saharan Africa. Lessons learnt provide a platform for future integration of RHD services countrywide, with implications for increasing access to and scale-up of secondary prevention measures for RHD care in Uganda.

The World Bank is publishing nine volumes of Disease Control Priorities, 3rd edition (DCP3) between 2015 and 2018. Volume 9, Improving Health and Reducing Poverty, summarises the main messages from all the volumes and contains cross-cutting analyses. This Review draws on all nine volumes to convey conclusions. The analysis in DCP3 is built around 21 essential packages that were developed in the nine volumes. Each essential package addresses the concerns of a major professional community (eg, child health or surgery) and contains a mix of intersectoral policies and health-sector interventions. 71 intersectoral prevention policies were identified in total, 29 of which are priorities for early introduction. Interventions within the health sector were grouped onto five platforms (population based, community level, health centre, first-level hospital, and referral hospital). DCP3 defines a model concept of essential universal health coverage (EUHC) with 218 interventions that provides a starting point for country-specific analysis of priorities. Assuming steady-state implementation by 2030, EUHC in lower-middle-income countries would reduce premature deaths by an estimated 4·2 million per year. Estimated total costs prove substantial: about 9·1% of (current) gross national income (GNI) in low-income countries and 5·2% of GNI in lower-middle-income countries. Financing provision of continuing intervention against chronic conditions accounts for about half of estimated incremental costs. For lower-middle-income countries, the mortality reduction from implementing the EUHC can only reach about half the mortality reduction in non-communicable diseases called for by the Sustainable Development Goals. Full achievement will require increased investment or sustained intersectoral action, and actions by finance ministries to tax smoking and polluting emissions and to reduce or eliminate (often large) subsidies on fossil fuels appear of central importance. DCP3 is intended to be a model starting point for analyses at the country level, but country-specific cost structures, epidemiological needs, and national priorities will generally lead to definitions of EUHC that differ from country to country and from the model in this Review. DCP3 is particularly relevant as achievement of EUHC relies increasingly on greater domestic finance, with global developmental assistance in health focusing more on global public goods. In addition to assessing effects on mortality, DCP3 looked at outcomes of EUHC not encompassed by the disability-adjusted life-year metric and related cost-effectiveness analyses. The other objectives included financial protection (potentially better provided upstream by keeping people out of the hospital rather than downstream by paying their hospital bills for them), stillbirths averted, palliative care, contraception, and child physical and intellectual growth. The first 1000 days after conception are highly important for child development, but the next 7000 days are likewise important and often neglected.

Background Existing implementation measures developed in high-income countries may have limited appropriateness for use within low- and middle-income countries (LMIC). In response, researchers at Johns Hopkins University began developing the Mental Health Implementation Science Tools (mhIST) in 2013 to assess priority implementation determinants and outcomes across four key stakeholder groups—consumers, providers, organization leaders, and policy makers—with dedicated versions of scales for each group. These were field tested and refined in several contexts, and criterion validity was established in Ukraine. The Consumer and Provider mhIST have since grown in popularity in mental health research, outpacing psychometric evaluation. Our objective was to establish the cross-context psychometric properties of these versions and inform future revisions. Methods We compiled secondary data from seven studies across six LMIC—Colombia, Myanmar, Pakistan, Thailand, Ukraine, and Zambia—to evaluate the psychometric performance of the Consumer and Provider mhIST. We used exploratory factor analysis to identify dimensionality, factor structure, and item loadings for each scale within each stakeholder version. We also used alignment analysis (i.e., multi-group confirmatory factor analysis) to estimate measurement invariance and differential item functioning of the Consumer scales across the six countries. Results All but one scale within the Provider and Consumer versions had Cronbach’s alpha greater than 0.8. Exploratory factor analysis indicated most scales were multidimensional, with factors generally aligning with a priori subscales for the Provider version; the Consumer version has no predefined subscales. Alignment analysis of the Consumer mhIST indicated a range of measurement invariance for scales across settings ( R 2 0.46 to 0.77). Several items were identified for potential revision due to participant nonresponse or low or cross- factor loadings. We found only one item, which asked consumers whether their intervention provider was available when needed, to have differential item functioning in both intercept and loading. Conclusion We provide evidence that the Consumer and Provider versions of the mhIST are internally valid and reliable across diverse contexts and stakeholder groups for mental health research in LMIC. We recommend the instrument be revised based on these analyses and future research examine instrument utility by linking measurement to other outcomes of interest.