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Lessons learned from implementing evaluations for Gavi, the Vaccine Alliance and the Global Fund for AIDS, Tuberculosis, and Malaria can help inform the design and implementation of ongoing or future evaluations of complex interventions. We share 5 lessons distilled from over 7 years of experience implementing evaluations in 7 countries., Key Findings We present 5 key lessons distilled from 7 years of experience implementing evaluations in 7 countries, which include the importance of: Including an inception phase to engage stakeholders and inform a relevant, useful evaluation designAligning on the degree to which the evaluation is embedded in the program implementationMonitoring programmatic, organizational, or contextual changes and adapting the evaluation accordinglyHiring evaluators with mixed-methods expertise and using tools and approaches that facilitate mixing methodsContextualizing recommendations and clearly communicating their underlying strength of evidence Key Implications Global health initiatives, particularly those funding or implementing complex interventions, should consider embedding evaluations to understand how and why the programs are working to adapt as necessary and maximize impact.Evaluators of complex interventions should continue to share lessons learned related to balancing stakeholder priorities, aligning on “breadth” versus “depth” of the evaluation scope and ensuring use of the evaluation findings., Introduction: As global health programs have become increasingly complex, corresponding evaluations must be designed to assess the full complexity of these programs. Gavi and the Global Fund have commissioned 2 such evaluations to assess the full spectrum of their investments using a prospective mixed-methods approach. We aim to describe lessons learned from implementing these evaluations. Methods: This article presents a synthesis of lessons learned based on the Gavi and Global Fund prospective mixed-methods evaluations, with each evaluation considered a case study. The lessons are based on the evaluation team’s experience from over 7 years (2013–2020) implementing these evaluations. The Centers for Disease Control and Prevention Framework for Evaluation in Public Health was used to ground the identification of lessons learned. Results: We identified 5 lessons learned that build on existing evaluation best practices and include a mix of practical and conceptual considerations. The lessons cover the importance of (1) including an inception phase to engage stakeholders and inform a relevant, useful evaluation design; (2) aligning on the degree to which the evaluation is embedded in the program implementation; (3) monitoring programmatic, organizational, or contextual changes and adapting the evaluation accordingly; (4) hiring evaluators with mixed-methods expertise and using tools and approaches that facilitate mixing methods; and (5) contextualizing recommendations and clearly communicating their underlying strength of evidence. Conclusion: Global health initiatives, particularly those leveraging complex interventions, should consider embedding evaluations to understand how and why the programs are working. These initiatives can learn from the lessons presented here to inform the design and implementation of such evaluations.

Background: In many low and middle-income countries (LMICs), timely access to emergency healthcare services is limited. In urban settings, traffic can have a significant impact on travel time, leading to life-threatening delays for time-sensitive injuries and medical emergencies. In this study, we examined travel times to hospitals in Nairobi, Kenya, one of the largest and most congested cities in the developing world. Methods: We used a network approach to estimate average minimum travel times to different types of hospitals (e.g. ownership and level of care) in Nairobi under both congested and uncongested traffic conditions. We also examined the correlation between travel time and socioeconomic status. Results: We estimate the average minimum travel time during uncongested traffic conditions to any level 4 health facility (primary hospitals) or above in Nairobi to be 4.5 min (IQR 2.5–6.1). Traffic added an average of 9.0 min (a 200% increase). In uncongested conditions, we estimate an average travel time of 7.9 min (IQR 5.1–10.4) to level 5 facilities (secondary hospitals) and 11.6 min (IQR 8.5–14.2) to Kenyatta National Hospital, the only level 6 facility (tertiary hospital) in the country. Traffic congestion added an average of 13.1 and 16.0 min (166% and 138% increase) to travel times to level 5 and level 6 facilities, respectively. For individuals living below the poverty line, we estimate that preferential use of public or faith-based facilities could increase travel time by as much as 65%. Conclusion: Average travel times to health facilities capable of providing emergency care in Nairobi are quite low, but traffic congestion double or triple estimated travel times. Furthermore, we estimate significant disparities in timely access to care for those individuals living under the poverty line who preferentially seek care in public or faith-based facilities. Keywords: Emergency care, Kenya, Traffic, Poverty

Background: Healthcare workers are at the forefront of the COVID-19 pandemic and it is essential to monitor the relative infection rate of this group, as compared to workers in other occupations. This study aimed to produce estimates of the relative incidence ratio between healthcare workers and workers in non-healthcare occupations. Methods: Analysis of cross-sectional data from a daily, web-based survey of 1,788,795 Facebook users from September 6, 2020 to October 18, 2020. Participants were Facebook users in the United States aged 18 and above who were tested for COVID-19 because of an employer or school requirement in the past 14 days. The exposure variable was a self-reported history of working in healthcare in the past four weeks and the main outcome was a self-reported positive test for COVID-19. Results: On October 18, 2020, in the United States, there was a relative COVID-19 incidence ratio of 0.7 (95% UI 0.6 to 0.8) between healthcare workers and workers in non-healthcare occupations. Conclusions: Currently in the United States, healthcare workers have a substantially and significantly lower COVID-19 incidence rate than workers in non-healthcare occupations.

Background: The Global Fund to Fight AIDS, Tuberculosis and Malaria was founded in 2002 as a public-private partnership between governments, the private sector, civil society, and populations affected by the three diseases. A key principle of the Global Fund is country ownership in accessing funding through “engagement of in-country stakeholders, including key and vulnerable populations, communities, and civil society.” Research documenting whether diverse stakeholders are actually engaged and on how stakeholder engagement affects processes and outcomes of grant applications is limited. Objective: To examine representation during the 2017 Global Fund application process in the Democratic Republic of the Congo (DRC) and Uganda and the benefits and drawbacks of partnership to the process. Methods: We developed a mixed-methods social network survey to measure network structure and assess perceptions of how working together in partnership with other individuals/organizations affected perceived effectiveness, efficiency, and country ownership of the application process. Surveys were administered from December 2017–May 2018, initially to a set of central actors, followed by any individuals named during the surveys (up to 10) as collaborators. Network analyses were conducted using R. Findings: Collaborators spanning many organizations and expertise areas contributed to the 2017 applications (DRC: 152 nodes, 237 ties; Uganda: 118 nodes, 241 ties). Participation from NGOs and civil society representatives was relatively strong, with most of their ties being to different organization types, Uganda (63%), and DRC (67%), highlighting their collaborative efforts across the network. Overall, the perceived benefits of partnership were high, including very strong ratings for effectiveness in both countries. Perceived drawbacks of partnership were minimal; however, less than half of respondents thought partnership helped reduce transaction costs or financial costs, suggesting an inclusive and participatory process may come with short-term efficiency tradeoffs. Conclusions: Social network analysis can be useful for identifying who is included and excluded from the process, which can support efforts to ensure stronger, more meaningful engagement in future Global Fund application processes.

Importance US health care spending has continued to increase and now accounts for 18% of the US economy, although little is known about how spending on each health condition varies by payer, and how these amounts have changed over time. Objective To estimate US spending on health care according to 3 types of payers (public insurance [including Medicare, Medicaid, and other government programs], private insurance, or out-of-pocket payments) and by health condition, age group, sex, and type of care for 1996 through 2016. Design and Setting Government budgets, insurance claims, facility records, household surveys, and official US records from 1996 through 2016 were collected to estimate spending for 154 health conditions. Spending growth rates (standardized by population size and age group) were calculated for each type of payer and health condition. Exposures Ambulatory care, inpatient care, nursing care facility stay, emergency department care, dental care, and purchase of prescribed pharmaceuticals in a retail setting. Main Outcomes and Measures National spending estimates stratified by health condition, age group, sex, type of care, and type of payer and modeled for each year from 1996 through 2016. Results Total health care spending increased from an estimated $1.4 trillion in 1996 (13.3% of gross domestic product [GDP]; $5259 per person) to an estimated $3.1 trillion in 2016 (17.9% of GDP; $9655 per person); 85.2% of that spending was included in this study. In 2016, an estimated 48.0% (95% CI, 48.0%-48.0%) of health care spending was paid by private insurance, 42.6% (95% CI, 42.5%-42.6%) by public insurance, and 9.4% (95% CI, 9.4%-9.4%) by out-of-pocket payments. In 2016, among the 154 conditions, low back and neck pain had the highest amount of health care spending with an estimated $134.5 billion (95% CI, $122.4-$146.9 billion) in spending, of which 57.2% (95% CI, 52.2%-61.2%) was paid by private insurance, 33.7% (95% CI, 30.0%-38.4%) by public insurance, and 9.2% (95% CI, 8.3%-10.4%) by out-of-pocket payments. Other musculoskeletal disorders accounted for the second highest amount of health care spending (estimated at $129.8 billion [95% CI, $116.3-$149.7 billion]) and most had private insurance (56.4% [95% CI, 52.6%-59.3%]). Diabetes accounted for the third highest amount of the health care spending (estimated at $111.2 billion [95% CI, $105.7-$115.9 billion]) and most had public insurance (49.8% [95% CI, 44.4%-56.0%]). Other conditions estimated to have substantial health care spending in 2016 were ischemic heart disease ($89.3 billion [95% CI, $81.1-$95.5 billion]), falls ($87.4 billion [95% CI, $75.0-$100.1 billion]), urinary diseases ($86.0 billion [95% CI, $76.3-$95.9 billion]), skin and subcutaneous diseases ($85.0 billion [95% CI, $80.5-$90.2 billion]), osteoarthritis ($80.0 billion [95% CI, $72.2-$86.1 billion]), dementias ($79.2 billion [95% CI, $67.6-$90.8 billion]), and hypertension ($79.0 billion [95% CI, $72.6-$86.8 billion]). The conditions with the highest spending varied by type of payer, age, sex, type of care, and year. After adjusting for changes in inflation, population size, and age groups, public insurance spending was estimated to have increased at an annualized rate of 2.9% (95% CI, 2.9%-2.9%); private insurance, 2.6% (95% CI, 2.6%-2.6%); and out-of-pocket payments, 1.1% (95% CI, 1.0%-1.1%). Conclusions and Relevance Estimates of US spending on health care showed substantial increases from 1996 through 2016, with the highest increases in population-adjusted spending by public insurance. Although spending on low back and neck pain, other musculoskeletal disorders, and diabetes accounted for the highest amounts of spending, the payers and the rates of change in annual spending growth rates varied considerably.

Because of a soaring number of opioid-related deaths during the past decade, opioid use disorder has become a prominent issue in both the scientific literature and lay press. Although most of the focus within the emergency medicine community has been on opioid prescribing-specifically, on reducing the incidence of opioid prescribing and examining alternative pain treatment-interest is heightening in identifying and managing patients with opioid use disorder in an effective and evidence-based manner. In this clinical review article, we examine current strategies for identifying patients with opioid use disorder, the treatment of patients with acute opioid withdrawal syndrome, approaches to medication-assisted therapy, and the transition of patients with opioid use disorder from the emergency department to outpatient services.

Background Non-communicable diseases (NCDs) represent the largest, and fastest growing, burden of disease in India. This study aimed to quantify levels of diagnosis, treatment, and control among hypertensive and diabetic patients, and to describe demand- and supply-side barriers to hypertension and diabetes diagnosis and care in two Indian districts, Shimla and Udaipur. Methods We conducted household and health facility surveys, as well as qualitative focus group discussions and interviews. The household survey randomly sampled individuals aged 15 and above in rural and urban areas in both districts. The survey included questions on NCD knowledge, history, and risk factors. Blood pressure, weight, height, and blood glucose measurements were obtained. The health facility survey was administered in 48 health care facilities, focusing on NCD diagnosis and treatment capacity, including staffing, equipment, and pharmaceuticals. Qualitative data was collected through semi-structured key informant interviews with health professionals and public health officials, as well as focus groups with patients and community members. Results Among 7181 individuals, 32% either reported a history of hypertension or were found to have a systolic blood pressure ≥ 140 mmHg and/or diastolic ≥90 mmHg. Only 26% of those found to have elevated blood pressure reported a prior diagnosis, and just 42% of individuals with a prior diagnosis of hypertension were found to be normotensive. A history of diabetes or an elevated blood sugar (Random blood glucose (RBG) ≥200 mg/dl or fasting blood glucose (FBG) ≥126 mg/dl) was noted in 7% of the population. Among those with an elevated RBG/FBG, 59% had previously received a diagnosis of diabetes. Only 60% of diabetics on treatment were measured with a RBG

Objective To assess the changes in patient outcome prediction and hospital performance ranking when incorporating diagnoses as risk adjusters rather than comorbidity indices. Data Sources Healthcare Cost and Utilization Project State Inpatient Databases for New York State, 2005–2009. Study Design Conducted tree-based classification for mortality and readmission by incorporating discrete patient diagnoses as predictors, comparing with traditional comorbidity indices such as those used for Centers for Medicare and Medicaid Services (CMS) outcome models. Principal Findings Diagnosis codes as predictors increased predictive accuracy 5.6 percent (95% CI: 4.5–6.9 percent) relative to CMS condition categories for heart failure 30-day mortality. Most other outcomes exhibited statistically significant accuracy gains and facility ranking shifts. Sensitivity analysis showed improvements even when predictors were limited to only the diagnoses included in CMS models. Conclusions Discretizing patient severity information beyond the levels of traditional comorbidity indices improves patient outcome predictions and substantially shifts facility rankings.

Objectives Increased demand for antiretroviral therapy (ART) services combined with plateaued levels of development assistance for HIV/AIDS requires that national ART programmes monitor programme effectiveness. In this pilot study, we compared commonly utilised performance metrics of 12- and 24-month retention with rates of viral load (VL) suppression at 15 health facilities in Uganda. Methods Retrospective chart review from which 12- and 24-month retention rates were estimated, and parallel HIV RNA VL testing on consecutive adult patients who presented to clinics and had been on ART for a minimum of six months. Rates of VL suppression were then calculated at each facility and compared to retention rates to assess the correlation between performance metrics. Multilevel logistic regression models predicting VL suppression and 12- and 24-month retention were constructed to estimate facility effects. Results We collected VL samples from 2961 patients and found that 88% had a VL ≤1000 copies/ml. Facility rates of VL suppression varied between 77% and 96%. When controlling for patient mix, a significant variation in facility performance persisted. Retention rates at 12 and 24 months were 91% and 79%, respectively, with a comparable facility-level variation. However, neither 12-month (ρ = 0.16) nor 24-month (ρ = -0.19) retention rates were correlated with facility rates of VL suppression. Conclusions Retaining patients in care and suppressing VL are both critical outcomes. Given the lack of correlation noted in this study, the utilisation of VL monitoring may be necessary to truly assess the effectiveness of health facilities delivering ART services.

IntroductionUnderstanding how to deliver interventions more effectively is a growing emphasis in Global Health. Simultaneously, health system strengthening is a key component to improving delivery. As a result, it is challenging to evaluate programme implementation while reflecting real-world complexity. We present our experience in using a health systems modelling approach as part of a mixed-methods evaluation and describe applications of these models.MethodsWe developed a framework for how health systems translate financial inputs into health outcomes, with in-country and international experts. We collated available data to measure framework indicators and developed models for malaria in Democratic Republic of the Congo (DRC), and tuberculosis in Guatemala and Senegal using Bayesian structural equation modelling. We conducted several postmodelling analyses: measuring efficiency, assessing bottlenecks, understanding mediation, analysing the cascade of care and measuring subnational effectiveness.ResultsThe DRC model indicated a strong relationship between shipment of commodities and utilisation thereof. In Guatemala, the strongest model coefficients were more evenly distributed. Results in Senegal varied most, but pathways related to community care had the strongest relationships. In DRC, we used model results to estimate the end-to-end cost of delivering commodities. In Guatemala, we used model results to identify potential bottlenecks and understand mediation. In Senegal, we used model results to identify potential weak links in the cascade of care, and explore subnationally.ConclusionThis study demonstrates a complementary modelling approach to traditional evaluation methods. Although these models have limitations, they can be applied in a variety of ways to gain greater insight into implementation and functioning of health service delivery.

ObjectiveTo conduct a landscape assessment of public knowledge of cardiovascular disease risk factors and acute myocardial infarction symptoms, cardiopulmonary resuscitation (CPR) and automated external defibrillator (AED) awareness and training in three underserved communities in Brazil.MethodsA cross-sectional, population-based survey of non-institutionalised adults age 30 or greater was conducted in three municipalities in Eastern Brazil. Data were analysed as survey-weighted percentages of the sampled populations.Results3035 surveys were completed. Overall, one-third of respondents was unable to identify at least one cardiovascular disease risk factor and 25% unable to identify at least one myocardial infarction symptom. A minority of respondents had received training in CPR or were able to identify an AED. Low levels of education and low socioeconomic status were consistent predictors of lower knowledge levels of cardiovascular disease risk factors, acute coronary syndrome symptoms and CPR and AED use.ConclusionsIn three municipalities in Eastern Brazil, overall public knowledge of cardiovascular disease risk factors and symptoms, as well as knowledge of appropriate CPR and AED use was low. Our findings indicate the need for interventions to improve public knowledge and response to acute cardiovascular events in Brazil as a first step towards improving health outcomes in this population. Significant heterogeneity in knowledge seen across sites and socioeconomic strata indicates a need to appropriately target such interventions.

BACKGROUND: Understanding the patterns of HIV/AIDS epidemics is crucial to tracking and monitoring the progress of prevention and control efforts in countries. We provide a comprehensive assessment of the levels and trends of HIV/AIDS incidence, prevalence, mortality, and coverage of antiretroviral therapy (ART) for 1980-2017 and forecast these estimates to 2030 for 195 countries and territories.METHODS: We determined a modelling strategy for each country on the basis of the availability and quality of data. For countries and territories with data from population-based seroprevalence surveys or antenatal care clinics, we estimated prevalence and incidence using an open-source version of the Estimation and Projection Package-a natural history model originally developed by the UNAIDS Reference Group on Estimates, Modelling, and Projections. For countries with cause-specific vital registration data, we corrected data for garbage coding (ie, deaths coded to an intermediate, immediate, or poorly defined cause) and HIV misclassification. We developed a process of cohort incidence bias adjustment to use information on survival and deaths recorded in vital registration to back-calculate HIV incidence. For countries without any representative data on HIV, we produced incidence estimates by pulling information from observed bias in the geographical region. We used a re-coded version of the Spectrum model (a cohort component model that uses rates of disease progression and HIV mortality on and off ART) to produce age-sex-specific incidence, prevalence, and mortality, and treatment coverage results for all countries, and forecast these measures to 2030 using Spectrum with inputs that were extended on the basis of past trends in treatment scale-up and new infections.FINDINGS: Global HIV mortality peaked in 2006 with 1·95 million deaths (95% uncertainty interval 1·87-2·04) and has since decreased to 0·95 million deaths (0·91-1·01) in 2017. New cases of HIV globally peaked in 1999 (3·16 million, 2·79-3·67) and since then have gradually decreased to 1·94 million (1·63-2·29) in 2017. These trends, along with ART scale-up, have globally resulted in increased prevalence, with 36·8 million (34·8-39·2) people living with HIV in 2017. Prevalence of HIV was highest in southern sub-Saharan Africa in 2017, and countries in the region had ART coverage ranging from 65·7% in Lesotho to 85·7% in eSwatini. Our forecasts showed that 54 countries will meet the UNAIDS target of 81% ART coverage by 2020 and 12 countries are on track to meet 90% ART coverage by 2030. Forecasted results estimate that few countries will meet the UNAIDS 2020 and 2030 mortality and incidence targets.INTERPRETATION: Despite progress in reducing HIV-related mortality over the past decade, slow decreases in incidence, combined with the current context of stagnated funding for related interventions, mean that many countries are not on track to reach the 2020 and 2030 global targets for reduction in incidence and mortality. With a growing population of people living with HIV, it will continue to be a major threat to public health for years to come. The pace of progress needs to be hastened by continuing to expand access to ART and increasing investments in proven HIV prevention initiatives that can be scaled up to have population-level impact.FUNDING: Bill & Melinda Gates Foundation, National Institute of Mental Health of the US National Institutes of Health (NIH), and the National Institute on Aging of the NIH.

Background The HealthRise initiative seeks to implement and evaluate innovative community-based strategies for diabetes, hypertension and hypercholesterolemia along the entire continuum of care (CoC)-from awareness and diagnosis, through treatment and control. In this study, we present baseline findings from HealthRise South Africa, identifying gaps in the CoC, as well as key barriers to care for non-communicable diseases (NCDs). Methods This mixed-methods needs assessment utilized national household data, health facility surveys, focus group discussions, and key informant interviews in Umgungundlovu and Pixley ka Seme districts. Risk factor and disease prevalence were estimated from the South Africa National Health and Nutrition Examination Survey. Health facility surveys were conducted at 86 facilities, focusing on essential intervention, medications and standard treatment guidelines. Quantitative results are presented descriptively, and qualitative data was analyzed using a framework approach. Results 46.8% of the population in Umgungundlovu and 51.0% in Pixley ka Seme were hypertensive. Diabetes was present in 11.0% and 9.7% of the population in Umgungundlovu and Pixley ka Seme. Hypercholesterolemia was more common in Pixley ka Seme (17.3% vs. 11.1%). Women and those of Indian descent were more likely to have diabetes. More than half of the population was found to be overweight, and binge drinking, inactivity and smoking were all common. More than half of patients with hypertension were unaware of their disease status (51.6% in Pixley ka Seme and 51.3% in Umgungundlovu), while the largest gap in the diabetes CoC occurred between initiation of treatment and achieving disease control. Demand-side barriers included lack of transportation, concerns about confidentiality, perceived discrimination and long wait times. Supply-side barriers included limited availability of testing equipment, inadequate staffing, and pharmaceutical stock outs. Conclusion In this baseline assessment of two South African health districts we found high rates of undiagnosed hypercholesterolemia and hypertension, and poor control of hypercholesterolemia, hypertension, and diabetes. The HealthRise Initiative will need to address key supply- and demand-side barriers in an effort to improve important NCD outcomes.

Background Considerable debate exists concerning the effects of antiretroviral therapy (ART) service scale-up on non-HIV services and overall health system performance in sub-Saharan Africa. In this study, we examined whether ART services affected trends in non-ART outpatient department (OPD) visits in Kenya and Uganda. Methods Using a nationally representative sample of health facilities in Kenya and Uganda, we estimated the effect of ART programs on OPD visits from 2007 to 2012. We modeled the annual percent change in non-ART OPD visits using hierarchical mixed-effects linear regressions, controlling for a range of facility characteristics. We used four different constructs of ART services to capture the different ways in which the presence, growth, overall, and relative size of ART programs may affect non-ART OPD services. Results Our final sample included 321 health facilities (140 in Kenya and 181 in Uganda). On average, OPD and ART visits increased steadily in Kenya and Uganda between 2007 and 2012. For facilities where ART services were not offered, the average annual increase in OPD visits was 4·2% in Kenya and 13·5% in Uganda. Among facilities that provided ART services, we found average annual OPD volume increases of 7·2% in Kenya and 5·6% in Uganda, with simultaneous annual increases of 13·7% and 12·5% in ART volumes. We did not find a statistically significant relationship between annual changes in OPD services and the presence, growth, overall, or relative size of ART services. However, in a subgroup analysis, we found that Ugandan hospitals that offered ART services had statistically significantly less growth in OPD visits than Ugandan hospitals that did not provide ART services. Conclusions Our findings suggest that ART services in Kenya and Uganda did not have a statistically significant deleterious effects on OPD services between 2007 and 2012, although subgroup analyses indicate variation by facility type. Our findings are encouraging, particularly given recent recommendations for universal access to ART, demonstrating that expanding ART services is not inherently linked to declines in other health services in sub-Saharan Africa.

OBJECTIVE Health care spending on diabetes in the U.S. has increased dramatically over the past several decades. This research describes health care spending on diabetes to quantify how that spending has changed from 1996 to 2013 and to determine what drivers are increasing spending. RESEARCH DESIGN AND METHODS Spending estimates were extracted from the Institute for Health Metrics and Evaluation’s Disease Expenditure 2013 database. Estimates were produced for each year from 1996 to 2013 for each of 38 age and sex groups and six types of care. Data on disease burden were extracted from the Global Burden of Disease 2016 study. We analyzed the drivers of spending by measuring the impact of population growth and aging and changes in diabetes prevalence, service utilization, and spending per encounter. RESULTS Spending on diabetes in the U.S. increased from $37 billion (95% uncertainty interval $32–$42 billion) in 1996 to $101 billion ($97–$107 billion) in 2013. The greatest amount of health care spending on diabetes in 2013 occurred in prescribed retail pharmaceuticals (57.6% [53.8–62.1%] of spending growth) followed by ambulatory care (23.5% [21.7–25.7%]). Between 1996 and 2013, pharmaceutical spending increased by 327.0% (222.9–456.6%). This increase can be attributed to changes in demography, increased disease prevalence, increased service utilization, and, especially, increases in spending per encounter, which increased pharmaceutical spending by 144.0% (87.3–197.3%) between 1996 and 2013. CONCLUSIONS Health care spending on diabetes in the U.S. has increased, and spending per encounter has been the biggest driver. This information can help policy makers who are attempting to control future spending on diabetes.

ObjectiveTo inform interventions targeted towards reducing mortality from acute myocardial infarction (AMI) and sudden cardiac arrest in three megacities in China and India, a baseline assessment of public knowledge, attitudes and practices was performed.MethodsA household survey, supplemented by focus group and individual interviews, was used to assess public understanding of cardiovascular disease (CVD) risk factors, AMI symptoms, cardiopulmonary resuscitation (CPR) and automated external defibrillators (AEDs). Additionally, information was collected on emergency service utilisation and associated barriers to care.Results5456 household surveys were completed. Hypertension was most commonly recognised among CVD risk factors in Beijing and Shanghai (68% and 67%, respectively), while behavioural risk factors were most commonly identified in Bangalore (smoking 91%; excessive alcohol consumption 64%). Chest pain/discomfort was reported by at least 60% of respondents in all cities as a symptom of AMI, but 21% of individuals in Bangalore could not name a single symptom. In Beijing, Shanghai and Bangalore, 26%, 15% and 3% of respondents were trained in CPR, respectively. Less than one-quarter of participants in all cities recognised an AED. Finally, emergency service utilisation rates were low, and many individuals expressed concern about the quality of prehospital care.ConclusionsOverall, we found low to modest knowledge of CVD risk factors and AMI symptoms, infrequent CPR training and little understanding of AEDs. Interventions will need to focus on basic principles of CVD and its complications in order for patients to receive timely and appropriate care for acute cardiac events.

Introduction: Alcohol use disorders (AUD) place a significant burden on individuals and society. Theemergency department (ED) offers a unique opportunity to address AUD with brief screening tools andearly intervention. We undertook a systematic review of the effectiveness of ED brief interventions forpatients identified through screening who are at risk for AUD, and the effectiveness of these interventionsat reducing alcohol intake and preventing alcohol-related injuries. Methods: We conducted systematic electronic database searches to include randomized controlled trialsof AUD screening, brief intervention, referral, and treatment (SBIRT), from January 1966 to April 2016. Twoauthors graded and abstracted data from each included paper. Results: We found 35 articles that had direct relevance to the ED with enrolled patients ranging from12 to 70 years of age. Multiple alcohol screening tools were used to identify patients at risk for AUD.Brief intervention (BI) and brief motivational intervention (BMI) strategies were compared to a controlintervention or usual care. Thirteen studies enrolling a total of 5,261 participants reported significantdifferences between control and intervention groups in their main alcohol-outcome criteria of number ofdrink days and number of units per drink day. Sixteen studies showed a reduction of alcohol consumptionin both the control and intervention groups; of those, seven studies did not identify a significant interventioneffect for the main outcome criteria, but nine observed some significant differences between BI and controlconditions for specific subgroups (i.e., adolescents and adolescents with prior history of drinking anddriving; women 22 years old or younger; low or moderate drinkers); or secondary outcome criteria (e.g.reduction in driving while intoxicated). Conclusion: Moderate-quality evidence of targeted use of BI/BMI in the ED showed a small reduction inalcohol use in low or moderate drinkers, a reduction in the negative consequences of use (such as injury),and a decline in ED repeat visits for adults and children 12 years of age and older. BI delivered in the EDappears to have a short-term effect in reducing at-risk drinking.

Importance Health care spending on children in the United States continues to rise, yet little is known about how this spending varies by condition, age and sex group, and type of care, nor how these patterns have changed over time. Objective To provide health care spending estimates for children and adolescents 19 years and younger in the United States from 1996 through 2013, disaggregated by condition, age and sex group, and type of care. Evidence Review Health care spending estimates were extracted from the Institute for Health Metrics and Evaluation Disease Expenditure 2013 project database. This project, based on 183 sources of data and 2.9 billion patient records, disaggregated health care spending in the United States by condition, age and sex group, and type of care. Annual estimates were produced for each year from 1996 through 2013. Estimates were adjusted for the presence of comorbidities and are reported using inflation-adjusted 2015 US dollars. Findings From 1996 to 2013, health care spending on children increased from $149.6 (uncertainty interval [UI], 144.1-155.5) billion to $233.5 (UI, 226.9-239.8) billion. In 2013, the largest health condition leading to health care spending for children was well-newborn care in the inpatient setting. Attention-deficit/hyperactivity disorder and well-dental care (including dental check-ups and orthodontia) were the second and third largest conditions, respectively. Spending per child was greatest for infants younger than 1 year, at $11 741 (UI, 10 799-12 765) in 2013. Across time, health care spending per child increased from $1915 (UI, 1845-1991) in 1996 to $2777 (UI, 2698-2851) in 2013. The greatest areas of growth in spending in absolute terms were ambulatory care among all types of care and inpatient well-newborn care, attention-deficit/hyperactivity disorder, and asthma among all conditions. Conclusions and Relevance These findings provide health policy makers and health care professionals with evidence to help guide future spending. Some conditions, such as attention-deficit/hyperactivity disorder and inpatient well-newborn care, had larger health care spending growth rates than other conditions.

Objective Heart failure is a major cause of disease burden in sub-Saharan Africa (SSA). There is an urgent need for better strategies for heart failure management in this region. However, there is little information on the capacity to diagnose and treat heart failure in SSA. We aim to provide a better understanding of the capacity to diagnose and treat heart failure in Kenya and Uganda to inform policy planning and interventions. Methods We analysed data from a nationally representative survey of health facilities in Kenya and Uganda (197 health facilities in Uganda and 143 in Kenya). We report on the availability of cardiac diagnostic technologies and select medications for heart failure (β-blockers, ACE inhibitors and furosemide). Facility-level data were analysed by country and platform type (hospital vs ambulatory facilities). Results Functional and staffed radiography, ultrasound and ECG were available in less than half of hospitals in Kenya and Uganda combined. Of the hospitals surveyed, 49% of Kenyan and 77% of Ugandan hospitals reported availability of the heart failure medication package. ACE inhibitors were only available in 51% of Kenyan and 79% of Ugandan hospitals. Almost one-third of the hospitals in each country had a stock-out of at least one of the medication classes in the prior quarter. Conclusions Few facilities in Kenya and Uganda were prepared to diagnose and manage heart failure. Medication shortages and stock-outs were common. Our findings call for increased investment in cardiac care to reduce the growing burden of heart failure.

Objectives There are many barriers impeding the conduct of high-quality emergency care research, particularly in low- and middle-income countries. Several of these barriers were originally outlined in 2013 as part of the Academic Emergency Medicine Global Health and Emergency Care Consensus Conference. This paper seeks to establish a broader consensus on the barriers to emergency care research globally and proposes a comprehensive array of new recommendations to overcome these barriers. Methods An electronic survey was conducted of a purposive sample of Global Emergency Medicine research experts from around the world to describe the major challenges and solutions to conducting emergency care research in low resource settings and rank them by importance. The Global Emergency Medicine Think Tank Clinical Research Working Group at the Society for Academic Emergency Medicine 2016 Annual Meeting utilized a modified Delphi technique for consensus-based decision making to categorize and expand upon these barriers and develop a comprehensive array of proposed solutions. Results The working group identified four broad categories of barriers to conducting emergency care research globally, including 1) the limited availability of research personnel, particularly those with prior research training; 2) logistical barriers and lack of standardization of data collection; 3) ethical barriers to conducting research in resource-limited settings, particularly when no local institutional review board is available; and 4) the relative dearth of funding for global emergency care research. Proposed solutions included building a diverse and interdisciplinary research team structured to promote mentorship of junior researchers; utilizing local research assistants or technological tools such as telemedicine for language translation; making use of new tools such as mobile health (mHealth) to standardize and streamline data collection; identifying alternatives to local institutional review board (IRB) approval and the use of community consent when appropriate; and increased advocacy for global emergency care research funding. Conclusions Significant barriers to the conduct of high-quality global emergency care research persist, and innovative strategies need to be adopted in order to promote and grow the field of global emergency care research. This paper provides a global consensus on the most important barriers identified, as well as recommendations for cost-effective strategies for overcoming these barriers with the overall goal of promoting high-quality research and improving emergency care worldwide. This article is protected by copyright. All rights reserved.

Background Since 2000, international funding for HIV has supported scaling up antiretroviral therapy (ART) in sub-Saharan Africa. However, such funding has stagnated for years, threatening the sustainability and reach of ART programs amid efforts to achieve universal treatment. Improving health system efficiencies, particularly at the facility level, is an increasingly critical avenue for extending limited resources for ART; nevertheless, the potential impact of increased facility efficiency on ART capacity remains largely unknown. Through the present study, we sought to quantify facility-level technical efficiency across countries, assess potential determinants of efficiency, and predict the potential for additional ART expansion. Methods Using nationally-representative facility datasets from Kenya, Uganda and Zambia, and measures adjusting for structural quality, we estimated facility-level technical efficiency using an ensemble approach that combined restricted versions of Data Envelopment Analysis and Stochastic Distance Function. We then conducted a series of bivariate and multivariate regression analyses to evaluate possible determinants of higher or lower technical efficiency. Finally, we predicted the potential for ART expansion across efficiency improvement scenarios, estimating how many additional ART visits could be accommodated if facilities with low efficiency thresholds reached those levels of efficiency. Results In each country, national averages of efficiency fell below 50 % and facility-level efficiency markedly varied. Among facilities providing ART, average efficiency scores spanned from 50 % (95 % uncertainty interval (UI), 48–62 %) in Uganda to 59 % (95 % UI, 53–67 %) in Zambia. Of the facility determinants analyzed, few were consistently associated with higher or lower technical efficiency scores, suggesting that other factors may be more strongly related to facility-level efficiency. Based on observed facility resources and an efficiency improvement scenario where all facilities providing ART reached 80 % efficiency, we predicted a 33 % potential increase in ART visits in Kenya, 62 % in Uganda, and 33 % in Zambia. Given observed resources in facilities offering ART, we estimated that 459,000 new ART patients could be seen if facilities in these countries reached 80 % efficiency, equating to a 40 % increase in new patients. Conclusions Health facilities in Kenya, Uganda, and Zambia could notably expand ART services if the efficiency with which they operate increased. Improving how facility resources are used, and not simply increasing their quantity, has the potential to substantially elevate the impact of global health investments and reduce treatment gaps for people living with HIV. Electronic supplementary material The online version of this article (doi:10.1186/s12916-016-0653-z) contains supplementary material, which is available to authorized users.

International audience; BACKGROUND: Reliable and timely information on the leading causes of death in populations, and how these are changing, is a crucial input into health policy debates. In the Global Burden of Diseases, Injuries, and Risk Factors Study 2010 (GBD 2010), we aimed to estimate annual deaths for the world and 21 regions between 1980 and 2010 for 235 causes, with uncertainty intervals (UIs), separately by age and sex. METHODS: We attempted to identify all available data on causes of death for 187 countries from 1980 to 2010 from vital registration, verbal autopsy, mortality surveillance, censuses, surveys, hospitals, police records, and mortuaries. We assessed data quality for completeness, diagnostic accuracy, missing data, stochastic variations, and probable causes of death. We applied six different modelling strategies to estimate cause-specific mortality trends depending on the strength of the data. For 133 causes and three special aggregates we used the Cause of Death Ensemble model (CODEm) approach, which uses four families of statistical models testing a large set of different models using different permutations of covariates. Model ensembles were developed from these component models. We assessed model performance with rigorous out-of-sample testing of prediction error and the validity of 95% UIs. For 13 causes with low observed numbers of deaths, we developed negative binomial models with plausible covariates. For 27 causes for which death is rare, we modelled the higher level cause in the cause hierarchy of the GBD 2010 and then allocated deaths across component causes proportionately, estimated from all available data in the database. For selected causes (African trypanosomiasis, congenital syphilis, whooping cough, measles, typhoid and parathyroid, leishmaniasis, acute hepatitis E, and HIV/AIDS), we used natural history models based on information on incidence, prevalence, and case-fatality. We separately estimated cause fractions by aetiology for diarrhoea, lower respiratory infections, and meningitis, as well as disaggregations by subcause for chronic kidney disease, maternal disorders, cirrhosis, and liver cancer. For deaths due to collective violence and natural disasters, we used mortality shock regressions. For every cause, we estimated 95% UIs that captured both parameter estimation uncertainty and uncertainty due to model specification where CODEm was used. We constrained cause-specific fractions within every age-sex group to sum to total mortality based on draws from the uncertainty distributions. FINDINGS: In 2010, there were 52*8 million deaths globally. At the most aggregate level, communicable, maternal, neonatal, and nutritional causes were 24*9% of deaths worldwide in 2010, down from 15*9 million (34*1%) of 46*5 million in 1990. This decrease was largely due to decreases in mortality from diarrhoeal disease (from 2*5 to 1*4 million), lower respiratory infections (from 3*4 to 2*8 million), neonatal disorders (from 3*1 to 2*2 million), measles (from 0*63 to 0*13 million), and tetanus (from 0*27 to 0*06 million). Deaths from HIV/AIDS increased from 0*30 million in 1990 to 1*5 million in 2010, reaching a peak of 1*7 million in 2006. Malaria mortality also rose by an estimated 19*9% since 1990 to 1*17 million deaths in 2010. Tuberculosis killed 1*2 million people in 2010. Deaths from non-communicable diseases rose by just under 8 million between 1990 and 2010, accounting for two of every three deaths (34*5 million) worldwide by 2010. 8 million people died from cancer in 2010, 38% more than two decades ago; of these, 1*5 million (19%) were from trachea, bronchus, and lung cancer. Ischaemic heart disease and stroke collectively killed 12*9 million people in 2010, or one in four deaths worldwide, compared with one in five in 1990; 1*3 million deaths were due to diabetes, twice as many as in 1990. The fraction of global deaths due to injuries (5*1 million deaths) was marginally higher in 2010 (9*6%) compared with two decades earlier (8*8%). This was driven by a 46% rise in deaths worldwide due to road traffic accidents (1*3 million in 2010) and a rise in deaths from falls. Ischaemic heart disease, stroke, chronic obstructive pulmonary disease (COPD), lower respiratory infections, lung cancer, and HIV/AIDS were the leading causes of death in 2010. Ischaemic heart disease, lower respiratory infections, stroke, diarrhoeal disease, malaria, and HIV/AIDS were the leading causes of years of life lost due to premature mortality (YLLs) in 2010, similar to what was estimated for 1990, except for HIV/AIDS and preterm birth complications. YLLs from lower respiratory infections and diarrhoea decreased by 45-54% since 1990; ischaemic heart disease and stroke YLLs increased by 17-28%. Regional variations in leading causes of death were substantial. Communicable, maternal, neonatal, and nutritional causes still accounted for 76% of premature mortality in sub-Saharan Africa in 2010. Age standardised death rates from some key disorders rose (HIV/AIDS, Alzheimer's disease, diabetes mellitus, and chronic kidney disease in particular), but for most diseases, death rates fell in the past two decades; including major vascular diseases, COPD, most forms of cancer, liver cirrhosis, and maternal disorders. For other conditions, notably malaria, prostate cancer, and injuries, little change was noted. INTERPRETATION: Population growth, increased average age of the world's population, and largely decreasing age-specific, sex-specific, and cause-specific death rates combine to drive a broad shift from communicable, maternal, neonatal, and nutritional causes towards non-communicable diseases. Nevertheless, communicable, maternal, neonatal, and nutritional causes remain the dominant causes of YLLs in sub-Saharan Africa. Overlaid on this general pattern of the epidemiological transition, marked regional variation exists in many causes, such as interpersonal violence, suicide, liver cancer, diabetes, cirrhosis, Chagas disease, African trypanosomiasis, melanoma, and others. Regional heterogeneity highlights the importance of sound epidemiological assessments of the causes of death on a regular basis. FUNDING: Bill & Melinda Gates Foundation.

BACKGROUND: The Millennium Declaration in 2000 brought special global attention to HIV, tuberculosis, and malaria through the formulation of Millennium Development Goal (MDG) 6. The Global Burden of Disease 2013 study provides a consistent and comprehensive approach to disease estimation for between 1990 and 2013, and an opportunity to assess whether accelerated progress has occured since the Millennium Declaration.METHODS: To estimate incidence and mortality for HIV, we used the UNAIDS Spectrum model appropriately modified based on a systematic review of available studies of mortality with and without antiretroviral therapy (ART). For concentrated epidemics, we calibrated Spectrum models to fit vital registration data corrected for misclassification of HIV deaths. In generalised epidemics, we minimised a loss function to select epidemic curves most consistent with prevalence data and demographic data for all-cause mortality. We analysed counterfactual scenarios for HIV to assess years of life saved through prevention of mother-to-child transmission (PMTCT) and ART. For tuberculosis, we analysed vital registration and verbal autopsy data to estimate mortality using cause of death ensemble modelling. We analysed data for corrected case-notifications, expert opinions on the case-detection rate, prevalence surveys, and estimated cause-specific mortality using Bayesian meta-regression to generate consistent trends in all parameters. We analysed malaria mortality and incidence using an updated cause of death database, a systematic analysis of verbal autopsy validation studies for malaria, and recent studies (2010-13) of incidence, drug resistance, and coverage of insecticide-treated bednets.FINDINGS: Globally in 2013, there were 1·8 million new HIV infections (95% uncertainty interval 1·7 million to 2·1 million), 29·2 million prevalent HIV cases (28·1 to 31·7), and 1·3 million HIV deaths (1·3 to 1·5). At the peak of the epidemic in 2005, HIV caused 1·7 million deaths (1·6 million to 1·9 million). Concentrated epidemics in Latin America and eastern Europe are substantially smaller than previously estimated. Through interventions including PMTCT and ART, 19·1 million life-years (16·6 million to 21·5 million) have been saved, 70·3% (65·4 to 76·1) in developing countries. From 2000 to 2011, the ratio of development assistance for health for HIV to years of life saved through intervention was US$4498 in developing countries. Including in HIV-positive individuals, all-form tuberculosis incidence was 7·5 million (7·4 million to 7·7 million), prevalence was 11·9 million (11·6 million to 12·2 million), and number of deaths was 1·4 million (1·3 million to 1·5 million) in 2013. In the same year and in only individuals who were HIV-negative, all-form tuberculosis incidence was 7·1 million (6·9 million to 7·3 million), prevalence was 11·2 million (10·8 million to 11·6 million), and number of deaths was 1·3 million (1·2 million to 1·4 million). Annualised rates of change (ARC) for incidence, prevalence, and death became negative after 2000. Tuberculosis in HIV-negative individuals disproportionately occurs in men and boys (versus women and girls); 64·0% of cases (63·6 to 64·3) and 64·7% of deaths (60·8 to 70·3). Globally, malaria cases and deaths grew rapidly from 1990 reaching a peak of 232 million cases (143 million to 387 million) in 2003 and 1·2 million deaths (1·1 million to 1·4 million) in 2004. Since 2004, child deaths from malaria in sub-Saharan Africa have decreased by 31·5% (15·7 to 44·1). Outside of Africa, malaria mortality has been steadily decreasing since 1990.INTERPRETATION: Our estimates of the number of people living with HIV are 18·7% smaller than UNAIDS's estimates in 2012. The number of people living with malaria is larger than estimated by WHO. The number of people living with HIV, tuberculosis, or malaria have all decreased since 2000. At the global level, upward trends for malaria and HIV deaths have been reversed and declines in tuberculosis deaths have accelerated. 101 countries (74 of which are developing) still have increasing HIV incidence. Substantial progress since the Millennium Declaration is an encouraging sign of the effect of global action.FUNDING: Bill & Melinda Gates Foundation.

Human trafficking is a significant human rights problem that is often associated with psychological and physical violence. There is no demographic that is spared from human trafficking. Traffickers maintain control of victims through physical, sexual, and emotional violence and manipulation. Because victims of trafficking seek medical attention for the medical and psychological consequences of assault and neglected health conditions, emergency clinicians are in a unique position to recognize victims and intervene. Evaluation of possible trafficking victims is challenging because patients who have been exploited rarely self-identify. This article outlines the clinical approach to the identification and treatment of a potential victim of human trafficking in the emergency department. Emergency practitioners should maintain a high index of suspicion when evaluating patients who appear to be at risk for abuse and violence, and assess for specific indicators of trafficking. Potential victims should be evaluated with a multidisciplinary and patient-centered technique. Furthermore, emergency practitioners should be aware of national and local resources to guide the approach to helping identified victims. Having established protocols for victim identification, care, and referrals can greatly facilitate health care providers' assisting this population.

International audience; BACKGROUND: Measuring disease and injury burden in populations requires a composite metric that captures both premature mortality and the prevalence and severity of ill-health. The 1990 Global Burden of Disease study proposed disability-adjusted life years (DALYs) to measure disease burden. No comprehensive update of disease burden worldwide incorporating a systematic reassessment of disease and injury-specific epidemiology has been done since the 1990 study. We aimed to calculate disease burden worldwide and for 21 regions for 1990, 2005, and 2010 with methods to enable meaningful comparisons over time. METHODS: We calculated DALYs as the sum of years of life lost (YLLs) and years lived with disability (YLDs). DALYs were calculated for 291 causes, 20 age groups, both sexes, and for 187 countries, and aggregated to regional and global estimates of disease burden for three points in time with strictly comparable definitions and methods. YLLs were calculated from age-sex-country-time-specific estimates of mortality by cause, with death by standardised lost life expectancy at each age. YLDs were calculated as prevalence of 1160 disabling sequelae, by age, sex, and cause, and weighted by new disability weights for each health state. Neither YLLs nor YLDs were age-weighted or discounted. Uncertainty around cause-specific DALYs was calculated incorporating uncertainty in levels of all-cause mortality, cause-specific mortality, prevalence, and disability weights. FINDINGS: Global DALYs remained stable from 1990 (2*503 billion) to 2010 (2*490 billion). Crude DALYs per 1000 decreased by 23% (472 per 1000 to 361 per 1000). An important shift has occurred in DALY composition with the contribution of deaths and disability among children (younger than 5 years of age) declining from 41% of global DALYs in 1990 to 25% in 2010. YLLs typically account for about half of disease burden in more developed regions (high-income Asia Pacific, western Europe, high-income North America, and Australasia), rising to over 80% of DALYs in sub-Saharan Africa. In 1990, 47% of DALYs worldwide were from communicable, maternal, neonatal, and nutritional disorders, 43% from non-communicable diseases, and 10% from injuries. By 2010, this had shifted to 35%, 54%, and 11%, respectively. Ischaemic heart disease was the leading cause of DALYs worldwide in 2010 (up from fourth rank in 1990, increasing by 29%), followed by lower respiratory infections (top rank in 1990; 44% decline in DALYs), stroke (fifth in 1990; 19% increase), diarrhoeal diseases (second in 1990; 51% decrease), and HIV/AIDS (33rd in 1990; 351% increase). Major depressive disorder increased from 15th to 11th rank (37% increase) and road injury from 12th to 10th rank (34% increase). Substantial heterogeneity exists in rankings of leading causes of disease burden among regions. INTERPRETATION: Global disease burden has continued to shift away from communicable to non-communicable diseases and from premature death to years lived with disability. In sub-Saharan Africa, however, many communicable, maternal, neonatal, and nutritional disorders remain the dominant causes of disease burden. The rising burden from mental and behavioural disorders, musculoskeletal disorders, and diabetes will impose new challenges on health systems. Regional heterogeneity highlights the importance of understanding local burden of disease and setting goals and targets for the post-2015 agenda taking such patterns into account. Because of improved definitions, methods, and data, these results for 1990 and 2010 supersede all previously published Global Burden of Disease results. FUNDING: Bill & Melinda Gates Foundation.