Estimating health care delivery system value for each US state and testing key associations.

OBJECTIVE: To estimate health care systems' value in treating major illnesses for each US state and identify system characteristics associated with value. DATA SOURCES: Annual condition-specific death and incidence estimates for each US state from the Global Burden Disease 2019 Study and annual health care spending per person for each state from the National Health Expenditure Accounts. STUDY DESIGN: Using non-linear meta-stochastic frontier analysis, mortality incidence ratios for 136 major treatable illnesses were regressed separately on per capita health care spending and key covariates such as age, obesity, smoking, and educational attainment. State- and year-specific inefficiency estimates were extracted for each health condition and combined to create a single estimate of health care delivery system value for each US state for each year, 1991-2014. The association between changes in health care value and changes in 23 key health care system characteristics and state policies was measured. DATA COLLECTION/EXTRACTION METHODS: Not applicable. PRINCIPAL FINDINGS: US state with relatively high spending per person or relatively poor health-outcomes were shown to have low health care delivery system value. New Jersey, Maryland, Florida, Arizona, and New York attained the highest value scores in 2014 (81 [95% uncertainty interval 72-88], 80 [72-87], 80 [71-86], 77 [69-84], and 77 [66-85], respectively), after controlling for health care spending, age, obesity, smoking, physical activity, race, and educational attainment. Greater market concentration of hospitals and of insurers were associated with worse health care value (p-value ranging from <0.01 to 0.02). Higher hospital geographic density and use were also associated with worse health care value (p-value ranging from 0.03 to 0.05). Enrollment in Medicare Advantage HMOs was associated with better value, as was more generous Medicaid income eligibility (p-value 0.04 and 0.01). CONCLUSIONS: Substantial variation in the value of health care exists across states. Key health system characteristics such as market concentration and provider density were associated with value.

Healthcare spending in U.S. emergency departments by health condition, 2006-2016.

BACKGROUND: Healthcare spending in the emergency department (ED) setting has received intense focus from policymakers in the United States (U.S.). Relatively few studies have systematically evaluated ED spending over time or disaggregated ED spending by policy-relevant groups, including health condition, age, sex, and payer to inform these discussions. This study's objective is to estimate ED spending trends in the U.S. from 2006 to 2016, by age, sex, payer, and across 154 health conditions and assess ED spending per visit over time. METHODS AND FINDINGS: This observational study utilized the National Emergency Department Sample, a nationally representative sample of hospital-based ED visits in the U.S. to measure healthcare spending for ED care. All spending estimates were adjusted for inflation and presented in 2016 U.S. Dollars. Overall ED spending was $79.2 billion (CI, $79.2 billion-$79.2 billion) in 2006 and grew to $136.6 billion (CI, $136.6 billion-$136.6 billion) in 2016, representing a population-adjusted annualized rate of change of 4.4% (CI, 4.4%-4.5%) as compared to total healthcare spending (1.4% [CI, 1.4%-1.4%]) during that same ten-year period. The percentage of U.S. health spending attributable to the ED has increased from 3.9% (CI, 3.9%-3.9%) in 2006 to 5.0% (CI, 5.0%-5.0%) in 2016. Nearly equal parts of ED spending in 2016 was paid by private payers (49.3% [CI, 49.3%-49.3%]) and public payers (46.9% [CI, 46.9%-46.9%]), with the remainder attributable to out-of-pocket spending (3.9% [CI, 3.9%-3.9%]). In terms of key groups, the majority of ED spending was allocated among females (versus males) and treat-and-release patients (versus those hospitalized); those between age 20-44 accounted for a plurality of ED spending. Road injuries, falls, and urinary diseases witnessed the highest levels of ED spending, accounting for 14.1% (CI, 13.1%-15.1%) of total ED spending in 2016. ED spending per visit also increased over time from $660.0 (CI, $655.1-$665.2) in 2006 to $943.2 (CI, $934.3-$951.6) in 2016, or at an annualized rate of 3.4% (CI, 3.3%-3.4%). CONCLUSIONS: Though ED spending accounts for a relatively small portion of total health system spending in the U.S., ED spending is sizable and growing. Understanding which diseases are driving this spending is helpful for informing value-based reforms that can impact overall health care costs.

US Health Care Spending by Race and Ethnicity, 2002-2016.

Importance: Measuring health care spending by race and ethnicity is important for understanding patterns in utilization and treatment. Objective: To estimate, identify, and account for differences in health care spending by race and ethnicity from 2002 through 2016 in the US. Design, Setting, and Participants: This exploratory study included data from 7.3 million health system visits, admissions, or prescriptions captured in the Medical Expenditure Panel Survey (2002-2016) and the Medicare Current Beneficiary Survey (2002-2012), which were combined with the insured population and notified case estimates from the National Health Interview Survey (2002; 2016) and health care spending estimates from the Disease Expenditure project (1996-2016). Exposure: Six mutually exclusive self-reported race and ethnicity groups. Main Outcomes and Measures: Total and age-standardized health care spending per person by race and ethnicity for each year from 2002 through 2016 by type of care. Health care spending per notified case by race and ethnicity for key diseases in 2016. Differences in health care spending across race and ethnicity groups were decomposed into differences in utilization rate vs differences in price and intensity of care. Results: In 2016, an estimated $2.4 trillion (95% uncertainty interval [UI], $2.4 trillion-$2.4 trillion) was spent on health care across the 6 types of care included in this study. The estimated age-standardized total health care spending per person in 2016 was $7649 (95% UI, $6129-$8814) for American Indian and Alaska Native (non-Hispanic) individuals; $4692 (95% UI, $4068-$5202) for Asian, Native Hawaiian, and Pacific Islander (non-Hispanic) individuals; $7361 (95% UI, $6917-$7797) for Black (non-Hispanic) individuals; $6025 (95% UI, $5703-$6373) for Hispanic individuals; $9276 (95% UI, $8066-$10 601) for individuals categorized as multiple races (non-Hispanic); and $8141 (95% UI, $8038-$8258) for White (non-Hispanic) individuals, who accounted for an estimated 72% (95% UI, 71%-73%) of health care spending. After adjusting for population size and age, White individuals received an estimated 15% (95% UI, 13%-17%; P < .001) more spending on ambulatory care than the all-population mean. Black (non-Hispanic) individuals received an estimated 26% (95% UI, 19%-32%; P < .001) less spending than the all-population mean on ambulatory care but received 19% (95% UI, 3%-32%; P = .02) more on inpatient and 12% (95% UI, 4%-24%; P = .04) more on emergency department care. Hispanic individuals received an estimated 33% (95% UI, 26%-37%; P < .001) less spending per person on ambulatory care than the all-population mean. Asian, Native Hawaiian, and Pacific Islander (non-Hispanic) individuals received less spending than the all-population mean on all types of care except dental (all P < .001), while American Indian and Alaska Native (non-Hispanic) individuals had more spending on emergency department care than the all-population mean (estimated 90% more; 95% UI, 11%-165%; P = .04), and multiple-race (non-Hispanic) individuals had more spending on emergency department care than the all-population mean (estimated 40% more; 95% UI, 19%-63%; P = .006). All 18 of the statistically significant race and ethnicity spending differences by type of care corresponded with differences in utilization. These differences persisted when controlling for underlying disease burden. Conclusions and Relevance: In the US from 2002 through 2016, health care spending varied by race and ethnicity across different types of care even after adjusting for age and health conditions. Further research is needed to determine current health care spending by race and ethnicity, including spending related to the COVID-19 pandemic.

An Implementation Research Approach to Re-orient Health Supply Chains Toward an Equity Agenda in the COVID-19 Era.

The Covid-19 pandemic has exposed critical inequities in global healthcare supply chains and the need for these systems to be analyzed and reoriented with an equity lens. Implementation research methodology can guide the use of evidence-based interventions to re-orient health supply chains towards equity and optimize health outcomes. Using this approach, private and public sector entities can adapt their strategies to focus not just on efficiency and cost savings but ensuring that vulnerable populations have access to essential medications, vaccines, and supplies. Findings can inform regulations that address supply chain inequities at the global level, strengthen existing systems to fill structural gaps at the national level, and address contextual challenges at the subnational level. This methodology can help account for historical practices from prior health initiatives, identify contemporary barriers and facilitators for positive change, and have applicability to the Covid-19 pandemic and ongoing vaccine distribution efforts. An implementation research approach is critical in equipping health supply chains with a path for more resilient and equitable distribution of necessary supplies, vaccines, and delivery of care.

Addressing the mental health needs of children affected by HIV in Rwanda: validation of a rapid depression screening tool for children 7-14 years old.

BACKGROUND: Depression in children presents a significant health burden to society and often co-exists with chronic illnesses, such as human immunodeficiency virus (HIV). Research has demonstrated that 10-37% of children and adolescents living with HIV also suffer from depression. Low-and-middle income countries (LMICs) shoulder a disproportionate burden of HIV among other health challenges, but reliable estimates of co-morbid depression are lacking in these settings. Prior studies in Rwanda, a LMIC of 12 million people in East Africa, found that 25% of children living with HIV met criteria for depression. Though depression may negatively affect adherence to HIV treatment among children and adolescents, most LMICs fail to routinely screen children for mental health problems due to a shortage of trained health care providers. While some screening tools exist, they can be costly to implement in resource-constrained settings and are often lacking a contextual appropriateness. METHODS: Relying on international guidelines for diagnosing depression, Rwandan health experts developed a freely available, open-access Child Depression Screening Tool (CDST). To validate this tool in Rwanda, a sample of 296 children with a known diagnosis of HIV between ages 7-14 years were recruited as study participants. In addition to completing the CDST, all participants were evaluated by a mental health professional using a structured clinical interview. The validity of the CDST was assessed in terms of sensitivity, specificity, and a receiver operating characteristic (ROC) curve. RESULTS: This analysis found that depression continues to be a co-morbid condition among children living with HIV in Rwanda. For identifying these at-risk children, the CDST had a sensitivity of 88.1% and specificity of 96.5% in identifying risk for depression among children living with HIV at a cutoff score of 6 points. This corresponded with an area under the ROC curve of 92.3%. CONCLUSIONS: This study provides evidence that the CDST is a valid tool for screening depression among children affected by HIV in a resource-constrained setting. As an open-access and freely available tool in LMICs, the CDST can allow any health practitioner to identify children at risk of depression and refer them in a timely manner to more specialized mental health services. Future work can show if and how this tool has the potential to be useful in screening depression in children suffering from other chronic illnesses.

Assessing Catastrophic Health Expenditures Among Uninsured People Who Seek Care in US Hospital-Based Emergency Departments.

Importance: Uninsured people uniquely rely on the emergency department (ED) for care as they are less likely to have access to lower-cost alternatives. Prior work has demonstrated that most uninsured patients are at risk of catastrophic health expenditure (CHE) after being hospitalized for life-saving care. The risk of CHE for a single treat-and-release ED visit that does not result in a hospitalization among uninsured patient encounters is currently unknown. Objective: To estimate the overall national risk of CHE among uninsured patients after a single treat-and-release ED visit from 2006 through 2017, and to characterize this risk across key traits. Design Setting and Population: This cross-sectional study is based on a nationally representative sample of hospital-based ED visits between 2006 and 2017 in the United States (US) from the Nationwide Emergency Department Sample (NEDS). It examined outpatient ED visits among uninsured patients. Main Outcomes and Measures: Risk of CHE for ED care defined as an ED charge that exceeds 40% of one's estimated annual post-subsistence income. Results: From 2006 to 2017, there were 41.7 million NEDS encounters that met inclusion criteria for this analysis, equating to a nationally weighted estimate of 184.6 million uninsured treat-and-release ED encounters over this period. The median ED charge for a single treat-and-release encounter grew from $842 in 2006 to $2033 by 2017. Approximately 1 in 5 uninsured patients (18% [95% CI, 18.0%-18.0%]) were at risk of CHE for a single treat-and-release ED visit over the study period. This estimated CHE risk increased from 13.6% (95% CI, 13.6%-13.6%) in 2006 to 22.6% (95% CI, 22.6%-22.7%) in 2017. Those living in the lowest income quartile faced a disproportionate share of this risk, with nearly 1 in 3 (28.5% [95% CI, 28.5%-28.6%]) facing CHE risk in 2017. In 2017, an estimated 3.2 million patient encounters nationally were at risk of CHE after a single treat-and-release ED visit. Conclusions and Relevance: This cross-sectional analysis from 2006 to 2017 of 184.6 million uninsured treat-and-release visits found that 1 in 5 uninsured patient encounters are at risk for CHE. This risk has grown over time. Future policies designed to improve access for unscheduled care must consider the unique role of the ED as the de facto safety net and ensure that uninsured patients are not at undue risk of financial harm for seeking care.

Medical Student Mobilization During a Crisis: Lessons From a COVID-19 Medical Student Response Team.

PROBLEM: On March 17, 2020, the Association of American Medical Colleges recommended the suspension of all direct patient contact responsibilities for medical students because of the COVID-19 pandemic. Given this change, medical students nationwide had to grapple with how and where they could fill the evolving needs of their schools' affiliated clinical sites, physicians, patients, and the community. APPROACH: At Harvard Medical School (HMS), student leaders created a COVID-19 Medical Student Response Team to: (1) develop a student-led organizational structure that would optimize students' ability to efficiently mobilize interested peers in the COVID-19 response, both clinically and in the community, in a strategic, safe, smart, and resource-conscious way; and (2) serve as a liaison with the administration and hospital leaders to identify evolving needs and rapidly engage students in those efforts. OUTCOMES: Within a week of its inception, the COVID-19 Medical Student Response Team had more than 500 medical student volunteers from HMS and had shared the organizational framework of the response team with multiple medical schools across the country. The HMS student volunteers joined any of the 4 virtual committees to complete this work: Education for the Medical Community, Education for the Broader Community, Activism for Clinical Support, and Community Activism. NEXT STEPS: The COVID-19 Medical Student Response Team helped to quickly mobilize hundreds of students and has been integrated into HMS's daily workflow. It may serve as a useful model for other schools and hospitals seeking medical student assistance during the COVID-19 pandemic. Next steps include expanding the initiative further, working with the leaders of response teams at other medical schools to coordinate efforts, and identifying new areas of need at local hospitals and within nearby communities that might benefit from medical student involvement as the pandemic evolves.

US Health Care Spending by Payer and Health Condition, 1996-2016.

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.

Trends in burden and risk factors associated with childhood stunting in Rwanda from 2000 to 2015: policy and program implications.

BACKGROUND: Rwanda has made substantial economic progress over the past two decades. However, evidence suggests that malnutrition among children remains high in spite of this progress. This study aims to examine trends and potential risk factors associated with childhood stunting from 2000 to 2015 in Rwanda. METHODS: Data for this study come from the 2000 to 2015 Rwanda's Demographic and Health Surveys (DHS), a cross-sectional, population-based survey that is conducted every 5 years. Following prior work, we define stunting based on age and weight as reported in the DHS. We assess the overall prevalence of stunting among children under the age of 5 in Rwanda and then conduct bivariate analyses across a range of policy-relevant demographic, socioeconomic, and health variables. We then incorporate key variables in a multivariable analysis to identify those factors that are independently associated with stunting. RESULTS: The prevalence of stunting among children under the age of 5 in Rwanda declined from 2000 (47.4%) to 2015 (38.3%), though rates were relatively stagnant between 2000 and 2010. Factors associated with higher rates of stunting included living in the lowest wealth quintile, having a mother with limited education, having a mother that smoked, being of the male sex, and being of low-birth weight. CONCLUSIONS: Though overall stunting rates have improved nationally, these gains have been uneven. Furthering ongoing national policies to address these disparities while also working to reduce the overall risk of malnutrition will be necessary for Rwanda to reach its overall economic and health equity goals.

Creating a pathway for public hospital accreditation in Rwanda: progress, challenges and lessons learned.

QUALITY PROBLEM: Weaknesses in the quality of care delivered at hospitals translates into patient safety challenges and causes unnecessary harm. Low-and-middle-income countries disproportionately shoulder the burden of poor quality of hospital care. INITIAL ASSESSMENT: In the early 2000s, Rwanda implemented a performance-based financing (PBF) system to improve quality and increase the quantity of care delivered at its public hospitals. PBF evaluations identified quality gaps that prompted a movement to pursue an accreditation process for public hospitals. CHOICE OF SOLUTION: Since it was prohibitively costly to implement an accreditation program overseen by an external entity to all of Rwanda's public hospitals, the Ministry of Health developed a set of standards for a national 3-Level accreditation program. IMPLEMENTATION: In 2012, Rwanda launched the first phase of the national accreditation system at five public hospitals. The program was then expected to expand across the remainder of the public hospitals throughout the country. EVALUATION: Out of Rwanda's 43 public hospitals, a total of 24 hospitals have achieved Level 1 status of the accreditation process and 4 have achieved Level 2 status of the accreditation process. LESSONS LEARNED: Linking the program to the country's existing PBF program increased compliance and motivation for participation, especially for those who were unfamiliar with accreditation principles. Furthermore, identifying dedicated quality improvement officers at each hospital has been important for improving engagement in the program. Lastly, to improve upon this process, there are ongoing efforts to develop a non-governmental accreditation entity to oversee this process for Rwanda's health system moving forward.

Leveraging massive open online courses to expand quality of healthcare education to health practitioners in Rwanda.

Improving the quality of healthcare delivery is increasingly a global health priority. However, quality improvement training opportunities that provide theoretical foundations and basic skills for patient safety and other quality initiatives have been limited or historically out of reach, especially in low-and-middle income countries (LMICs). To address this gap, the Harvard Initiative on Global Health Quality (HIGHQ) created and launched a massive open online course (MOOC) in 2014 focused on patient safety and quality of care using the edX platform. More than 30 000 students from across 195 countries registered for the online course. This paper summarises an innovative educational partnership between the course team and one of these countries, Rwanda, to develop a blended-learning model to bolster participation in this new course among Rwandan healthcare professionals. Although a small country, Rwanda was among the top performing countries for attracting course registrants and was the leading country for the proportion of enrollees who ultimately completed the course. Further, half (21 of 42) of Rwanda's district hospitals opted to appoint a PH555x course facilitator at their site to help lead regular meetings and discussions about the course content at their facility. The majority of Rwandan enrollees were health professionals (63%) and 81% reported that PH555x was their first experience taking an online course. Among those participating in the 'flipped' component at hospital sites, 94% reported that the course helped them to think of specific ways to improve healthcare quality at their facility. In this paper, we describe this innovative public-private educational model, challenges to implementation and lessons learned that may be helpful for future MOOC developers who wish to augment learning opportunities among healthcare professionals in LMICs.

Transitioning to Country Ownership of HIV Programs in Rwanda.

Agnes Binagwaho and colleagues describe how Rwanda achieved country ownership of its HIV programs.

Perceived barriers to the development of modern public health in Bulgaria: a qualitative study.

OBJECTIVES: This qualitative investigation documents Bulgarian perspectives on public health following its accession to the European Union (EU) and explores perceived obstacles to the modernization of public health sciences to more effectively address the country's high rates of premature avoidable mortality. METHODS: 28 semi-structured interviews were conducted throughout Bulgaria in April 2007 with Bulgarian academics, clinicians, policymakers and students in Sofia, Varna and Pleven. Full transcripts were subjected to formal thematic analysis. RESULTS: Respondents identified various barriers to the development and modernization to public health infrastructures in Bulgaria that were classified by four key interlinked themes: (1) institutional and political, (2) financial, (3) dearth of local epidemiological studies, and (4) insufficient public health capacity. CONCLUSIONS: This study is the first to explore specific perspectives and beliefs regarding barriers to the development, modernization, and utilization of public health sciences in Bulgaria. Although the reorientation and strengthening of public health institutions are unlikely to proceed without resistance, optimism for improvement in this field exists now that Bulgaria has joined the EU.