Population health impact, cost-effectiveness, and affordability of community-based HIV treatment and monitoring in South Africa: A health economics modelling study.

Community-based delivery and monitoring of antiretroviral therapy (ART) for HIV has the potential to increase viral suppression for individual- and population-level health benefits. However, the cost-effectiveness and budget impact are needed for public health policy. We used a mathematical model of HIV transmission in KwaZulu-Natal, South Africa, to estimate population prevalence, incidence, mortality, and disability-adjusted life-years (DALYs) from 2020 to 2060 for two scenarios: 1) standard clinic-based HIV care and 2) five-yearly home testing campaigns with community ART for people not reached by clinic-based care. We parameterised model scenarios using observed community-based ART efficacy. Using a health system perspective, we evaluated incremental cost-effectiveness and net health benefits using a threshold of $750/DALY averted. In a sensitivity analysis, we varied the discount rate; time horizon; costs for clinic and community ART, hospitalisation, and testing; and the proportion of the population receiving community ART. Uncertainty ranges (URs) were estimated across 25 best-fitting parameter sets. By 2060, community ART following home testing averted 27.9% (UR: 24.3-31.5) of incident HIV infections, 27.8% (26.8-28.8) of HIV-related deaths, and 18.7% (17.9-19.7) of DALYs compared to standard of care. Adolescent girls and young women aged 15-24 years experienced the greatest reduction in incident HIV (30.7%, 27.1-34.7). In the first five years (2020-2024), community ART required an additional $44.9 million (35.8-50.1) annually, representing 14.3% (11.4-16.0) of the annual HIV budget. The cost per DALY averted was $102 (85-117) for community ART compared with standard of care. Providing six-monthly refills instead of quarterly refills further increased cost-effectiveness to $78.5 per DALY averted (62.9-92.8). Cost-effectiveness was robust to sensitivity analyses. In a high-prevalence setting, scale-up of decentralised ART dispensing and monitoring can provide large population health benefits and is cost-effective in preventing death and disability due to HIV.

Varied Health Spending Growth Across US States Was Associated With Incomes, Price Levels, And Medicaid Expansion, 2000-19.

Little is known about health care spending variation across the US for recent years. To estimate health spending by state and payer, we combined data from the government's State Health Expenditure Accounts, which have estimates through 2014, with other primary data on spending. In 2019 state-specific per person spending ranged from $7,250 to $14,500. After adjustment for inflation, annualized per person spending growth for each state ranged from 1.0 percent in Washington, D.C., to 4.2 percent in South Dakota between 2013 and 2019. The factors that explained the most variation across states were incomes (25.3 percent) and consumer prices (21.7 percent). Medicaid expansion was associated with increases in total spending per person, although the median of spending in expansion states showed slower growth in out-of-pocket spending than the median in nonexpansion states. Contemporary estimates of state health spending are valuable for tracking divergent expenditure trajectories in the US and assessing the associated factors.

Toward mandatory health insurance in low-income countries? An analysis of claims data in Tanzania.

Many low-income countries are in the process of scaling up health insurance with the goal of achieving universal coverage. However, little is known about the usage and financial sustainability of mandatory health insurance. This study analyzes 26 million claims submitted to the Tanzanian National Health Insurance Fund (NHIF), which covers two million public servants for whom public insurance is mandatory, to understand insurance usage patterns, cost drivers, and financial sustainability. We find that in 2016, half of policyholders used a health service within a single year, with an average annual cost of 33 US$ per policyholder. About 10% of the population was responsible for 80% of the health costs, and women, middle-age and middle-income groups had the highest costs. Out of 7390 health centers, only five health centers are responsible for 30% of total costs. Estimating the expected health expenditures for the entire population based on the NHIF cost structure, we find that for a sustainable national scale-up, policy makers will have to decide between reducing the health benefit package or increasing revenues. We also show that the cost structure of a mandatory insurance scheme in a low-income country differs substantially from high-income settings. Replication studies for other countries are warranted.

Costs of community-wide mass drug administration and school-based deworming for soil-transmitted helminths: evidence from a randomised controlled trial in Benin, India and Malawi.

OBJECTIVES: Current guidelines for the control of soil-transmitted helminths (STH) recommend deworming children and other high-risk groups, primarily using school-based deworming (SBD) programmes. However, targeting individuals of all ages through community-wide mass drug administration (cMDA) may interrupt STH transmission in some settings. We compared the costs of cMDA to SBD to inform decision-making about future updates to STH policy. DESIGN: We conducted activity-based microcosting of cMDA and SBD for 2 years in Benin, India and Malawi within an ongoing cMDA trial. SETTING: Field sites and collaborating research institutions. PRIMARY AND SECONDARY OUTCOMES: We calculated total financial and opportunity costs and costs per treatment administered (unit costs in 2019 USD ($)) from the service provider perspective, including costs related to community drug distributors and other volunteers. RESULTS: On average, cMDA unit costs were more expensive than SBD in India ($1.17 vs $0.72) and Malawi ($2.26 vs $1.69), and comparable in Benin ($2.45 vs $2.47). cMDA was more expensive than SBD in part because most costs (~60%) were 'supportive costs' needed to deliver treatment with high coverage, such as additional supervision and electronic data capture. A smaller fraction of cMDA costs (~30%) was routine expenditures (eg, drug distributor allowances). The remaining cMDA costs (~10%) were opportunity costs of staff and volunteer time. A larger percentage of SBD costs was opportunity costs for teachers and other government staff (between ~25% and 75%). Unit costs varied over time and were sensitive to the number of treatments administered. CONCLUSIONS: cMDA was generally more expensive than SBD. Accounting for local staff time (volunteers, teachers, health workers) in community programmes is important and drives higher cost estimates than commonly recognised in the literature. Costs may be lower outside of a trial setting, given a reduction in supportive costs used to drive higher treatment coverage and economies of scale. TRIAL REGISTRATION NUMBER: NCT03014167.

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.

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.

Costing interventions in the field: preliminary cost estimates and lessons learned from an evaluation of community-wide mass drug administration for elimination of soil-transmitted helminths in the DeWorm3 trial.

OBJECTIVE: To present a costing study integrated within the DeWorm3 multi-country field trial of community-wide mass drug administration (cMDA) for elimination of soil-transmitted helminths. DESIGN: Tailored data collection instruments covering resource use, expenditure and operational details were developed for each site. These were populated alongside field activities by on-site staff. Data quality control and validation processes were established. Programmed routines were used to clean, standardise and analyse data to derive costs of cMDA and supportive activities. SETTING: Field site and collaborating research institutions. PRIMARY AND SECONDARY OUTCOME MEASURES: A strategy for costing interventions in parallel with field activities was discussed. Interim estimates of cMDA costs obtained with the strategy were presented for one of the trial sites. RESULTS: The study demonstrated that it was both feasible and advantageous to collect data alongside field activities. Practical decisions on implementing the strategy and the trade-offs involved varied by site; trialists and local partners were key to tailoring data collection to the technical and operational realities in the field. The strategy capitalised on the established processes for routine financial reporting at sites, benefitted from high recall and gathered operational insight that facilitated interpretation of the estimates derived. The methodology produced granular costs that aligned with the literature and allowed exploration of relevant scenarios. In the first year of the trial, net of drugs, the incremental financial cost of extending deworming of school-aged children to the whole community in India site averaged US$1.14 (USD, 2018) per person per round. A hypothesised at-scale routine implementation scenario yielded a much lower estimate of US$0.11 per person treated per round. CONCLUSIONS: We showed that costing interventions alongside field activities offers unique opportunities for collecting rich data to inform policy toward optimising health interventions and for facilitating transfer of economic evidence from the field to the programme. TRIAL REGISTRATION NUMBER: NCT03014167; Pre-results.

Tracking total spending on tuberculosis by source and function in 135 low-income and middle-income countries, 2000-17: a financial modelling study.

BACKGROUND: Estimates of government spending and development assistance for tuberculosis exist, but less is known about out-of-pocket and prepaid private spending. We aimed to provide comprehensive estimates of total spending on tuberculosis in low-income and middle-income countries for 2000-17. METHODS: We extracted data on tuberculosis spending, unit costs, and health-care use from the WHO global tuberculosis database, Global Fund proposals and reports, National Health Accounts, the WHO-Choosing Interventions that are Cost-Effective project database, and the Institute for Health Metrics and Evaluation Development Assistance for Health Database. We extracted data from at least one of these sources for all 135 low-income and middle-income countries using the World Bank 2019 definitions. We estimated tuberculosis spending by source and function for notified (officially reported) and non-notified tuberculosis cases separately and combined, using spatiotemporal Gaussian process regression to fill in for missing data and estimate uncertainty. We aggregated estimates of government, out-of-pocket, prepaid private, and development assistance spending on tuberculosis to estimate total spending in 2019 US$. FINDINGS: Total spending on tuberculosis in 135 low-income and middle-income countries increased annually by 3·9% (95% CI 3·0 to 4·6), from $5·7 billion (5·2 to 6·5) in 2000 to $10·9 billion (10·3 to 11·8) in 2017. Government spending increased annually by 5·1% (4·4 to 5·7) between 2000 and 2017, and reached $6·9 billion (6·5 to 7·5) or 63·5% (59·2 to 66·8) of all tuberculosis spending in 2017. Of government spending, $5·8 billion (5·6 to 6·1) was spent on notified cases. Out-of-pocket spending decreased annually by 0·8% (-2·9 to 1·3), from $2·4 billion (1·9 to 3·1) in 2000 to $2·1 billion (1·6 to 2·7) in 2017. Development assistance for country-specific spending on tuberculosis increased from $54·6 million in 2000 to $1·1 billion in 2017. Administrative costs and development assistance for global projects related to tuberculosis care increased from $85·3 million in 2000 to $576·2 million in 2017. 30 high tuberculosis burden countries of low and middle income accounted for 73·7% (71·8-75·8) of tuberculosis spending in 2017. INTERPRETATION: Despite substantial increases since 2000, funding for tuberculosis is still far short of global financing targets and out-of-pocket spending remains high in resource-constrained countries, posing a barrier to patient's access to care and treatment adherence. Of the 30 countries with a high-burden of tuberculosis, just over half were primarily funded by government, while others, especially lower-middle-income and low-income countries, were still primarily dependent on development assistance for tuberculosis or out-of-pocket health spending. FUNDING: Bill & Melinda Gates Foundation.

Health systems and global progress towards malaria elimination, 2000-2016.

BACKGROUND: As more countries progress towards malaria elimination, a better understanding of the most critical health system features for enabling and supporting malaria control and elimination is needed. METHODS: All available health systems data relevant for malaria control were collated from 23 online data repositories. Principal component analysis was used to create domain specific health system performance measures. Multiple regression model selection approaches were used to identify key health systems predictors of progress in malaria control in the 2000-2016 period among 105 countries. Additional analysis was performed within malaria burden groups. RESULTS: There was large heterogeneity in progress in malaria control in the 2000-2016 period. In univariate analysis, several health systems factors displayed a strong positive correlation with reductions in malaria burden between 2000 and 2016. In multivariable models, delivery of routine services and hospital capacity were strongly predictive of reductions in malaria cases, especially in high burden countries. In low-burden countries approaching elimination, primary health center density appeared negatively associated with progress while hospital capacity was positively correlated with eliminating malaria. CONCLUSIONS: The findings presented in this manuscript suggest that strengthening health systems can be an effective strategy for reducing malaria cases, especially in countries with high malaria burden. Potential returns appear particularly high in the area of service delivery.

Screening for Tuberculosis Among Adults Newly Diagnosed With HIV in Sub-Saharan Africa: A Cost-Effectiveness Analysis.

OBJECTIVE: New tools, including light-emitting diode (LED) fluorescence microscopy and the molecular assay Xpert MTB/RIF, offer increased sensitivity for tuberculosis (TB) in persons with HIV but come with higher costs. Using operational data from rural Malawi, we explored the potential cost-effectiveness of on-demand screening for TB in low-income countries of Sub-Saharan Africa. DESIGN AND METHODS: Costs were empirically collected in 4 clinics and in 1 hospital using a microcosting approach, through direct interview and observation from the national TB program perspective. Using decision analysis, newly diagnosed persons with HIV were modeled as being screened by 1 of the 3 strategies: Xpert, LED, or standard of care (ie, at the discretion of the treating physician). RESULTS: Cost-effectiveness of TB screening among persons newly diagnosed with HIV was largely determined by 2 factors: prevalence of active TB among patients newly diagnosed with HIV and volume of testing. In facilities screening at least 50 people with a 6.5% prevalence of TB, or at least 500 people with a 2.5% TB prevalence, Xpert is likely to be cost-effective. At lower prevalence-including that observed in Malawi-LED microscopy may be the preferred strategy, whereas in settings of lower TB prevalence or small numbers of eligible patients, no screening may be reasonable (such that resources can be deployed elsewhere). CONCLUSIONS: TB screening at the point of HIV diagnosis may be cost-effective in low-income countries of Sub-Saharan Africa, but only if a relatively large population with high prevalence of TB can be identified for screening.

Preventing tuberculosis among HIV-infected pregnant women in Lesotho: the case for rolling out active case finding and isoniazid preventive therapy.

BACKGROUND: The Lesotho Ministry of Health issued guidelines on active case finding (ACF) for tuberculosis (TB) and isoniazid preventive therapy (IPT) in April 2011. ACF has been recommended in maternal and child health (MCH) settings globally, however, the feasibility of implementing IPT within MCH in countries with high concurrent HIV and TB epidemics is unknown. DESIGN/METHODS: The study evaluated the implementation of ACF and IPT guidelines in MCH settings in 2 health facilities in Lesotho. This descriptive prospective study analyzed data collected during routine services. Categorical data and continuous variables were summarized using descriptive statistics. The χ test or Wilcoxon rank-sum test was used to ascertain significant associations between categorical and continuous variables, respectively. RESULTS: Data from 160 HIV-positive and 640 HIV-negative women were reviewed. Within this study population, 99.8% of women were screened for TB, and 11.4% HIV-positive women compared with 2.3% HIV-negative women were reported to have symptoms of TB (P < 0.001). IPT was initiated in 124/158 (78.5%) HIV-positive pregnant women, 64.5% women completed a 6-month IPT regimen, 2 (1.6%) died of causes unrelated to IPT/TB, and 31.5% were lost to follow-up. Predictors of IPT initiation among HIV-positive women included gestational age at the first antenatal visit (unadjusted odds ratio, -0.93; 95% confidence interval: -0.88 to 0.98), and receipt of antiretroviral therapy for treatment rather than for prevention of mother-to-child transmission prophylaxis only (odds ratio, 4.59; 95% confidence interval: 1.32 to 15.93). CONCLUSIONS: Implementation of ACF and IPT is feasible within the MCH setting. Uptake of IPT during pregnancy among HIV-positive women was high, but with a high rate of loss to follow-up.