Tuberculosis patients face high treatment support costs in Colombia, 2021.

OBJECTIVE: To estimate the baseline to measure one of the three indicators of the World Health Organization (WHO) End TB strategy (2015-2035), measure the costs incurred by patients affected by tuberculosis (TB) during a treatment episode and estimate the proportion of households facing catastrophic costs (CC) and associated risk factors, in Colombia, 2021. MATERIAL AND METHODS: A nationally representative cross-sectional survey was conducted among participants on TB treatment in Colombia, using telephone interviews due to the exceptional context of the COVID-19 pandemic. The survey collected household costs (direct [medical and non-medical out-of-pocket expenses] and indirect) over an episode of TB, loss of time, coping measures, self-reported income, and asset ownership. Total costs were expressed as a proportion of annual household income and analyzed for risk factors of CC (defined as costs above 20% annual household income). RESULTS: The proportion of TB-affected households incurring in costs above 20% annual household income (CC) was 51.7% (95%CI: 45.4-58.0) overall, 51.3% (95%CI: 44.9-57.7) among patients with drug-sensitive (DS) TB, and 65.0% (95%CI: 48.0-82.0) among drug-resistant (DR). The average patient cost of a TB case in Colombia was $1,218 (95%CI 1,106-1,330) including $860.9 (95%CI 776.1-945.7) for non-medical costs, $339 (95%CI 257-421) for the indirect costs, and $18.1 (95%CI 11.9-24.4) for the medical costs. The factors that influenced the probability of facing CC were income quintile, job loss, DR-TB patient, and TB type. CONCLUSION: Main cost drivers for CC were non-medical out-of-pocket expenses and income loss (indirect costs). Current social protection programs ought to be expanded to mitigate the proportion of TB-affected households facing CC in Colombia, especially those with lower income levels.

The economic burden of households affected by tuberculosis in Brazil: First national survey results, 2019-2021.

BACKGROUND: One of the three main targets of the World Health Organization (WHO) End TB Strategy (2015-2035) is that no tuberculosis (TB) patients or their households face catastrophic costs (defined as exceeding 20% of the annual household income) because of the disease. Our study seeks to determine, as a baseline, the magnitude and main drivers of the costs associated with TB disease for patients and their households and to monitor the proportion of households experiencing catastrophic costs in Brazil. METHODS: A national cross-sectional cluster-based survey was conducted in Brazil in 2019-2021 following WHO methodology. TB patients of all ages and types of TB were eligible for the survey. Adult TB patients and guardians of minors (<18 years old) were interviewed once about costs, time loss, coping measures, income, household expenses, and asset ownership. Total costs, including indirect costs measured as reported household income change, were expressed as a percentage of annual household income. We used descriptive statistics to analyze the cost drivers and multivariate logistic regression to determine factors associated with catastrophic costs. RESULTS: We interviewed 603 patients, including 538 (89%) with drug-sensitive (DS) and 65 (11%) with drug-resistant (DR) TB. Of 603 affected households, 48.1% (95%CI: 43-53.2) experienced costs above 20% of their annual household income during their TB episode. The proportion was 44.4% and 78.5% among patients with DS- and DR-TB, respectively. On average, patients incurred costs of US$1573 (95%CI: 1361.8-1785.0) per TB episode, including pre-diagnosis and post-diagnosis expenses. Key cost drivers were post-diagnosis nutritional supplements (US$317.6, 95%CI: 232.7-402.6) followed by medical costs (US$85.5, 95%CI: 54.3-116.5) and costs of travel for clinic visits during treatment (US$79.2, 95%CI: 61.9-96.5). In multivariate analysis, predictors of catastrophic costs included positive HIV status (aOR = 3.0, 95%CI:1.1-8.6) and self-employment (aOR = 2.7, 95%CI:1.1-6.5); high education was a protective factor (aOR = 0.1, 95%CI:0.0-0.9). CONCLUSIONS: Although the services offered to patients with TB are free of charge in the Brazilian public health sector, the availability of free diagnosis and treatment services does not alleviate patients' financial burden related to accessing TB care. The study allowed us to identify the costs incurred by patients and suggest actions to mitigate their suffering. In addition, this study established a baseline for monitoring catastrophic costs and fostering a national policy to reduce the costs to patients for TB care in Brazil.

Costs incurred by people receiving tuberculosis treatment in low-income and middle-income countries: a meta-regression analysis.

BACKGROUND: People accessing and completing treatment for tuberculosis can face large economic costs, even when treatment is provided free of charge. The WHO End TB Strategy targets the elimination of catastrophic costs among tuberculosis-affected households. While low-income and middle-income countries (LMICs) represent 99% of global tuberculosis cases, only 29 of 135 LMICs had conducted national surveys of costs for patients with tuberculosis by December, 2022. We estimated costs for patients with tuberculosis in countries that have not conducted a national survey, to provide evidence on the economic burden of tuberculosis in these settings and inform estimates of global economic burden. METHODS: We extracted data from 22 national surveys of costs faced by patients with tuberculosis that were completed across 2015-22 and met inclusion criteria. Using a Bayesian meta-regression approach, we used these data and covariate data for all 135 LMICs to estimate per-patient costs (2021 US$) by cost category (ie, direct medical, direct non-medical, and indirect), country, drug resistance, and household income quintile. We also estimated the proportion of households experiencing catastrophic total costs (defined as >20% of annual household income) as a result of tuberculosis disease. FINDINGS: Across LMICs, mean direct medical costs incurred by patients with tuberculosis were estimated as US$211 (95% uncertainty interval 154-302), direct non-medical costs were $512 (428-620), and indirect costs were $530 (423-663) per episode of tuberculosis. Overall, per-patient costs were $1253 (1127-1417). Estimated proportions of tuberculosis-affected households experiencing catastrophic total costs ranged from 75·2% (70·3-80·0) in the poorest quintile to 42·5% (34·3-51·5) in the richest quintile, compared with 54·9% (47·0-63·2) overall. INTERPRETATION: Tuberculosis diagnosis and treatment impose substantial costs on affected households. Eliminating these economic losses is crucial for removing barriers to accessing tuberculosis diagnosis and completing treatment among affected households and achieving the targets set in WHO's End TB Strategy. FUNDING: World Health Organization.

National tuberculosis spending efficiency and its associated factors in 121 low-income and middle-income countries, 2010-19: a data envelopment and stochastic frontier analysis.

BACKGROUND: Maximising the efficiency of national tuberculosis programmes is key to improving service coverage, outcomes, and progress towards End TB targets. We aimed to determine the overall efficiency of tuberculosis spending and investigate associated factors in 121 low-income and middle-income countries between 2010 and 2019. METHODS: In this data envelopment and stochastic frontier analysis, we used data from the WHO Global TB report series on tuberculosis spending as the input and treatment coverage as the output to estimate tuberculosis spending efficiency. We investigated associations between 25 independent variables and overall efficiency. FINDINGS: We estimated global tuberculosis spending efficiency to be between 73·8% (95% CI 71·2-76·3) and 87·7% (84·9-90·6) in 2019, depending on the analytical method used. This estimate suggests that existing global tuberculosis treatment coverage could be increased by between 12·3% (95% CI 9·4-15·1) and 26·2% (23·7-28·8) for the same amount of spending. Efficiency has improved over the study period, mainly since 2015, but a substantial difference of 70·7-72·1 percentage points between the most and least efficient countries still exists. We found a consistent significant association between efficiency and current health expenditure as a share of gross domestic product, out-of-pocket spending on health, and some Sustainable Development Goal (SDG) indicators such as universal health coverage. INTERPRETATION: To improve efficiency, treatment coverage will need to be increased, particularly in the least efficient contexts where this might require additional spending. However, progress towards global End TB targets is slow even in the most efficient countries. Variables associated with TB spending efficiency suggest efficiency is complimented by commitments to improving health-care access that is free at the point of use and wider progress towards the SDGs. These findings support calls for additional investment in tuberculosis care. FUNDING: None.

Determinants of household catastrophic costs for drug sensitive tuberculosis patients in Kenya.

BACKGROUND: Despite free diagnosis and treatment for tuberculosis (TB), the costs during treatment impose a significant financial burden on patients and their households. The study sought to identify the determinants for catastrophic costs among patients with drug-sensitive TB (DSTB) and their households in Kenya. METHODS: The data was collected during the 2017 Kenya national patient cost survey from a nationally representative sample (n = 1071). Treatment related costs and productivity losses were estimated. Total costs exceeding 20% of household income were defined as catastrophic and used as the outcome. Multivariable Poisson regression analysis was performed to measure the association between selected individual, household and disease characteristics and occurrence of catastrophic costs. A deterministic sensitivity analysis was carried using different thresholds and the significant predictors were explored. RESULTS: The proportion of catastrophic costs among DSTB patients was 27% (n = 294). Patients with catastrophic costs had higher median productivity losses, 39 h [interquartile range (IQR): 20-104], and total median costs of USD 567 (IQR: 299-1144). The incidence of catastrophic costs had a dose response with household expenditure. The poorest quintile was 6.2 times [95% confidence intervals (CI): 4.0-9.7] more likely to incur catastrophic costs compared to the richest. The prevalence of catastrophic costs decreased with increasing household expenditure quintiles (proportion of catastrophic costs: 59.7%, 32.9%, 23.6%, 15.9%, and 9.5%) from the lowest quintile (Q1) to the highest quintile (Q5). Other determinants included hospitalization: prevalence ratio (PR) = 2.8 (95% CI: 1.8-4.5) and delayed treatment: PR = 1.5 (95% CI: 1.3-1.7). Protective factors included receiving care at a public health facility: PR = 0.8 (95% CI: 0.6-1.0), and a higher body mass index (BMI): PR = 0.97 (95% CI: 0.96-0.98). Pre TB expenditure, hospitalization and BMI were significant predictors in all sensitivity analysis scenarios. CONCLUSIONS: There are significant inequities in the occurrence of catastrophic costs. Social protection interventions in addition to existing medical and public health interventions are important to implement for patients most at risk of incurring catastrophic costs.

Catastrophic costs among tuberculosis-affected households in Zimbabwe: A national health facility-based survey.

OBJECTIVES: To determine the incidence and major drivers of catastrophic costs among TB-affected households in Zimbabwe. METHODS: We conducted a nationally representative health facility-based survey with random cluster sampling among consecutively enrolled drug-susceptible (DS-TB) and drug-resistant TB (DR-TB) patients. Costs incurred and income lost due to TB illness were captured using an interviewer-administered standardised questionnaire. We used multivariable logistic regression to determine the risk factors for experiencing catastrophic costs. RESULTS: A total of 841 patients were enrolled and were weighted to 900 during data analysis. There were 500 (56%) males and 46 (6%) DR-TB patients. Thirty-five (72%) DR-TB patients were HIV co-infected. Overall, 80% (95% CI: 77-82) of TB patients and their households experienced catastrophic costs. The major cost driver pre-TB diagnosis was direct medical costs. Nutritional supplements were the major cost driver post-TB diagnosis, with a median cost of US$360 (IQR: 240-600). Post-TB median diagnosis costs were three times higher among DR-TB (US$1,659 [653-2,787]) than drug DS-TB-affected households (US$537 [204-1,134]). Income loss was five times higher among DR-TB than DS-TB patients. In multivariable analysis, household wealth was the only covariate that remained significantly associated with catastrophic costs: The poorest households had 16 times the odds of incurring catastrophic costs versus the wealthiest households (adjusted odds ratio [aOR: 15.7 95% CI: 7.5-33.1]). CONCLUSION: The majority of TB-affected households, especially those affected by DR-TB, experienced catastrophic costs. Since the major cost drivers fall outside the healthcare system, multi-sectoral approaches to TB control and linking TB patients to social protection may reduce catastrophic costs.

Examining the level and inequality in health insurance coverage in 36 sub-Saharan African countries.

INTRODUCTION: Low/middle-income countries (LMICs) in sub-Saharan Africa (SSA) are increasingly turning to public contributory health insurance as a mechanism for removing financial barriers to access and extending financial risk protection to the population. Against this backdrop, we assessed the level and inequality of population coverage of existing health insurance schemes in 36 SSA countries. METHODS: Using secondary data from the most recent Demographic and Health Surveys, we computed mean population coverage for any type of health insurance, and for specific forms of health insurance schemes, by country. We developed concentration curves, computed concentration indices, and rich-poor differences and ratios to examine inequality in health insurance coverage. We decomposed the concentration index using a generalised linear model to examine the contribution of household and individual-level factors to the inequality in health insurance coverage. RESULTS: Only four countries had coverage levels with any type of health insurance of above 20% (Rwanda-78.7% (95% CI 77.5% to 79.9%), Ghana-58.2% (95% CI 56.2% to 60.1%), Gabon-40.8% (95% CI 38.2% to 43.5%), and Burundi 22.0% (95% CI 20.7% to 23.2%)). Overall, health insurance coverage was low (7.9% (95% CI 7.8% to 7.9%)) and pro-rich; concentration index=0.4 (95% CI 0.3 to 0.4, p<0.001). Exposure to media made the greatest contribution to the pro-rich distribution of health insurance coverage (50.3%), followed by socioeconomic status (44.3%) and the level of education (41.6%). CONCLUSION: Coverage of health insurance in SSA is low and pro-rich. The four countries that had health insurance coverage levels greater than 20% were all characterised by substantial funding from tax revenues. The other study countries featured predominantly voluntary mechanisms. In a context of high informality of labour markets, SSA and other LMICs should rethink the role of voluntary contributory health insurance and instead embrace tax funding as a sustainable and feasible mechanism for mobilising resources for the health sector.

Patient costs of diabetes mellitus care in public health care facilities in Kenya.

OBJECTIVE: To estimate the direct and indirect costs of diabetes mellitus care at five public health facilities in Kenya. METHODS: We conducted a cross-sectional study in two counties where diabetes patients aged 18 years and above were interviewed. Data on care-seeking costs were obtained from 163 patients seeking diabetes care at five public facilities using the cost-of-illness approach. Medicines and user charges were classified as direct health care costs while expenses on transport, food, and accommodation were classified as direct non-health care costs. Productivity losses due to diabetes were classified as indirect costs. We computed annual direct and indirect costs borne by these patients. RESULTS: More than half (57.7%) of sampled patients had hypertension comorbidity. Overall, the mean annual direct patient cost was KES 53 907 (95% CI, 43 625.4-64 188.6) (US$ 528.5 [95% CI, 427.7-629.3]). Medicines accounted for 52.4%, transport 22.6%, user charges 17.5%, and food 7.5% of total direct costs. Overall mean annual indirect cost was KES 23 174 (95% CI, 20 910-25 438.8) (US$ 227.2 [95% CI, 205-249.4]). Patients reporting hypertension comorbidity incurred higher costs compared with diabetes-only patients. The incidence of catastrophic costs was 63.1% (95% CI, 55.7-70.7) and increased to 75.4% (95% CI, 68.3-82.1) when transport costs were included. CONCLUSION: There are substantial direct and indirect costs borne by diabetic patients in seeking care from public facilities in Kenya. High incidence of catastrophic costs suggests diabetes services are unaffordable to majority of diabetic patients and illustrate the urgent need to improve financial risk protection to ensure access to care.

Patient costs of hypertension care in public health care facilities in Kenya.

BACKGROUND: Hypertension in low- and middle-income countries, including Kenya, is of economic importance due to its increasing prevalence and its potential to present an economic burden to households. In this study, we examined the patient costs associated with obtaining care for hypertension in public health care facilities in Kenya. METHODS: We conducted a cross-sectional study among adult respondents above 18 years of age, with at least 6 months of treatment in two counties. A total of 212 patients seeking hypertension care at five public facilities were interviewed, and information on care seeking and the associated costs was obtained. We computed both annual direct and indirect costs borne by these patients. RESULTS: Overall, the mean annual direct cost to patients was US$ 304.8 (95% CI, 235.7-374.0). Medicines (mean annual cost, US$ 168.9; 95% CI, 132.5-205.4), transport (mean annual cost, US$ 126.7; 95% CI, 77.6-175.9), and user charges (mean annual cost, US$ 57.7; 95% CI, 43.7-71.6) were the highest direct cost categories. Overall mean annual indirect cost was US$ 171.7 (95% CI, 152.8-190.5). The incidence of catastrophic health care costs was 43.3% (95% CI, 36.8-50.2) and increased to 59.0% (95% CI, 52.2-65.4) when transport costs were included. CONCLUSIONS: Hypertensive patients incur substantial direct and indirect costs. High rates of catastrophic costs illustrate the urgency of improving financial risk protection for these patients and strengthening primary care to ensure affordability of hypertension care.

A critical analysis of health care purchasing arrangements in Kenya: A case study of the county departments of health.

BACKGROUND: Purchasing in health care financing refers to the transfer of pooled funds to health care providers for the provision of health care services. There is limited empirical work on purchasing arrangements and what is required for strategic purchasing in low- and middle-income countries. We conducted this study to critically assess the purchasing arrangements of the county departments of health (CDOH) who are the largest purchasers of health care in Kenya. METHODS: We used a qualitative case study approach to assess the extent to which the purchasing actions of the CDOH in Kenya were strategic. We purposively sampled 10 counties and collected data using in-depth interviews (n = 81), focus group discussions (n = 4), and documents review. We analyzed data using a framework approach. RESULTS: County departments of health did not practice strategic purchasing. The government's (national and county) role as a steward for the purchasing function was characterized by poor accountability and inadequate budgetary allocations for service delivery. The absence of a purchaser-provider split between the CDOH and public health care providers undermined provider selection based on performance and quality. Poor public participation and ineffective complaints and feedback mechanisms limited public accountability and responsiveness to the needs of the people. CONCLUSION: Our findings show that while there are frameworks that could promote strategic purchasing of the CDOH, strategic purchasing is impaired by poor implementation of these frameworks and the inherent weaknesses of a public integrated purchasing system that lacks purchaser-provider split.

Measuring progress towards Sustainable Development Goal 3.8 on universal health coverage in Kenya.

BACKGROUND: The inclusion of universal health coverage (UHC) as a health-related Sustainable Development Goal has cemented its position as a key global health priority. We aimed to develop a summary measure of UHC for Kenya and track the country's progress between 2003 and 2013. METHODS: We developed a summary index for UHC by computing the geometrical mean of indicators for the two dimensions of UHC, service coverage (SC) and financial risk protection (FRP). The SC indicator was computed as the geometrical mean of preventive and treatment indicators, while the financial protection indicator was computed as a geometrical mean of an indicator for the incidence of catastrophic healthcare expenditure, and the impoverishing effect of healthcare payments. We analysed data from three waves of two nationally representative household surveys. FINDINGS: The weighted summary indicator for SC increased from 27.65% (27.13%-28.14%) in 2003 to 41.73% (41.34%-42.12%) in 2013, while the summary indicator for FRP reduced from 69.82% (69.11%-70.51%) in 2003 to 63.78% (63.55%-63.82%) in 2013. Inequities were observed in both these indicators. The weighted summary measure of UHC increased from 43.94% (95% CI 43.48% to 44.38%) in 2003 to 51.55% (95% CI 51.29% to 51.82%) in 2013. CONCLUSION: Significant gaps exist in Kenya's quest to achieve UHC. It is imperative that targeted health financing and other health sector reforms are made to achieve this goal. Such reforms should be focused on both, rather than on only either, of the dimensions of UHC.

Determining the effective coverage of maternal and child health services in Kenya, using demographic and health survey data sets: tracking progress towards universal health coverage.

OBJECTIVES: Effective coverage (EC) is a measure of health systems' performance that combines need, use and quality indicators. This study aimed to assess the extent to which the Kenyan health system provides effective and equitable maternal and child health services, as a means of tracking the country's progress towards universal health coverage. METHODS AND RESULTS: The Demographic Health Surveys (2003, 2008-2009 and 2014) and Service Provision Assessment surveys (2004, 2010) were the main sources of data. Indicators of need, use and quality for eight maternal and child health interventions were aggregated across interventions and economic quintiles to compute EC. EC has increased from 26.7% in 2003 to 50.9% in 2014, but remains low for the majority of interventions. There is a reduction in economic inequalities in EC with the highest to lowest wealth quintile ratio decreasing from 2.41 in 2003 to 1.65 in 2014, but maternal health services remain highly inequitable. CONCLUSIONS: Effective coverage of key maternal and child health services remains low, indicating that individuals are not receiving the maximum possible health gain from existing health services. There is an urgent need to focus on the quality and reach of maternal and child health services in Kenya to achieve the goals of universal health coverage.

Facility-level intervention to improve attendance and adherence among patients on anti-retroviral treatment in Kenya--a quasi-experimental study using time series analysis.

BACKGROUND: Achieving high rates of adherence to antiretroviral therapy (ART) in resource-poor settings comprises serious, but different, challenges in both the first months of treatment and during the life-long maintenance phase. We measured the impact of a health system-oriented, facility-based intervention to improve clinic attendance and patient adherence. METHODS: This was a quasi-experimental, longitudinal, controlled intervention study using interrupted time series analysis. The intervention consisted of (1) using a clinic appointment diary to track patient attendance and monitor monthly performance; (2) changing the mode of asking for self-reported adherence; (3) training staff on adherence concepts, intervention methods, and use of monitoring data; (4) conducting visits to support facility teams with the implementation.We conducted the study in 12 rural district hospitals (6 intervention, 6 control) in Kenya and randomly selected 1894 adult patients over 18 years of age in two cohorts: experienced patients on treatment for at least one year, and newly treated patients initiating ART during the study. Outcome measures were: attending the clinic on or before the date of a scheduled appointment, attending within 3 days of a scheduled appointment, reporting perfect adherence, and experiencing a gap in medication supply of more than 14 days. RESULTS: Among experienced patients, the percentage attending the clinic on or before a scheduled appointment increased in both level (average total increase immediately after intervention) (+5.7%; 95% CI=2.1, 9.3) and trend (increase per month) (+1.0% per month; 95% CI=0.6, 1.5) following the intervention, as did the level and trend of those keeping appointments within three days (+4.2%; 95% CI=1.6, 6.7; and +0.8% per month; 95% CI=0.6, 1.1, respectively). The relative difference between the intervention and control groups based on the monthly difference in visit rates increased significantly in both level (+6.5; 95% CI=1.4, 11.6) and trend (1.0% per month; 95% CI=0.2, 1.8) following the intervention for experienced patients attending the clinic within 3 days of their scheduled appointments.The decrease in the percentage of experienced patients with a medication gap greater than 14 days approached statistical significance (-11.3%; 95% CI=-22.7, 0.1), and the change seemed to persist over 11 months after the intervention. All facility staff used appointment-keeping data to calculate adherence and discussed outcomes regularly. CONCLUSION: The appointment-tracking system and monthly performance monitoring was strengthened, and patient attendance was improved. Scale-up to national level may be considered.