Extended cost-effectiveness analysis of interventions to improve uptake of diabetes services in South Africa.

The rising prevalence of diabetes in South Africa (SA), coupled with significant levels of unmet need for diagnosis and treatment, results in high rates of diabetes-associated complications. Income status is a determinant of utilization of diagnosis and treatment services, with transport costs and loss of wages being key barriers to care. A conditional cash transfer (CCT) programme, targeted to compensate for such costs, may improve service utilization. We applied extended cost-effectiveness analysis (ECEA) methods and used a Markov model to compare the costs, health benefits and financial risk protection (FRP) attributes of a CCT programme. A population was simulated, drawing from SA-specific data, which transitioned yearly through various health states, based on specific probabilities obtained from local data, over a 45-year time horizon. Costs and disability-adjusted life years (DALYs) were applied to each health state. Three CCT programme strategies were simulated and compared to a 'no programme' scenario: (1) covering diagnosis services only; (2) covering treatment services only; (3) covering both diagnosis and treatment services. Cost-effectiveness was reported as incremental net monetary benefit (INMB) using a cost-effectiveness threshold of USD3015 per DALY for SA, while FRP outcomes were reported as catastrophic health expenditure (CHE) cases averted. Distributions of the outcomes were reported by income quintile and sex. Covering both diagnosis and treatment services for the bottom two quintiles resulted in the greatest INMB (USD22 per person) and the greatest CHE cases averted. There were greater FRP benefits for women compared to men. A CCT programme covering diabetes diagnosis and treatment services was found to be cost-effective, when provided to the poorest 40% of the SA population. ECEA provides a useful platform for including equity considerations to inform priority setting and implementation policies in SA.

Empirical Estimates of the Marginal Cost of Health Produced by a Healthcare System: Methodological Considerations from Country-Level Estimates.

Many health technology assessment committees have an explicit or implicit reference value (often referred to as a 'threshold') below which new health technologies or interventions are considered value for money. The basis for these reference values is unclear but one argument is that it should be based on the health opportunity costs of funding decisions. Empirical estimates of the marginal cost per unit of health produced by a healthcare system have been proposed to capture the health opportunity costs of new funding decisions. Based on a systematic search, we identified eight studies that have sought to estimate a reference value through empirical estimation of the marginal cost per unit of health produced by a healthcare system for England, Spain, Australia, The Netherlands, Sweden, South Africa and China. We review these eight studies to provide an overview of the key methodological approaches taken to estimate the marginal cost per unit of health produced by the healthcare system with the aim to help inform future estimates for additional countries. The lead author for each of these papers was invited to contribute to the current paper to ensure all the key methodological issues encountered were appropriately captured. These included consideration of the key variables required and their measurement, accounting for endogeneity of spending to health outcomes, the inclusion of lagged spending, discounting and future costs, the use of analytical weights, level of disease aggregation, expected duration of health gains, and modelling approaches to estimating mortality and morbidity effects of health spending. Subsequent research estimates for additional countries should (1) carefully consider the specific context and data available, (2) clearly and transparently report the assumptions made and include stakeholder perspectives on their appropriateness and acceptability, and (3) assess the sensitivity of the preferred central estimate to these assumptions.

Estimating a cost-effectiveness threshold for health care decision-making in South Africa.

Cost-effectiveness thresholds are important decision rules that determine whether health interventions represent good value for money. In low- and middle-income countries, the World Health Organization (WHO) one to three times per capita gross domestic product (GDP) per disability-adjusted life years (DALYs) averted has been the most widely used threshold for informing resource allocation decisions. However, in 2016, the WHO withdrew recommendations for using this threshold, creating a significant vacuum in South Africa and many countries that rely on results of cost-effectiveness analyses for making resource allocation decisions. This study estimates a cost-effectiveness threshold that reflects the health opportunity cost of health spending in South Africa using a three-step approach. First, marginal returns to health spending was estimated as health spending elasticity for crude death rates using a fixed effect estimation approach. Second, the opportunity cost of health spending was estimated as DALYs averted. Finally, a cost per DALY averted threshold was estimated as the inverse of the marginal product of health spending. We show that 1% of total health spending in 2015 (equivalent to approximately ZAR 1.54 billion/USD 120.7 million) averted 1050 deaths, 34 180 years of life lost, 5880 years lived with disability and 40 055 DALYs. The cost-effectiveness threshold was estimated at approximately ZAR 38 500 (USD 3015) per DALY averted, ∼53% of South Africa's per capita GDP in 2015 (ZAR 72 700/USD 5700) and lower than the previously recommended one to three times per capita GDP. As South Africa moves towards implementing universal health coverage reforms through National Health Insurance by 2025, the adoption of a threshold that reflects health opportunity costs will be crucial for ensuring efficiency in the allocation of scarce resources. This study provides useful insight into the magnitude of the health opportunity cost of health spending in South Africa and highlights the need for further research.

Implications of Misclassification Errors in Empirical Studies of Adolescent Smoking Behaviours.

Misclassification errors in a dependent variable can introduce attenuation bias to covariate effects in a binary choice model. Misreporting of smoking behaviours by adolescents has been widely documented. However, the consequence in empirical studies of adolescent smoking participation has received little attention. This study uses the Health Survey for England (HSE) to investigate the extent and implication of misclassification errors in self-reported smoking among adolescents aged 11-15 years. The HSE contains both a self-reported smoking component and an objective measure of smoking obtained from saliva cotinine assays. Saliva cotinine concentration ≥12 ng/ml is considered the 'true' indicator of adolescent smoking participation against which self-reported smoking is compared. The findings show that smoking is misreported in this age group, resulting in a downwards bias of marginal effect estimates. Given the widespread use of self-reported smoking data, this study explores the performance of the Hausman, Abrevaya and Scott-Morton-modified maximum likelihood estimation (HAS approach) in recovering true estimates of covariate effects. In this context, the HAS approach performs better when the misclassification probabilities are treated as constants compared with when they are treated as conditionally dependent parameters. Copyright © 2016 John Wiley & Sons, Ltd.

Healthcare costs of paternal depression in the postnatal period.

BACKGROUND: There is growing evidence that fathers experience depressive symptoms following the birth of a child. The aim of this study was to estimate the healthcare costs of paternal postnatal depression, thereby informing research into cost-effective preventative and treatment interventions for the condition. METHODS: Data on healthcare resource-use over the first 12 months postpartum was collected from 192 fathers recruited from two postnatal wards in southern England. Three groups of fathers were identified: fathers with depression (n=31), fathers at high risk of developing depression (n=67) and fathers without depression (n=94). RESULTS: Mean father-child dyad costs were estimated at £ 1103.51, £ 1075.06 and £ 945.03 (£ sterling, 2008 prices) in these three groups, respectively (P=0.796). After controlling for potentially confounding factors, paternal depression was associated with significantly higher community care costs. CONCLUSION: This study provides useful preliminary insights into the healthcare costs associated with paternal depression during the postnatal period. LIMITATION: The small sample size may, in part, account for the failure to detect statistically significant differences in mean costs between study groups for most cost categories.