Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.
Innovation in the pharmaceutical industry: new estimates of R&D costs. Journal of Health Economics [PubMed] Published 12th February 2016
This study is an update of the original study by DiMasi and colleagues, whose finding, published in an article in the Journal of Health Economics that the costs (in 2000 USD) of drug development were close to $1 billion, has achieved near canonical status. However, considerable doubt has been thrown on these claims, and the criticisms of the original study should be applied to this new research. Light and Warburton’s critique drew on a number of points: the lack of comparability and reliability about the original survey data as well as the lack of transparency (as the data were not made publically available); there was a clear interest for pharmaceutical companies to overstate their costs in survey responses; neither the firms nor the drugs considered were random samples; the only drugs considered in the study were “self-originated new chemical entities” (NCEs) whose costs of development are many times higher than acquired or licensed-in NCEs, new formulations, combinations, or administrations of existing drugs, and yet only comprise around 22% of new drug approvals; government subsidies were not deducted; and, there was no adjustment for tax deductions and credits, to name but a few. Articles in major journals based on industry sponsored research are three to four times more likely to report results favourable to the sponsors than articles with independent funding (see here and here). Considerable variation therefore exists in estimates of the costs of drug development. Light and Warburton have estimated the median figure to be roughly a tenth of the original DiMasi estimate. While this may seem implausibly low it certainly suggests we need to take industry sponsored research that affects health policy with a healthy dose of scepticism. The new estimate in this paper is $2.9 billion, but I’ll let you be the judge of its validity.
Outcomes in economic evaluations of public health interventions in low- and middle-income countries: health, capabilities and subjective wellbeing. Health Economics [PubMed]. Published 25th January 2016
This study forms part of a special issue of Health Economics on the subject of economic evaluation in low and middle income countries (LMICs) published recently. The whole special issue is worth a read, but here I’ll just outline one paper that discusses outcomes in the evaluation of public health interventions in LMICs. Public health interventions and other community based programs often aim to improve a number of aspects of people’s lives beyond health. The question of value is a growing topic in health economics. People have reason to value other outcomes such as knowledge, education, or liberty. For this reason QALYs or DALYs have been argued to not be well suited to the evaluation of public health interventions as they only capture health related changes to people’s lives. New approaches, such as the capabilities approach or subjective well-being, are therefore being developed. Subjective well-being may indeed fit into a more traditional welfarist approach to policy evaluation, which may be suitable in countries where cost-effectiveness thresholds have not been established. This paper provides some examples of these applications and discusses challenges to their use in LMICs.
Does introducing imprecision around probabilities for benefit and harm influence the way people value treatments? Medical Decision Making [PubMed] Published 31st March 2016
In many cases economic evaluation is concerned with estimation of the incremental cost-effectiveness ratio of a treatment or technology where both costs and benefits are considered at the patient level. This information can be used to inform clinical guidelines and recommendations. However, patients generally have a choice with regards to their treatment. When the costs or benefits of an intervention depend on the number of patients treated, such as may be the case with a structural health systems intervention, a public health intervention, or a treatment program, then patient choice and uptake affects the overall cost-effectiveness of the intervention. Methods for clinical trial design based upon the effects to patient choice have been previously published. This study here shows how the level of uncertainty involved and the way it is presented to patients impacts upon their choice of treatment. Such information may prove useful to the evaluation of interventions where uptake matters and may serve to inform clinical trial design.