Erik Tollefson’s journal round-up for 13th June 2016

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.

A general method for decomposing the causes of socioeconomic inequality in health. Journal of Health Economics [PubMed] Published 7th April 2016

In this paper, Heckley, Gerdtham, and Kjellsson establish a new methodology for decomposing the causes of socioeconomic inequality in health. Currently, versions of the concentration index, using bivariate rank dependent indices, play a dominant methodological role. The index depends on a bivariate calculation assigning a negative (positive) value to an individual’s cumulative health and socioeconomic rank. The WDW method, developed by Wagstaff, is the main decomposition method to understand potential causes of a change in the index. Decomposition methods for the index face several limitations.  The main limitation is that although the bivariate rank index are two-dimensional indices that consider the covariance between health and rank, the decomposition method is only one-dimensional looking at health but not rank. Thus, it is difficult to understand what the parameters are for identification; decomposition has become an exercise in accounting rather than explanation. The authors propose a new decomposition method that aims to explain the causes of socioeconomic inequality by looking directly at the health and socioeconomic rank that composes the index. The authors apply RIF regression to accomplish this, deriving RIF for a general bivariate rank index. The decomposition method is thus able to explain potential causes of socioeconomic inequality by directly decomposing the weighted covariance of health and socioeconomic rank.

Understanding the improvement in disability free life expectancy in the US elderly population. NBER Working Paper [RePEcPublished June 2016

In this working paper, Chernew, Cutler, Ghosh, and Landrum explore two key questions. First, how have life expectancy disability-free lifespans changed in the US population in the elderly cohort (over the age of 65)? Second, what is responsible for the extension (diminution) of longevity and disability-free lifespans? In order to answer these questions, the authors build off previous work in which they used secondary mortality data and primary survey data to estimate the trajectory of longevity and disability-free living.  They extend the previous data, which ended in 2005, up to 2008 in the paper, finding that both longevity and disability-free living has increased over time. The authors then assess which medical conditions are (causally) responsible for the greatest additions to disability-free life expectancy through decomposing mortality and disability into fifteen different conditions (inclusive of acute and chronic diseases). The paper finds that the largest gains in disability-free years are due to improvements in two areas: cardiovascular disease and vision problems. Finally, the authors create a model to explore what percentage the improvement in these conditions is due to health care interventions. The authors use the IMPACT model to estimate that health care accounts for 50% of disability-free living in cardiovascular health and cataract surgery accounts for 25% improvement in disability free living for vision problems. Overall, the paper provides useful data looking at not only why longevity and disability-free lifespans are increasing, but also what percentage is due to health interventions versus social factors. Although the results of the causal contribution of health care are provisional they provide an interesting methodological window, particularly in the United States, to understand which medical procedures provide the greatest value for elderly beneficiaries.

Global differences in cancer drug prices: a comparative analysis. Journal of Clinical Oncology Published June 2016

Increasing public attention is paid to prices of cancer drugs. This is not only true in developed countries where access to expensive cancer drugs can be prohibitive, but also in developing countries where access to cancer drugs generally and generic cancer drugs specifically is an emerging problem. In this study, the authors looked at the differences of (listed) cancer drug prices for 23 cancer drugs (15 of which are available generically) across five continents and six countries: Australia, China, India, South Africa, United Kingdom, and the United States. The study estimated the price of the drugs on a monthly basis as a percentage of the respective country’s per-capita GDP. Overall, the study found tremendous variation in prices of cancer drugs, with greater affordability in developed countries compared to developing or poorer countries. This study is quite useful in providing a data-driven analysis of cancer drug prices. The public debate in developed countries on cancer drug prices is often times hijacked by two rhetorical extremes: drug companies touting the benefits of innovative therapies on the one hand and advocates calling for price guidance (controls) on the other hand. Little attention (and data) is available for cancer pricing, especially in developing countries. This study provides an excellent foundation for cross-country pricing comparisons, but could be improved by correcting for differences between listed prices and actually paid prices, as well as adjusting for differences in health insurance coverage across countries. Including drug access measures as part of a greater cancer drugs index would also help to understand drug availability.

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