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.


Social impact bonds: is an ounce of (bond) prevention worth more than a pound of (budgetary) cure

It is one of the curious ironies of history that ideas which tend to destroy also help to rebuild. Innovative financial instruments played a key role in the 2007-2008 financial crisis that not only dented economic growth worldwide, but also hit government revenue streams making fewer resources available for health care spending. Roughly five years after the crisis, social impact bonds (SIBs) – a new financial instrument – hold promise to fund a raft of innovative social service delivery models via private capital. Though SIBs are still in the early development phase, they could play a niche role in relieving burdened state health care budgets and financing innovative preventive health schemes in both the US and UK.

SIBs share some common characteristics with (vanilla) bonds; however, there are also notable differences. When an investor purchases a regular bond, he/she pays a principal amount (e.g. a face value of $10,000) with the expectation of receiving periodic interest payments until the bond matures, at which point the principal amount is returned to the investor. SIBs still require an initial principal investment from investors, usually with more than a modicum of altruism for the cause involved. Not-for-profits, and sometimes commercial entities, are the main current investors in SIBs.

The main differences lie in how the money is used and how payments to investors are made. An intermediary, which charges fees, serves as the organizer of the SIB selecting the investors, service providers, and overseeing the process. Once investors purchase a SIB, a government agency contracts out with social service delivery organisation(s) for a selected cohort of individuals. Investors are not offered regular interest payments; rather, they are offered ‘performance-based’ payments based on agreed-to benchmarks in service delivery.

For example, Social Finance UK issued the first social impact bond in September 2010 in the United Kingdom. In the case of the 2010 Peterborough SIB offering, incentive payments were tied to ex-prisoner recidivism levels. That is, if the selected cohort of released ex-prisoners ‘covered’ under the bond’s services had a lower rate of recidivism than an agreed-upon counter-factual cohort (usually the natural average), investors would be rewarded with a payment from the government. If the cohort demonstrated a higher rate of recidivism, investors would forfeit both the initial principal investment and performance payments. In this scheme, the financing mechanism acts more like equity when investors receive a dividend for superior corporate performance (without the capital gain) rather than guaranteed interest payments (see diagram below from Social Finance for the SIB flow of funds between investor, government, and social service deliverer).

(c) Social Finance 2011

(c) Social Finance 2011

The interest for SIBs in health care service delivery is gaining momentum. After the successful launch of the first SIB in 2010, coupled with a greater emphasis on ‘responsible finance’, the idea quickly expanded to other fields including education, adoption and work retraining schemes. The business case for health care SIBs is arguably at least as strong, if not stronger, than other areas. There are two reasons for this.

First, governments face difficult funding choices in the age of austerity. Regardless of the expenditure area, general budgetary funds are usually allocated to existing programs with minimal risk; innovative programs with high start-up costs and unknown outcomes are not seen to deliver value-for-money.

Second, a majority of health care budgets in advanced countries are dedicated to treating patients with chronic conditions, primarily in hospital or long-term care settings. Spending on preventive services has traditionally been much lower, although this is gradually changing. This is particularly true for innovative schemes to prevent chronic disease onset. Policy makers need more tools to address the crowding out of preventive spending in health care budgets as the average population age and number of comorbidities per patient grows. SIBs might be one tool to diversify the risk associated with these schemes, while also allowing governments to pay only for programs that actually improve outcomes.

Although interest exists, adoption of SIBs for health care services has been slow.  Though the UK served as the initial testing ground for SIBs, their use in health care has been minimal. Some of the inertia is due to the NHS: the large bureaucracy has established payment and program trial systems that are not compatible with SIBs. This attitude may be changing however, particularly due to the fiscal pressures of austerity. In reaction to a May 2013 NHS/Monitor discussion paper on changing the NHS’s payment system, several organisations submitted responses that proposed SIBs as a necessary strategy. The Health Foundation’s submission cited a trial in the Milton Keynes NHS Trust associated with psychological assessment of diabetes patients with ‘SIB-like’ properties.

In the United States, state and local health care stakeholders have been at the forefront of developing SIBs. The city of Fresno in California is the country’s first site for a health care SIB: a two- year demonstration bond has been approved to assess the use of evidence-based practices in the treatment of 200 low-income paediatric asthma patients. The $660,000 SIB, funded by Collective Health and the California Endowment, will evaluate if intensive patient education and home visits will be effective in preventing emergency department visits and inpatient hospitalisations. If the selected cohort achieves a lower utilisation rate than another selected cohort in California’s Medical population, investors will receive their payback and the initial trial will be expanded to cover 2000 children in the state.

SIBs, despite their innovative nature, are also a target of criticism. First, critics point out that the SIB delivery structure is economically inefficient. The SIB’s intermediary charges fees that would not exist in a direct relationship between the government and contractor; these fees mean that a project can be expensive to scale up and potentially waste government funds. Second, the singular focus on pre-determined quantitative measures may be wrong-headed. A typical evaluation of social service schemes is more flexible including both qualitative and quantitative assessments of success. The evaluation also takes note of when service delivery or outcomes did not follow prescribed guidelines, or allows for changes in how the demonstration proceeds based on feedback. This iterative process may not be possible in SIBs.

Overall, SIBs are still in their nascency and face many challenges. The idea, however, is not simply put of a larger social investing fad. If SIBs are able to allocate investments in areas where governments are unable or unwilling to invest, they may serve their purpose; even if they show which delivery schemes fail. With tighter health care budgets and the pressing need for innovative solutions in health, SIBs should be seen as a useful new financing tool.