Chris Sampson’s journal round-up for 17th December 2018

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.

Health related quality of life aspects not captured by EQ-5D-5L: results from an international survey of patients. Health Policy Published 14th December 2018

Generic preference-based measures, such as the EQ-5D, cannot capture all aspects of health-related quality of life. They’re not meant to. Rather, their purpose is to capture just enough information to be able to adequately distinguish between health states with respect to the domains deemed normatively relavent to decisionmakers. The stated aim of this paper is to determine whether people with a variety of chronic conditions believe that their experiences can be adequately represented by the EQ-5D-5L.

The authors conducted an online survey, identifying participants through 320 patient associations across 47 countries. Participants were asked to complete the EQ-5D-5L and then asked if any aspects of their illness, which had a “big impact” on their health, were not captured by the EQ-5D-5L. 1,031 people started the survey and 767 completed it. More than half were from the UK. 51% of respondents said that there was some aspect of health not captured by the EQ-5D-5L. Of them, 19% mentioned fatigue, 12% mentioned medication side effects, 9.5% mentioned co-morbid conditions, and then a bunch of others in smaller proportions.

It’s nice to know what people think, but I have a few concerns about the usefulness of this study. One of the main problems is that it doesn’t seem safe to assume that respondents interpret “big impact” as meaning “an impact that is independently important in determining your overall level of quality of life”. So, even if we accept that people judging something to be important makes it important (which I’m not sure it does), then we still can’t be sure whether what they are identifying is within the scope of what we’re trying to measure. For starters, I can see no justification for including a ‘medication side effects’ domain. There’s also some concern about selection and attrition. I’d guess that people with more complicated or less common health concerns would be more likely to start and finish a survey about more complicated or less common health concerns.

The main thing I took from this study is that half of respondents with chronic diseases thought that the EQ-5D-5L captured every single aspect of health that had a “big impact”, and that there wasn’t broad support for any other specific dimension.

Reducing drug wastage in pharmaceuticals dosed by weight or body surface areas by optimising vial sizes. Applied Health Economics and Health Policy [PubMed] Published 5th December 2018

It’s common for pharmaceuticals to be wasted. Not just those out-of-date painkillers you threw in the bin, but also the expensive stuff being used in hospitals. One of the main reasons that waste occurs is that vials are made to specific sizes and, often, dosage varies from patient to patient – according to weight, for example – and doesn’t match the vial size. Suppose that vials are available as 50mg and 80mg and that an individual requires a 60mg dose. One way to address this might be to allow for vial sharing, whereby the leftovers are given to the next patient. But that isn’t always possible. So, we might like to consider what the best combination of available vial sizes should be, given the characteristics of the population.

In this paper, the authors set out the problem mathematically. Essentially, the optimisation problem is to minimise cost across the population subject to the vial sizes. An example is presented for two drugs (pembrolizumab and cabazitaxel), simulating patients based on samples drawn from the Health Survey for England. Simplifications are applied to the examples, such as setting a constraint of 8 vials per patient and assuming that prices are linear (i.e. fixed per milligram).

Pembrolizumab is currently available in 50mg and 100mg vials, and the authors estimate current wastage to be 13.2%. The simulations show that switching the 50mg to a 70mg would cut wastage to 8.6%. Cabazitaxel is available in 60mg vials, resulting in 19.4% wastage. Introducing a 12.5mg vial would cut wastage by around two thirds. An important general finding, which should be self-evident, is that vial sizes should not be divisible by each other, as this limits the number of possible combinations.

Depending on when vial sizes are determined (e.g. pre- or post-authorisation), pharmaceutical companies might use it to increase profit margins, or health systems might use it to save costs. Regardless, wastage isn’t useful. Evidence-based manufacture is an example of one of those best ideas; the sort that is simple and seems obvious once it’s spelt out. It’s a rare opportunity to benefit patients, health care providers, and manufacturers, with no significant burden on policymakers.

Death or debt? National estimates of financial toxicity in persons with newly-diagnosed cancer. The American Journal of Medicine [PubMed] Published October 2018

If you’re British, what’s the scariest thing about an ‘Americanised’ (/Americanized) health care system? Expensive inhalers? A shortened life expectancy? My guess is that the prospect of having to add financial ruin to terminal illness looms pretty large. You should make sure your fear is evidence-based. Here’s a paper to shake in the face of anyone who doesn’t support universal health care.

The authors use data from the Health and Retirement Study from 1998-2014, which includes people over 50 years of age and includes new (self-reported) diagnoses of cancer. This was the basis for inclusion in the study, with over 9.5 million new diagnoses of cancer. Up to two years pre-diagnosis was taken as a baseline. The data set also includes information on participants’ assets and debts, allowing the authors to use change in net worth as the primary outcome. Generalised linear models were used to assess various indicators of financial toxicity, including change or incurrence of consumer debt, mortgage debt, and home equity debt at two- and four-year follow-up. In addition to cancer diagnosis, various chronic comorbidities and socio-demographic variables were included in the models.

Shockingly, after two years following diagnosis, 42.4% of people had depleted their entire life’s assets. Average net worth had dropped $92,000. After four years, 38.2% were still insolvent. Women, older people, people who weren’t White, people with Medicaid, and those with worsening cancer status were among those more likely to have completely depleted their assets within two years. Having private insurance and being married had protective effects, as we might expect. There were some interesting findings associated with the 2008 financial crisis, which also seemed to be protective. And a protective effect associated with psychiatric comorbidity deserves more thought.

It’s difficult to explain away any (let alone all) of the magnitude of these findings. The analysis seems robust. But, given all other evidence available about out-of-pocket costs for cancer patients in the US, it should be shocking but not unexpected. The authors describe financial toxicity as ‘unintended’. There’s nothing unintended about this. Policymakers in the US keep deciding that they’d prefer to destroy the lives of sick people than allow for the spreading of that financial risk.

Credits

Sam Watson’s journal round-up for 24th July 2017

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.

Ten years after the financial crisis: the long reach of austerity and its global impacts on health. Social Science & Medicine [PubMedPublished 22nd June 2017

The subject of austerity and its impact on health has generated its own subgenre in the academic literature. We have covered a number of papers on these journal round-ups on this topic, which, given the nature of economic papers, are generally quantitative in nature. However, while quantitative studies are necessary for generation of knowledge of the social world, they are not sufficient. At aggregate levels, quantitative studies may often rely on a black box approach. We may reasonably conclude a policy caused a change in some population-level indicator on the basis of a causal inference type paper, but we often need other types of evidence to answer why or how this occurred. A realist philosophy of social science may see this as a process of triangulation; at the very least it’s a process of abduction to develop theory that best explains what we observe. In clinical research, Bradford-Hill’s famous criteria can be used as a heuristic for causal inference: a cause can be attributed to an effect if it demonstrates a number of criteria including dose-response and reproducibility. For social science, we can conceive of a similar set of criteria. Effects must follow causes, there has to be a plausible mechanism, and so forth. This article in Social Science & Medicine introduces a themed issue on austerity and its effects on health. The issue contains a number of papers examining experiences of people with respect to austerity and how these may translate into changes in health. One example is a study in a Mozambican hospital and how health outcomes change in response to continued restructuring programs due to budget shortfalls. Another study explores the narrative of austerity in Guyana and it has long been sold as necessary for future benefits which never actually materialise. It is not immediately clear how austerity is being defined here, but it is presumably something like ‘a fiscal contraction that causes a significant increase in aggregate unemployment‘. In any case, it makes for interesting reading and complements economics research on the topic. It is a refreshing change from the bizarre ravings we featured a couple of weeks ago!

Home-to-home time — measuring what matters to patients and payers. New England Journal of Medicine [PubMedPublished 6th July 2017

Length of hospital stay is often used as a metric to evaluate hospital performance: for a given severity of illness, a shorter length of hospital stay may suggest higher quality care. However, hospitals can of course game these metrics, and they are further complicated by survival bias. Hospitals are further incentivised to reduce length of stay. For example, the move from per diem reimbursement to per episode had the effect of dramatically reducing length of stay in hospitals. As a patient recovers, they may no longer need hospital based care, the care they require may be adequately provided in other institutional settings. Although, in the UK there has been a significant issue with many patients convalescing in hospital for extended periods as they wait for a place in residential care homes. Thus from the perspective of the whole health system, length of stay in hospital may no longer be the right metric to evaluate performance. This article makes this argument and provides some interesting statistics. For example, between 2004 and 2011 the average length of stay in hospital among Medicare beneficiaries in the US decreased from 6.3 to 5.7 days; post-acute care stays increased from 4.8 to 6.0 days. Thus, the total time in care actually increased from 11.1 to 11.7 days over this period. In the post-acute care setting, Medicare still reimburses providers on a per diem basis, so total payments adjusted for inflation also increased. This article makes the argument that we need to structure incentives and reimbursement schemes across the whole care system if we want to ensure efficiency and equity.

The population health benefits of a healthy lifestyle: life expectancy increased and onset of disability delayed. Health Affairs [PubMedPublished July 2017

Obesity and tobacco smoking increase the risk of ill health and in so doing reduce life expectancy. The same goes for alcohol, although the relationship between alcohol consumption and risk of illness is less well understood. One goal of public health policy is to mitigate these risks. One successful way of communicating the risks of different behaviours is as changes to life expectancy, or conversely ‘effective age‘. From a different perspective, understanding how different risk factors affect life expectancy and disability-free life expectancy is important for cost-benefit analyses of different public health interventions. This study estimates life expectancy and disability-free life expectancy associated with smoking, obesity, and moderate alcohol consumption using the US-based Health and Retirement Study. However, I struggle to see how this study adds much; while it communicates its results well, it is, in essence, a series of univariate comparisons followed by a multivariate comparison. This has been done widely before, such as here and here. Nevertheless, the results reinforce those previous studies. For example, obesity reduced disability-free life expectancy by 3 years for men and 6 years for women.

Credits