Chris Sampson’s journal round-up for 13th March 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.

The effects of exercise and relaxation on health and wellbeing. Health Economics [PubMedPublished 9th Month 2017

Encouraging self-management of health sounds like a good idea, but the evidence is pretty weak. As economists, we know that something must be displaced in order to do it. This study considers the opportunity cost of time and how it might affect self-management activity and any associated benefits. Employment and education are likely to increase income and thus facilitate more expenditure on exercise. But the time cost of exercise is also likely to increase, meaning that the impact on demand is ambiguous. The study uses data from a trial of self-management support that included people with diabetes, COPD or IBS. EQ-5D, self-assessed health and the amount of time spent ‘being happy’ were all collected. Information was available for 12 different self-management activities, including ‘do exercises’ and ‘rest and relax’, and the extent to which individuals did these. Outcomes for 3,472 people at 12-month follow-up are estimated, controlling for outcomes at baseline and 6 months. The study assumes that employment and education affect health via their influence on exercise and relaxation. That seems a bit questionable and the other 10 self-management indicators could have been looked at to test this. People in full-time employment were 11 percentage points less likely to use relaxation to manage their condition, suggesting that the substitution effect on time dominates as the opportunity cost of self-management increases. Having a degree or professional qualification increased the probability of using exercise by 5 percentage points, suggesting that the income effect dominates. Those who are more likely to use either exercise or relaxation are also more likely to do the other. An interesting suggestion is that time preference might explain things here. Those with more education may prefer to exercise (as an investment) than to get the instant gratification of rest and relaxation. It’s important that policy recommendations take into consideration the fact that different groups will respond differently to incentives for self-management, at least partly due to their differing time constraints. The thing I find most interesting is the analysis of the different outcomes (something I’ve worked on). Exercise is found to improve self-assessed health, while relaxation increases happiness. Neither exercise or relaxation had a (statistically significant) effect on EQ-5D. Depending on your perspective, this either suggests that the EQ-5D is failing to identify important changes in broad health-related domains or it means that self-management does not achieve the goals (QALYs to the max) of the health service.

New findings from the time trade-off for income approach to elicit willingness to pay for a quality adjusted life year. The European Journal of Health Economics [PubMedPublished 8th March 2017

The question ‘what is a QALY worth’ could invoke any number of reactions in a health economist, from chin scratching to eye rolling. The perspective that we’re probably most familiar with in the UK is that the value of a QALY is the value of health foregone in order to achieve it (i.e. opportunity cost within the health care perspective). An alternative perspective is that the value of a QALY is the consumption value of health; how much consumption would individuals be willing to give up in order to obtain an additional QALY? This second perspective facilitates a broader societal perspective. It can tell us whether or not the budget is set at an appropriate level, while the health care perspective can only take the budget as given. This study relates mainly to decisions made with the ‘consumption value’ perspective. One approach that has been proposed is to assess willingness to pay for a QALY using a time trade-off exercise that incorporates trade-offs between length and quality of life and income. This study builds on the original work by using a multiplicative utility function to estimate willingness to pay and also bringing in prospect theory to allow for reference dependence and loss aversion. 550 participants were asked to choose between living 10 years in their current health state with their current salary or to live a reduced number of years in their current health state with a luxury income (pre-specified by the participant). Respondents were also asked to make a similar choice, but framed as a loss of income, between living 10 years at a subsistence income or fewer years with their current income. A quality of life trade-off exercise was also conducted, in which people traded reduced health and a lower income. The findings support the predictions of prospect theory. Loss aversion is found to be stronger for duration than for quality of life. Individuals were more willing to sacrifice life years to move from subsistence income to current income than to move from current income to luxury income. The results imply that quality of life and income are closer substitutes than longevity and income. That makes sense, given the all-or-nothing nature of being alive. Crucially, the findings highlight the need to better understand the shape of the underlying lifetime utility function. In all tasks, more than half of respondents were either non-traders or over-traded, indicating a negative willingness to pay. That should give pause for thought when it comes to any aggregation of the results. Willingness to pay studies often throw up more questions than answers. This one does so more than most, particularly about sources of bias in people’s responses. The authors identify plenty of opportunities for future research.

Beyond QALYs: multi-criteria based estimation of maximum willingness to pay for health technologies. The European Journal of Health Economics [PubMed] Published 3rd March 2017

Life is messy. Evaluating things in terms of a single outcome, whether that be QALYs, £££s or whatever, is necessarily simplifying and restrictive. That’s not necessarily a bad thing, but we’d do well to bear it in mind. In this paper, Erik Nord sets out a kind of cost value analysis that does away with QALYs (gasp!). The author starts by outlining some familiar criticisms of the QALY approach, such as its failure to consider the inherent value of life and people’s differing reference points. Generally, I see these as features rather than bugs, and it isn’t QALYs themselves in the crosshairs here so much as cost-per-QALY analysis. The proposed method flips current practice by putting societal preferences about fair and efficient resource allocation before attaching values to the outcomes. As such, it acknowledges the fact that society’s preferences for gains in quality of life differ from those for gains in length of life. For example, society may prefer treating the more severely ill (independent of age) but also exhibit a ‘fair innings’ preference that is related to age. Thus, quality and quantity of life are disaggregated and the QALY is no more. A set of tables is presented that can be read to assess ‘value’ in alternative scenarios, given the assumptions set out in the paper. There is merit in the approach and a lot that I like about the possibilities of its use. But for me, the whole thing was made less attractive by the way it is presented in the paper. The author touts willingness to pay – for quality of life gains and for longevity gains – as the basis for value. Anything that makes resource allocation more dependent on willingness to pay values for things without a price (health, life) is a big no-no for me. But the method doesn’t depend on that. Furthermore, as is so often the case, most of the criticisms within relate to ways of using QALYs, rather than the fundamental basis for their estimation. This only weakens the argument for an alternative. But I can think of plenty of problems with QALYs, some of which might be addressed by this alternative approach. It’s unfortunate that the paper doesn’t outline how these more fundamental problems might be addressed. There may come a day when we do away with QALYs, and we may end up doing something similar to what’s outlined here, but we need to think harder about how this alternative is really better.

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Chris Sampson’s journal round-up for 6th February 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.

A review of NICE methods and processes across health technology assessment programmes: why the differences and what is the impact? Applied Health Economics and Health Policy [PubMed] Published 27th January 2017

Depending on the type of technology under consideration, NICE adopts a variety of different approaches in coming up with their recommendations. Different approaches might result in different decisions, which could undermine allocative efficiency. This study explores this possibility. Data were extracted from the manuals and websites for 5 programmes, under the themes of ‘remit and scope’, ‘process of assessment’, ‘methods of evaluation’ and ‘appraisal of evidence’. Semi-structured interviews were conducted with 5 people with expertise in each of the 5 programmes. Results are presented in a series of tables – one for each theme – outlining the essential characteristics of the 5 programmes. In their discussion, the authors then go on to consider how the identified differences might impact on efficiency from either a ‘utilitarian’ health-maximisation perspective or NICE’s egalitarian aim of ensuring adequate levels of health care. Not all programmes deliver recommendations with mandatory funding status, and it is only the ones that do that have a formal appeals process. Allowing for local rulings on funding could be good or bad news for efficiency, depending on the capacity of local decision makers to conduct economic evaluations (so that means probably bad news). At the same time, regional variation could undermine NICE’s fairness agenda. The evidence considered by the programmes varies, from a narrow focus on clinical and cost-effectiveness to the incorporation of budget impact and wider ethical and social values. Only some of the programmes have reference cases, and those that do are the ones that use cost-per-QALY analysis, which probably isn’t a coincidence. The fact that some programmes use outcomes other than QALYs obviously has the potential to undermine health-maximisation. Most differences or borne of practicality; there’s no point in insisting on a CUA if there is no evidence at all to support one – the appraisal would simply not happen. The very existence of alternative programmes indicates that NICE is not simply concerned with health-maximisation. Additional weight is given to rare conditions, for example. And NICE want to encourage research and innovation. So it’s no surprise that we need to take into account NICE’s egalitarian view to understand the type of efficiency for which it strives.

Economic evaluations alongside efficient study designs using large observational datasets: the PLEASANT trial case study. PharmacoEconomics [PubMed] Published 21st January 2017

One of the worst things about working on trial-based economic evaluations is going to lots of effort to collect lots of data, then finding that at the end of the day you don’t have much to show for it. Nowadays, the health service routinely collects many data for other purposes. There have been proposals to use these data – instead of prospectively collecting data – to conduct clinical trials. This study explores the potential for doing an economic evaluation alongside such a trial. The study uses CPRD data, including diagnostic, clinical and resource use information, for 8,608 trial participants. The intervention was the sending out of a letter in the hope of reducing unscheduled medical contacts due to asthma exacerbation in children starting a new school year. QALYs couldn’t be estimated using the CPRD data, so values were derived from the literature and estimated on the basis of exacerbations indicated by changes in prescriptions or hospitalisations. Note here the potentially artificial correlation between costs and outcomes that this creates, thus somewhat undermining the benefit of some good old bootstrapping. The results suggest the intervention is cost-saving with little impact on QALYs. Lots of sensitivity analyses are conducted, which are interesting in themselves and say something about the concerns around some of the structural assumptions. The authors outline the pros and cons of the approach. It’s an important discussion as it seems that studies like this are going to become increasingly common. Regarding data collection, there’s little doubt that this approach is more efficient, and it should be particularly valuable in the evaluation of public health and service delivery type interventions. The problem is that the study is not able to use individual-level cost and outcome data from the same people, which is what sets a trial-based economic evaluation apart from a model-based study. So for me, this isn’t really a trial-based economic evaluation. Indeed, the analysis incorporates a Markov-type model of exacerbations. It’s a different kind of beast, which incorporates aspects of modelling and aspects of trial-based analysis, along with some unique challenges of its own. There’s a lot more methodological work that needs to be done in this area, but this study demonstrates that it could be fruitful.

“Too much medicine”: insights and explanations from economic theory and research. Social Science & Medicine [PubMed] Published 18th January 2017

Overconsumption of health care represents an inefficient use of resources, and so we wouldn’t recommend it. But is that all we – as economists – have to say on the matter? This study sought to dig a little deeper. A literature search was conducted to establish a working definition of overconsumption. Related notions such as overdiagnosis, overtreatment, overuse, low-value care, overmedicalisation and even ‘pharmaceuticalisation’ all crop up. The authors introduce ‘need’ as a basis for understanding overconsumption; it represents health care that should never be considered as “needed”. A useful distinction is identified between misconsumption – where an individual’s own consumption is detrimental to their own well-being – and overconsumption, which can be understood as having a negative effect on social welfare. Note that in a collectively funded system the two concepts aren’t entirely distinguishable. Misconsumption becomes the focus of the paper, as avoiding harm to patients has been the subject of the “too much medicine” movement. I think this is a shame, and not really consistent with an economist’s usual perspective. The authors go on to discuss issues such as moral hazard, supplier-induced demand, provider payment mechanisms, ‘indication creep’, regret theory, and physicians’ positional consumption, and whether or not such phenomena might lead to individual welfare losses and thus be considered causes of misconsumption. The authors provide a neat diagram showing the various causes of misconsumption on a plane. One dimension represents the extent to which the cause is imperfect knowledge or imperfect agency, and the other the degree to which the cause is at the individual or market level. There’s a big gap in the top right, where market level causes meet imperfect knowledge. This area could have included patent systems, research fraud and dodgy Pharma practices. Or maybe just a portrait of Ben Goldacre for shorthand. There are some warnings about the (limited) extent to which market reforms might address misconsumption, and the proposed remedy for overconsumption is not really an economic one. Rather, a change in culture is prescribed. More research looking at existing treatments rather than technology adoption, and to investigate subgroup effects, is also recommended. The authors further suggest collaboration between health economists and ecological economists.

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Brent Gibbons’s journal round-up for 12th December 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.

As the U.S. moves into a new era with the recent election results, Republicans will have a chance to modify or repeal the Affordable Care Act. The Affordable Care Act (ACA), also called Obamacare, is a comprehensive health reform that was enacted on the 23rd of March, 2010, that helped millions of uninsured individuals and families gain coverage through new private insurance coverage and through expanded Medicaid coverage for those with very low income. The ACA has been nothing short of controversial and has often been at the forefront of partisan divides. The ACA was an attempt to fill the insurance coverage gaps of the patchwork American health insurance system that was built on employer-sponsored insurance (ESI) and a mix of publicly funded programs for various vulnerable subpopulations. The new administration and republican legislators are promising to repeal the law, at least in part, and have suggested plans that will re-emphasize the private insurance model based on ESI. For this reason, the following articles selected for this week’s round-up highlight different aspects of ESI.

The Mental Health Parity and Addiction Equity Act evaluation study: Impact on specialty-behavioral health utilization and expenditures among “carve-out” enrollees. Journal of Health Economics [PubMed] Published December 2016

Behavioral health services have historically been covered at lower levels and with more restrictions by ESI than physical health services. Advocates for behavioral health system reform have pushed for equal coverage of behavioral health services for decades. In 2008, the Mental Health Parity and Addiction Equity Act (MHPAEA) was passed with a fairly comprehensive set of rules for how behavioral health coverage would need to be comparable to medical/surgical coverage, including for ESI. This first article in our round-up examines the impact of this law on utilization and expenditures of behavioral health services in ESI plans. The authors use an individual-level interrupted time series design using panel data with monthly measures of outcomes. Administrative claims and enrollment data are used from a large private insurance company that provides health insurance for a number of large employers in the years 2008 – 2013. A segmented regression analysis is used in order to measure the impact of the law at two different time points, first in 2010 for what is considered a transition year, and then in the 2011 – 2013 period, both compared to the pre-MHPAEA time period, 2008 – 2009. Indicator variables are used for the different periods as well as spline variables to measure the change in level and slope of the time trends, controlling for other explanatory variables. Results suggest that MHPAEA had little effect on utilization and total expenditures, but that out-of-pocket expenditures were shifted from the patient to the health plan. For patients who had positive expenditures, there was a post-MHPAEA level increase in health plan expenditures of $58.03 and a post-MHPAEA level decrease in out-of-pocket expenditure of $21.58, both per-member-per-month. To address worries of confounding time trends, the authors performed several sensitivity analyses, including a difference-in-difference (DID) analysis that used states that already had strict parity legislation as a comparison population. The authors also examined those with a bipolar or schizophrenia disorder to test the hypothesis that impacts may be stronger for individuals with more severe conditions. Sensitivity analyses tended to result in larger p-values. These results, which were examined at the mean, are consistent with reports that the primary change in behavioral health coverage in ESI was the elimination of treatment limits. In addition to using a sensitivity analysis with individuals with bipolar and schizophrenia, it would have been interesting to see impacts for individuals defined as “high-utilizers”. It would also have been nice to see a longer pre-MHPAEA time period since insurers could have adjusted plans prior to the 2010 effective date.

Health plan type variations in spells of health-care treatment. American Journal of Health Economics [RePEcPublished 12th October 2016

Health care costs in the U.S. were roughly 17.8 percent of the GDP in 2015 and attempts to rein in health insurance costs have largely proved elusive. Different private insurance health plans have tried to rein in costs through different plan types that have a mix of supply-side mechanisms and demand-side mechanisms. Two recent plan types that have emerged are exclusive provider organizations (EPOs) and consumer-driven/high-deductible health plans (CDHPs). EPOs use a more narrowly restricted network of providers that agree to lower payments and presumably also deliver quality care while CDHPs give patients broader networks but shift cost-sharing to patients. EPOs therefore are more focused on supply-side mechanisms of cost reduction, while CDHPs emphasize demand-side incentives to reduce costs. Ellis and Zhu use a large ESI claims-based dataset to examine the impact of these two health plan types and to try to answer whether supply-side or demand-side mechanisms of cost reduction are more effective. The authors present an extremely extensive analysis that is really worth reading. They use a technique for modeling periods of care, called treatment “spells” that is a mix of monthly treatment periods and episode-based models of care. Utilization and expenditures are examined in the context of these treatment “spells” for the different health plan types. A 2SLS regression model is used that controls for endogenous plan choice in the first-stage. The predicted probabilities from plan choice are used as an instrument in the second stage along with a number of controls, including risk-adjustment techniques and individual fixed effects. The one drawback in using the predicted probabilities as the sole instrument is it is not possible to perform an exclusion test. The results, however, suggest that neither of the new plan types performs better than a standardly used health plan. EPOs have the lowest overall spending, but are not significantly different than the standard plan type, and CDHPs have 16 percent higher spending than the standard plan type. The CDHPs in particular have not been studied carefully and these results suggest that previous research on CDHPs found cost-savings due to younger and healthier patients and not because of plan type effects. There are also worries with high deductible plans that patients may elect to forgo necessary healthcare services.

The financial burdens of high-deductible plans. Health Affairs [PubMed] Published December 2016

Having discussed the consumer-directed/high deductible health plans, this third journal article looks at the Medical Expenditure Panel Survey (MEPS) data to examine the burden high deductible health plans place on individuals and families with low incomes. High deductible health plans like the CDHPs are increasingly offered. High deductible plans are sometimes paired with the option to use a flexible spending account (FSA). An FSA gives the patient the option to set aside money from her salary or paycheck that can only be used for healthcare costs, with the benefit that the money set aside will not be subject to various income taxes. The benefit of the high deductible plan is supposed to be lower premiums and the possibility of saving money through the FSA, if that option is available. Yet descriptive analyses using MEPS data from 2011 – 2013 from ESI plans show that high deductible plans impose a particularly high burden on individuals with family incomes below 250 percent of the poverty line. Specifically, the authors found that 29.1 percent of individuals with high deductible plans had financial costs exceeding 20 percent of family income, compared to 20.6 percent of individuals with low deductible plans. For individuals with family income greater than 400 percent of the poverty line, financial burden was not different for high deductible plans compared to other plan types. Yet worryingly, individuals with low incomes were just as likely to have high deductible plans as individuals with high incomes.

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