Chris Sampson’s journal round-up for 24th February 2020

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.

Should health economic evaluations undertaken from a societal perspective include net government spending multiplier effects? Applied Health Economics and Health Policy [PubMed] Published 4th February 2020

Any mention of “macroeconomics” usually causes my eyes to glaze over and my mind to return to 2007 and to ECN202. With some luck, I might scrape through the conversation as I did my second year of undergrad. Perhaps other health economists share my affliction, and that’s why fiscal multipliers haven’t been paid much attention. This paper seeks to redress the balance by considering the possible importance of accounting for the general effects of health expenditure on the economy.

The title of the paper raises the question of ‘should‘, but it’s really more about the ‘could‘. The authors start out by reminding us what a fiscal multiplier is and how it is commonly used and estimated. In short, it’s the amount of expansion we might expect to see in an economy relative to government expenditure. So, with a fiscal multiplier of 1.5, the government spending £1 would expand the economy by £1.50. This study is conducted in the Australian context, so the authors do a bit of groundwork to identify a multiplier for Australia of 1.1. Then, the authors proceed to use this multiplier for domestic expenditure in health care, to demonstrate the potential importance of its use in estimating the societal benefits of health care expenditure.

Two previously conducted economic evaluations are used as test cases. One case study is for a pharmaceutical intervention and the other is for physiotherapy. The key difference between the two – as far as this analysis is concerned – is that the pharmaceutical is produced outside of Australia, with 77% of the expenditure falling outside of the country. Physiotherapy is largely based in expenditure on domestic labour, with only 3% of expenditure falling outside of Australia. What this means is that the effective cost-effectiveness of the pharmaceutical is reduced, while the cost-effectiveness of the physiotherapy is increased. The difference in the case of the pharmaceutical is quite large, with the incremental cost-effectiveness ratio shifting from $31,244 to $47,311 per QALY. Clearly, this could affect decision-making, with implications for cost-effectiveness thresholds.

Personally, I’m a societal perspective sceptic. So, from my position, the main value of considering fiscal multipliers is not from using them to estimate the cost-effectiveness of individual interventions, but rather to help to determine industrial policy. As the authors explain, this approach can be used to identify the value of having health care industries base their operations within a country. Perhaps we could get to the point where a pharmaceutical manufacturer enjoys a higher threshold in a given country if they also pay more taxes. From a (national) societal perspective, there’s a satisfying logic in that.

Whom should we ask? A systematic literature review of the arguments regarding the most accurate source of information for valuation of health states. Quality of Life Research [PubMed] Published 3rd February 2020

For many years, there has been debate about ‘patient’ vs ‘public’ values when it comes to preferences for health states. Gradually, researchers are realising that this is not a useful distinction, as all patients are members of the public and the public are all past and future patients. Nevertheless, there is a useful distinction between valuing a health state based on one’s own current experience and valuing a hypothetical health state. Which should be used to generate quality-adjusted life years (QALYs) to inform resource allocation decisions? In this paper, the authors review the arguments that have been made in the literature.

A literature search was conducted and studies were included in the review if they contained arguments about the source of health state valuations, with 82 articles included. The authors conducted a descriptive qualitative content analysis, grouping arguments into themes at three levels of granularity. The arguments favouring ‘patient’ values related to issues such as the superiority of patient knowledge, adaptation, and patient interests. Arguments in favour of ‘public’ values related to issues such as valuation difficulties for patients, socially directed values, and practical advantages.

This study provides a valuable review of a complex literature, but I believe it is flawed in its conception. There is no such thing as “the most accurate source of information” in this context. For this to be the case, there would need to be some true value that we were seeking to identify. But the value that is most close to the truth depends on our conception of value. Therefore, the answer to the question “which is most accurate?” and “whom should we ask?” are one in the same. This is easily demonstrated by the unanswerable question “how do we define accuracy?” The authors’ attempt to separate the two inevitably fails. Arguments that they frame as ‘irrelevant’ are only irrelevant if we accept the premise that value and decision-making imperatives are separable. The authors’ concluding argument in favour of patient values is both pre-determined by their conception of ‘accuracy’ and groundless.

Nevertheless, I like the paper a lot, as it digests a large amount of information and provides a taxonomy of quotations that will be extremely valuable to researchers developing ideas in this context. My only complaint is that they did not include blog posts in their review!

Health-related quality of life in neonates and infants: a conceptual framework. Quality of Life Research [PubMed] Published 29th January 2020

I’m working on an evaluative study in the context of newborns, and it’s the first time I’ve worked on an intervention where consideration of health-related quality of life (in the short term) – let alone QALYs – is barely even on the table. Yet many interventions and support services for newborns might reasonably be expected to have huge impacts on their quality of life. This study attempts to bring us closer to a world where we can identify QALYs for newborns and infants.

A qualitative study was conducted in a Toronto hospital with two focus groups and five interviews with caregivers of children with intestinal failure and with 14 health care professionals. The focus groups and interviews used open-ended questioning, allowing participants to state what they saw as the most important factors. Fourteen different factors arose, including things like sleep, feeding needs, safety, hygiene, and physical abilities. The authors arranged these into four levels, relating to i) basic needs, ii) non-basic needs, iii) caregivers and family, and iv) society and community.

Much the same dimensions were identified for neonates (0-28 days) and infants (up to one year), but the weighting attributed to the dimensions differed. The importance of non-basic needs increased with age. One implication of this is that time in hospital, where basic needs can be met but other aspects of HRQoL may be limited, may be very good for a neonate but not so good for an older infant. As a result of this, the authors suggest that a weighting algorithm according to age or developmental status may be appropriate. An interesting characterisation of HRQoL that comes out of the study is as a surrogate for the effort required by caregivers to obtain some degree of normalcy in the child’s life. The HRQoL of the individual and of the caregiver(s) is clearly inseparable. But the authors aren’t able to offer much guidance on how this affects measurement.

The authors set out from the position that measuring health-related quality of life in this cohort is important. I don’t know the ethics literature well enough to disagree, so I have to take their word for it. But it does seem that it might be OK for clinical decision-making in this context to be guided by a very different set of criteria to those used in older populations. Whatever the right solution, it will be guided by this important study.


Brent Gibbons’s journal round-up for 10th February 2020

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.

Impact of comprehensive smoking bans on the health of infants and children. American Journal of Health Economics [RePEc] Published 15th January 2020

While debates on tobacco control policies have recently focused on the rising use of e-cigarettes and vaping devices, along with recent associated lung injuries in the U.S., there is still much to learn on the effectiveness of established tobacco control options. In the U.S., while strategies to increase cigarette taxes and to promote smoke-free public spaces have contributed to a decline in smoking prevalence, more stringent policies such as plain packaging, pictorial warning labels, and no point-of-sale advertising have generally not been implemented. Furthermore, comprehensive smoking bans that include restaurants, bars, and workplaces have only been implemented in approximately 60 percent of localities. This article fills an important gap in the evidence on comprehensive smoking bans, answering how this policy affects the health of children. It also provides interesting evidence on the effect of comprehensive smoking bans on smoking behavior in private residences.

There is ample evidence to support the conclusion that smoking bans reduce smoking prevalence and the exposure of nonsmoking adults to second-hand smoke. This reduced second-hand smoke exposure has been linked to reductions in related health conditions for adults, but has not been studied for infants and children. Of particular concern is that smoking bans may have the unintended ‘displacement’ effect of increasing smoking in private residences, potentially increasing exposure for some children and pregnant women.

For their analyses, the authors use nationally representative data from the US Vital Statistics Natality Data and the National Health Interview Survey (NHIS), coupled with detailed local and state tobacco policy data. The policy data allows the authors to look at partial smoking bans (e.g. limited smoking bans in bars and restaurants) versus comprehensive smoking bans, which are defined as 100 percent smoke-free environments in restaurants, bars, and workplaces in a locale. For their main analyses, a difference-in-difference model is used, comparing locales with comprehensive smoking bans to locales with no smoking bans; a counter factual of no smoking bans or partial bans is also used. Outcomes for infants are low birth weight and gestation, while smoke-related adverse health conditions (e.g. asthma) are used for children under 18.

Results support the conclusion that comprehensive smoking bans are linked to positive health effects for infants and children. The authors included local geographic fixed effects, controlled for excise taxes, and tested an impressive array of sensitivity analyses, all of which support the positive findings. For birth outcomes, the mechanism of effect is explored, using self-reported smoking status. The authors find that a majority of the birth outcome effects are likely due to pregnant mothers’ second-hand smoke exposure (80-85 percent), as opposed to a reduction in prenatal smoking. And regarding displacement concerns, the authors examine NHIS data and find no evidence that smoking bans were associated with displacement of smoking to private residences.

This paper is worth a deep dive. The authors have made an important contribution to the evidence on smoking bans, addressing a possible unintended consequence and adding further weight to arguments for extending comprehensive smoking bans nationwide in the U.S. The health implications are non-trivial, where impacts on birth outcomes alone “can prevent between approximately 1,100 and 1,750 low birth weight births among low-educated mothers, resulting in economic cost savings of about $71-111 million annually.”

Europeans’ willingness to pay for ending homelessness: a contingent valuation study. Social Science & Medicine Published 15th January 2020

Housing First (HF) is a social program that originates from a program in the U.S. to address homelessness in Los Angeles. Over time, it has been adapted particularly for individuals with unstable housing who have long-term behavioral health disorders, including mental health and substance use disorders. Similar to other community mental health services, HF has incorporated a philosophy of not requiring conditions before providing services. For example, with supported employment services, to help those with persistent behavioral health disorders gain employment, the currently accepted approach is to ‘place’ individuals in jobs and then provide training and other support; this is opposed to traditional models of ‘train, then place’. Similarly, for housing, the philosophy is to provide housing first, with various wraparound supports available, whether those wraparound services are accepted or not, and whether the person has refrained from substance use or not. The model is based on the logic that without stable housing, other health and social services will be less effective. It is also based on the assertion that stable housing is a basic human right.

Evidence for HF has generally supported its advantage over more traditional policies, especially in its effectiveness in improving stable housing. Other cost offsets have been reported, including health service use reductions, however, the literature is more inconclusive on the existence and amount of cost offsets. The Substance Abuse and Mental Health Services Administration (SAMHSA) has identified HF as an evidence-based model and a number of countries, including the U.S., Canada, and several European countries, have begun incorporating HF into their homelessness policies. Yet the cost effectiveness of HF is not firmly addressed in the literature. At present, results appear favorable towards HF in comparison to other housing policies, though there are considerable difficulties in HF CEAs, most notably that there are multiple measures of effectiveness (e.g. stable housing days and QALYs). More research needs to be done to better establish the cost-effectiveness of HF.

I’ve chosen to highlight this background because Loubiere et al., in this article, have pushed a large contingent valuation (CV) study to assess willingness to pay (WTP) for HF, which the title implies is commensurate with “ending homelessness”. Contingent valuation is generally accepted as one method for valuing resources where no market is available, though not without considerable past criticism. Discrete choice experiments are favored (though not with their own criticism), but the authors decided on CV as the survey was embedded in a longer questionnaire. The study is aimed at policy makers who must take into account broader public preferences for either increased taxation or for a shifting of resources. The intention is laudable in the respect that it attempts to highlight how much the average person would be willing to give up to not have homelessness exist in her country; this information may help policy makers to act. But more important, I would argue, is to have more definitive information on HF’s cost-effectiveness.

As far as the rigor of the study, I was disappointed to see that the survey was performed through telephone, which goes against recommendations to use personal interviews in CV. An iterative bidding process was used which helps to mitigate overvaluation, though there is still the threat of anchoring bias, which was not randomly allocated. There was limited description of what was conveyed to respondents, including what efficacy results were used for HF. This information is important to make appropriate sense of the results. Aside from other survey limitations such as acquiescence bias and non-response bias, the authors did attempt to deal with the issue of ‘protest’ answers by performing alternative analyses with and without protest answers, where protest answers were assigned a €0 value. WTP ranged from an average of €23 (€16 in Poland to €57 in Sweden) to €28 Euros. Analyses were also conducted to understand factors related to reported WTP. The results suggest that Europeans are supportive of reducing homelessness and will give up considerable hard earned cash toward this cause. This reader for one is not convinced. However, I would hope that policy makers, armed with better cost effectiveness research, could make policy decisions for a marginalized group, even without a more rigorous WTP estimate.


David Mott’s journal round-up for 16th September 2019

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.

Opening the ‘black box’: an overview of methods to investigate the decision‑making process in choice‑based surveys. The Patient [PubMed] Published 5th September 2019

Choice-based surveys using methods such as discrete choice experiments (DCEs) and best-worst scaling (BWS) exercises are increasingly being used in health to understand people’s preferences. A lot of time and energy is spent on analysing the data that come out from these surveys but increasingly there is an interest in better understanding respondents’ decision-making processes. Whilst many will be aware of ‘think aloud’ interviews (often used for piloting), other methods may be less familiar as they’re not applied frequently in health. That’s where this fascinating paper by Dan Rigby and colleagues comes in. It provides an overview of five different methods of what they call ‘pre-choice process analysis’ of decision-making, describing the application, state of knowledge, and future research opportunities.

Eye-tracking has been used in health recently. It’s intuitive and provides an insight into where the participants’ focus is (or isn’t). The authors explained that one of the ways it has been used is to explore attribute non-attendance (ANA), which essentially occurs when people are ignoring attributes either because they’re irrelevant to them, or simply because it makes the task easier. However, surprisingly, it has been suggested that ‘visual ANA’ (not looking at the attribute) doesn’t always align with ‘stated ANA’ (participants stating that they ignored the attribute) – which raises some interesting questions!

However, the real highlight for me was the overview of the use of brain imaging techniques to explore choices being made in DCEs. One study highlighted by the authors – which was a DCE about eggs and is now at least #2 on my list of the bizarre preference study topics after this oddly specific one on Iberian ham – predicted choices from an initial ‘passive viewing’ using functional magnetic resonance imaging (fMRI). They found that incorporating changes in blood flow (prompted by changes in attribute levels during ‘passive viewing’) into a random utility model accounted for a lot of the variation in willingness to pay for eggs – pretty amazing stuff.

Whilst I’ve highlighted the more unusual methods here, after reading this overview I have to admit that I’m an even bigger advocate for the ‘think aloud’ technique now. Although it may have some limitations, the amount of insight offered combined with its practicality is hard to beat. Though maybe I’m biased because I know that I won’t get my hands on any eye-tracking or brain imaging devices any time soon. In any case, I highly recommend that any researchers conducting preference studies give this paper a read as it’s really well written and will surely be of interest.

Disentangling public preferences for health gains at end-of-life: further evidence of no support of an end-of-life premium. Social Science & Medicine [PubMed] Published 21st June 2019

The end of life (EOL) policy introduced by NICE in 2009 [PDF] has proven controversial. The policy allows treatments that are not cost-effective within the usual range to be considered for approval, provided that certain criteria are met. Specifically, that the treatment targets patients with a short life expectancy (≤24 months), offers a life extension (of ≥3 months) and is for a ‘small patient population’. One of the biggest issues with this policy is that it is unclear whether the general population actually supports the idea of valuing health gains (specifically life extension) at EOL more than other health gains.

Numerous academic studies, usually involving some form of stated preference exercise, have been conducted to test whether the public might support this EOL premium. A recent review by Koonal Shah and colleagues summarised the existing published studies (up to October 2017), highlighting that evidence is extremely mixed. This recently published Danish study, by Lise Desireé Hansen and Trine Kjær, adds to this literature. The authors conducted an incredibly thorough stated preference exercise to test whether quality of life (QOL) gains and life extension (LE) at EOL are valued differently from other similarly sized health gains. Not only that, but the study also explored the effect of perspective on results (social vs individual), the effect of age (18-35 vs. 65+), and impact of initial severity (25% vs. 40% initial QOL) on results.

Overall, they did not find evidence of support for an EOL premium for QOL gains or for LEs (regardless of perspective) but their results do suggest that QOL gains are preferred over LE. In some scenarios, there was slightly more support for EOL in the social perspective variant, relative to the individual perspective – which seems quite intuitive. Both age and initial severity had an impact on results, with respondents preferring to treat the young and those with worse QOL at baseline. One of the most interesting results for me was within their subgroup analyses, which suggested that women and those with a relation to a terminally ill patient had a significantly positive preference for EOL – but only in the social perspective scenarios.

This is a really well-designed study, which covers a lot of different concepts. This probably doesn’t end the debate on NICE’s use of the EOL criteria – not least because the study wasn’t conducted in England and Wales – but it contributes a lot. I’d consider it a must-read for anyone interested in this area.

How should we capture health state utility in dementia? Comparisons of DEMQOL-Proxy-U and of self- and proxy-completed EQ-5D-5L. Value in Health Published 26th August 2019

Capturing quality of life (QOL) in dementia and obtaining health state utilities is incredibly challenging; which is something that I’ve started to really appreciate recently upon getting involved in a EuroQol-funded ‘bolt-ons’ project. The EQ-5D is not always able to detect meaningful changes in cognitive function and condition-specific preference-based measures (PBMs), such as the DEMQOL, may be preferred as a result. However, this isn’t the only challenge because in many cases patients are not in a position to complete the surveys themselves. This means that proxy-reporting is often required, which could be done by either a professional (formal) carer, or a friend or family member (informal carer). Researchers that want to use a PBM in this population therefore have a lot to consider.

This paper compares the performance of the EQ-5D-5L and the DEMQOL-Proxy when completed by care home residents (EQ-5D-5L only), formal carers and informal carers. The impressive dataset that the authors use contains 1,004 care home residents, across up to three waves, and includes a battery of different cognitive and QOL measures. The overall objective was to compare the performance of the EQ-5D-5L and DEMQOL-Proxy, across the three respondent groups, based on 1) construct validity, 2) criterion validity, and 3) responsiveness.

The authors found that self-reported EQ-5D-5L scores were larger and less responsive to changes in the cognitive measures, but better at capturing residents’ self-reported QOL (based on a non-PBM) relative to proxy-reported scores. It is unclear whether this is a case of adaptation as seen in many other patient groups, or if the residents’ cognitive impairments prevent them from reliably assessing their current status. The proxy-reported EQ-5D-5L scores were generally more responsive to changes in the cognitive measures relative to the DEMQOL-Proxy (irrespective of which type of proxy), which the authors note is probably due to the fact that the DEMQOL-Proxy focuses more on the emotional impact of dementia rather than functional impairment.

Overall, this is a really interesting paper, which highlights the challenges well and illustrates that there is value in collecting these data from both patients and proxies. In terms of the PBM comparison, whilst the authors do not explicitly state it, it does seem that the EQ-5D-5L may have a slight upper hand due to its responsiveness, as well as for pragmatic reasons (the DEMQOL-Proxy has >30 questions). Perhaps a cognition ‘bolt-on’ to the EQ-5D-5L might help to improve the situation in future?