Rita Faria’s journal round-up for 26th August 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.

Vaccine hesitancy and (fake) news: quasi‐experimental evidence from Italy. Health Economics [PubMed] [RePEc] Published 20th August 2019

Has fake news led to fewer children being vaccinated? At least in Italy, the answer seems to be yes.

It’s shocking to read that the WHO has included the reluctance or refusal to vaccinate as one of the 10 threats to global health today. And many of us are asking: why has this happened and what can we do to address it? Vincenzo Carrieri, Leonardo Madio and Francesco Principe help answer this first question. They looked at how fake news affects the take-up of vaccines, assuming that exposure to fake news is proxied by access to broadband and within a difference-in-differences framework. They found that a 10% increase in broadband coverage is associated with a 1.2-1.6% reduction in vaccination rates.

The differences-in-differences method hinges on a court ruling in 2012 that accepted that the MMR vaccine causes autism. Following the ruling, fake news about vaccines spread across the internet. In parallel, broadband coverage increased over time due to a government programme, but it varied by region, depending on the existing infrastructure and geographical conditions. Broadband coverage, by itself, cannot lead to lower vaccination rates. So it makes sense to assume that broadband coverage leads to greater exposure to fake news about vaccines, which in turn leads to lower vaccination rates.

On the other hand, it may be that greater broadband coverage and lower vaccination rates are both caused by something else. The authors wrote a good introduction to justify the model assumptions and show a few robustness checks. Had they had more space, I would have like to read a bit more about the uncertainties around the model assumptions. This is a fantastic paper and good food for thought on the consequences of fake news. Great read!

The cost-effectiveness of one-time birth cohort screening for hepatitis C as part of the National Health Service Health Check programme in England. Value in Health Published 19th August 2019

Jack Williams and colleagues looked at the cost-effectiveness of one-time birth cohort screening for hepatitis C. As hepatitis C is usually asymptomatic before reaching its more advanced stages, people may not be aware that they are infected. Therefore, they may not get tested and treated, even though treatment is effective and cost-effective.

At the level of the individual eligible for testing, the ICERs were between £8k-£31k/QALY, with lower ICERs for younger birth cohorts. The ICERs also depended on the transition probabilities for the progression of the disease, with lower ICERs if progression is faster. Extensive sensitivity and value of information analyses indicate that the key cost-effectiveness drivers are the transition probabilities, probabilities of referral and of treatment post-referral, and the quality of life benefits of being cured.

This is a great example of a good quality applied cost-effectiveness analysis. The model is well justified, the results are thoroughly tested, and the discussion is meticulous. Well done!

NICE, in confidence: an assessment of redaction to obscure confidential information in Single Technology Appraisals by the National Institute for Health and Care Excellence. PharmacoEconomics [PubMed] Published 27th June 2019

NICE walks a fine line between making decisions transparent and protecting confidential information. Confidential information includes commercially sensitive information (e.g. discounts to the price paid by the NHS) and academic-in-confidence information, such as unpublished results of clinical trials. The problem is that the redacted information may preclude readers from understanding NICE decisions.

Ash Bullement and colleagues reviewed NICE appraisals of technologies with an approved price discount. Their goal was to understand the extent of redactions and their consequences on the transparency of NICE decisions. Of the 171 NICE appraisals, 118 had an approved commercial arrangement and 110 had a simple price discount. The type of redacted information varied. Some did not present the ICER, others presented ICERs but not the components of the ICERs, and others did not even present the estimates of life expectancy from the model. Remarkably, the confidential discount could be back-calculated in seven NICE appraisals! The authors also looked at the academic-in-confidence redactions. They found that 68 out of 86 appraisals published before 2018 still had academic-in-confidence information redacted. This made me wonder if NICE has a process to review these redactions and disclose them once the information is in the public domain.

As Ash and colleagues rightly conclude, this review shows that there does not seem to be a consistent process for redaction and disclosure. This is a compelling paper on the practicalities of the NICE process, and with useful reflections for HTA agencies around the world. The message for NICE is that it may be time to review the process to handle sensitive information.

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Chris Sampson’s journal round-up for 27th 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.

Does it pay to know prices in health care? American Economic Journal: Economic Policy Published February 2017

In the US, people in need of health care have to pay for it – or for insurance to cover it – without knowing in advance how much said health care actually costs. Weird, right? Instinctively, it feels as if people really ought to be able to find out. However, if knowing prices in advance doesn’t actually affect consumption, maybe we can say it really doesn’t matter. Well, we can’t. As this new study shows, having access to price information affects consumer choices. There’s plenty of price dispersion to make this potentially important: in this study’s dataset, a move from the 90th to the 50th percentile is on average associated with a price drop of 35%. The data relate to 387,774 procedures for 6,208 people working for a corporate client of a price information firm. Access to this service was staggered for different employees, creating the potential for experimental investigation. The principal strategy is difference-in-differences regression analysis. Access to the price information service was associated with prices around 1.6% lower on average. For primary care – which might be less price sensitive – and for complex cases where lots of procedures are taking place, the effect is weakened. The results seem robust to matching and other tests. The author is able to provide further insight by showing that access to price information increases the probability of seeing a new doctor by 14%. And when an instrumental variable approach is used to assess the price reduction specifically for people who searched for price information and then received a procedure within 30 days, the reduction in price reaches a whopping 17%. This suggests that the average impact of a 1.6% reduction could be a lot higher if people searched for price information more frequently. The fact that they don’t is likely due to a particular kind of moral hazard being at play. Moral hazard in search occurs when people have no incentive to search for cheaper services. The author goes on to show that in any given week an individual is around 90% less likely to search if they have already met their deductible, and that this translates into an elasticity of search propensity to the proportion out-of-pocket expense of approximately 1.8. We mustn’t forget the other side of the welfare coin here. What if people are choosing lower quality care in order to save money, or foregoing it altogether? Looking at the rate of follow-through after searches and bringing in hospital quality data seems to show that this isn’t a concern here. This group of people aren’t representative of the general population so it may be that access to prices is only valuable to certain groups. Nevertheless, this paper tells us a lot about the importance of price information and in particular the special kind of moral hazard that can arise in the presence of comprehensive insurance coverage.

Mitigating the consequences of a health condition: The role of intra- and interhousehold assistance. Journal of Health Economics Published 20th February 2017

There’s a lot of research around the effect that an individual’s health problem can have on their immediate family, both in terms of the overspill in quality of life impacts and the costs of satisfying need for health care. However, large panel data research can be limited because the data can’t connect non-coresident family members. This study considers informal insurance and consumption smoothing within families beyond the current household. The data come from the Panel Study of Income Dynamics, with 7,578 individuals and around 33,000 household years from 2001-2011. The panel follows offspring after they leave a household, facilitating the identification of genetically linked families. Participants are asked whether they suffer from 11 different health problems and, if they do, the extent to which it limits their daily activities. The data also include information on different categories of spending, including health. The analysis involves regression that accounts for individual fixed effects and looks at the impact of a change in health status on consumption. If a household is fully insured, changes in health status should not affect non-health expenditures. The analysis focuses on the impact of severe limitations, which are reported at some point by 1,321 people. Such a change in health status was associated with a reduction in annual working hours of around 20%, corresponding to $5000 for men and $2800 for women. Additionally, household health expenditures increased by $479 on average. The notion of complete insurance facilitating consumption smoothing appears to fail, with a decline in consumption of around 10%. Partial insurance smoothes roughly half the loss. Households with formal insurance exhibit a much smaller reduction in consumption. A key finding is that being married may facilitate consumption smoothing to the extent of full insurance, while unmarried couples take a bigger hit. Home equity seems to play an important role in this dynamic, with married couples more likely to remortgage in response to a health shock. Married couples also receive more in social security transfers. Unmarried couples, it seems, have to turn to non-coresident family members instead and are 50% more likely to use this channel than married couples. Male children are more likely to use their own home equity to support their parents, while female children tend to reduce their own consumption. This study identifies a lot of interesting relationships and divergent strategies for consumption smoothing that warrant further investigation.

Handling missing data in within-trial cost-effectiveness analysis: a review with future recommendations. PharmacoEconomics – Open Published 9th February 2017

If you conduct trial-based cost-effectiveness analyses then chances are that at some point you’ve had to go and figure out how to deal with all that missing data. There are a handful of quality papers out there that offer guidance. If we all followed their advice then we’d be doing a decent job of it. This new paper demonstrates that we aren’t all doing a good job of it and offers fresh guidance. The paper starts by outlining the ‘principled’ approach to handling missing data. Essentially it means being sensible with the data, considering the most appropriate statistical model and describing assumptions about the missing data mechanism. Imputation methods that can support this principled approach are briefly discussed. The authors present a quality evaluation scheme, which can be used to assess the appropriateness of methods adopted in a study and the completeness of reporting. It makes recommendations with respect to the description of missing data, the methods used to handle it and the limitations associated with the study. The quality evaluation scheme can be used to score and rank papers from A-E. This is what the authors go on to do, with a systematic review including 81 eligible papers. A previous review found complete case analysis to be the most popular base case method adopted. In 2009-2015, multiple imputation became the most frequently used base case method, though complete case analysis remains common and many studies are still unclear about the methods adopted. Most articles did not describe any robustness analysis, reporting only the base case approach to missing data. Many articles were classified as the lowest quality (E), though this has improved over time. The authors demonstrate that their proposed grading system is associated with the strength of the assumptions in the adopted methods. If you’re engaged in trial-based economic evaluation, you ought to read this paper.

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