Paul Mitchell’s journal round-up for 17th 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.

What goes wrong with the allocation of domestic and international resources for HIV? Health Economics [PubMedPublished 7th July 2017

Investment in foreign aid is coming under considered scrutiny as a number of leading western economies re-evaluate their role in the world and their obligations to countries with developing economies. Therefore, it is important for those who believe in the benefits of such investments to show that they are being done efficiently. This paper looks at how funding for HIV is distributed both domestically and internationally across countries, using multivariate regression analysis with instruments to control for reverse causality between financing and HIV prevalence, and domestic and international financing. The author is also concerned about countries free riding on international aid and estimates how countries ought to be allocating national resources to HIV using quintile regression to estimate what countries have fiscal space for expanding their current spending domestically. The results of the study show that domestic expenditure relative to GDP per capita is almost unit elastic, whereas it is inelastic with regards to HIV prevalence. Government effectiveness (as defined by the World Bank indices) has a statistically significant effect on domestic expenditure, although it is nonlinear, with gains more likely when moving up from a lower level of government effectiveness. International expenditure is inversely related to GDP per capita and HIV prevalence, and positively with government effectiveness, albeit the regression models for international expenditure had poor explanatory power. Countries with higher GDP per capita tended to dedicate more money towards HIV, however, the author reckons there is $3bn of fiscal space in countries such as South Africa and Nigeria to contribute more to HIV, freeing up international aid for other countries such as Cameroon, Ghana, Thailand, Pakistan and Columbia. The author is concerned that countries with higher GDP should be able to allocate more to HIV, but feels there are improvements to be made in how international aid is distributed too. Although there is plenty of food for thought in this paper, I was left wondering how this analysis can help in aiding a better allocation of resources. The normative model of what funding for HIV ought to be is from the viewpoint that this is the sole objective of countries of allocating resources, which is clearly contestable (the author even casts doubt as to whether this is true for international funding of HIV). Perhaps the other demands faced by national governments (e.g. funding for other diseases, education etc.) can be better reflected in future research in this area.

Can pay-for-performance to primary care providers stimulate appropriate use of antibiotics? Health Economics [PubMed] [RePEcPublished 7th July 2017

Antibiotic resistance is one of the largest challenges facing global health this century. This study from Sweden looks to see whether pay for performance (P4P) can have a role in the prescription practices of GPs when it comes to treating children with respiratory tract infection. P4P was introduced on a staggered basis across a number of regions in Sweden to incentivise primary care to use narrow spectrum penicillin as a first line treatment, as it is said to have a smaller impact on resistance. Taking advantage of data from the Swedish Prescribed Drug Register between 2006-2013, the authors conducted a difference in difference regression analysis to show the effect P4P had on the share of the incentivised antibiotic. They find a positive main effect of P4P on drug prescribing of 1.1 percentage points, that is also statistically significant. Of interest, the P4P in Sweden under analysis here was not directly linked to salaries of GPs but the health care centre. Although there are a number of limitations with the study that the authors clearly highlight in the discussion, it is a good example of how to make the most of routinely available data. It also highlights that although the share of the less resistant antibiotic went up, the national picture of usage of antibiotics did not reduce in line with a national policy aimed at doing so during the same time period. Even though Sweden is reported to be one of the lower users of antibiotics in Europe, it highlights the need to carefully think through how targets are achieved and where incentives might help in some areas to meet such targets.

Econometric modelling of multiple self-reports of health states: the switch from EQ-5D-3L to EQ-5D-5L in evaluating drug therapies for rheumatoid arthritis. Journal of Health Economics Published 4th July 2017

The EQ-5D is the most frequently used health state descriptive system for the generation of utility values for quality-adjusted life years (QALYs) in economic evaluation. To improve sensitivity and reduce floor and ceiling effects, the EuroQol team developed a five level version (5L) compared to the previous three level (3L) version. This study adds to recent evidence in this area of the unforeseen consequences of making this change to the descriptive system and also the valuation system used for the 5L. Using data from the National Data Bank for Rheumatic Diseases, where both 3L and 5L versions were completed simultaneously alongside other clinical measures, the authors construct a mapping between both versions of EQ-5D, informed by the response levels and the valuation systems that have been developed in the UK for the measures. They also test their mapping estimates on a previous economic evaluation for rheumatoid arthritis treatments. The descriptive results show that although there is a high correlation between both versions, and the 5L version achieves its aim of greater sensitivity, there is a systematic difference in utility scores generated using both versions, with an average 87% of the score of the 3L recorded compared to the 5L. Not only are there differences highlighted between value sets for the 3L and 5L but also the responses to dimensions across measures, where the mobility and pain dimensions do not align as one would expect. The new mapping developed in this paper highlights some of the issues with previous mapping methods used in practice, including the assumption of independence of dimension levels from one another that was used while the new valuation for the 5L was being developed. Although the case study they use to demonstrate the effect of using the different approaches in practice did not result in a different cost-effectiveness result, the study does manage to highlight that the assumption of 3L and 5L versions being substitutes for one another, both in terms of descriptive systems and value sets, does not hold. Although the authors are keen to highlight the benefits of their new mapping that produces a smooth distribution from actual to predicted 5L, decision makers will need to be clear about what descriptive system they now want for the generation of QALYs, given the discrepancies between 3L and 5L versions of EQ-5D, so that consistent results are obtained from economic evaluations.

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Meeting round-up: 7th annual Vancouver Health Economics Methodology (VanHEM) meeting

The 7th annual Vancouver Health Economics Methodology (VanHEM) meeting took place on June 16 in Vancouver, Canada. This one-day conference brings together health economists from across the Pacific Northwest, including Vancouver, Washington State, and Calgary. This has always been more than a Vancouver meeting, which led Anirban Basu from Washington State to suggest changing the name of the meeting to the Cascadia Health Economics Workshop (CHEW) – a definite improvement.

This year’s event began a day early, with Richard Grieve from the London School of Hygiene and Tropical Medicine, Stephen O’Neill from NUI Galway, and Jasjeet Sekhon from the University of California Berkeley, delivering a workshop titled Methods for Addressing Confounding in Comparative Effectiveness and Cost-effectiveness Studies. This provided both theoretical and practical examples of propensity score matching, genetic matching, difference-in-difference estimation and the synthetic control method. I was fortunate enough to be one of the 16 attendees (it was oversubscribed) to participate after being unable to attend when the course was offered at the Society for Medical Decision Making conference this past October. The course was an excellent introduction to these methodologies, including both theoretical and empirical examples of their use. I was particularly interested to have R and Stata code provided, to work through real-world examples. Being able to see the data and code and explore different analyses provided an incredibly rich learning experience.

The following morning, Prof Grieve delivered the plenary address to the more than 80 attendees. This talk discussed the potential for causal inference and large-scale data to influence policy, and outlined how observational data can complement evidence from randomized controlled trials (the slides are available here [PDF]). Since the expertise of our health economics community centres on other methods, primarily economic evaluation and stated preference methods, Prof Grieve’s plenary catalyzed a lot of discussion, which continued throughout the day. After the plenary, there were eight papers discussed over four parallel sessions, in addition to ten posters presented over lunch. This included an interesting paper by Nathaniel Hendrix from Washington state on a mapping algorithm between a generic and condition-specific quality-of-life measure for epilepsy, and two papers using discrete choice methodology. One by Tracey-Lea Laba evaluated cost sharing for long-acting beta-agonists in Australia, and another by Dean Regier, Verity Watson and Jonathon Sicsic explored choice certainty and choice consistency in DCEs using Kahneman’s dual processing theory.

Having been to three HESG meetings, there are lots of similarities with the format of VanHEM. For instance, papers are discussed for 20 minutes by another attendee, and the author has 5-minutes for clarification. What is different is that before a wider discussion, members of the audience break into small groups for 5 minutes. In my experience, this addition has been very effective at increasing participation during the final 25 minutes of the session, which is an open discussion amongst all attendees. It also gave attendees the opportunity to swap tips on where to find the best deals on plaid shirts.

I was fortunate enough to have my paper accepted and discussed by Prof Larry Lynd from the UBC Faculty of Pharmaceutical Science. Prof Lynd provided a number of excellent suggestions. Of particular note was a much simpler and more intuitive description of the marginal rate of substitution.

VanHEM also afforded an opportunity for discussion and reflection within the local health economics community. Recently, the Canadian Institutes for Health Research launched the Strategy for Patient-Oriented Research (SPOR). In BC, this involves an $80 million investment to “foster evidence-informed health care by bringing innovative approaches to the point of care, so as to ensure greater quality, accountability, and access of care”. One innovative approach is the creation of a new health economics methods cluster in the province, which is co-led by David Whitehurst (Simon Fraser University) and Nick Bansback (University of British Columbia). It receives SPOR funds to help support the health economics community as a whole, and specific research projects that focus on novel methods. At VanHEM, one hour was dedicated to determining how the cluster could help support the community that sees many health economists located at different sites throughout the region. Participants suggested having a number of dedicated academic half-days throughout the year that aim to provide an opportunity for members of the community to see each other face-to-face and engage in activities that support professional development. The theme of great titles continued with the suggestion of a “HEck-a-thon”.

Overall, this year’s VanHEM meeting was a great success. The addition of a pre-meeting workshop provided an excellent opportunity for our community to gain practical experience in causal methods, and we continue to see increased numbers of participants from outside our local region. I’m looking forward to doing this again in 2018, and I would encourage anyone visiting our region to be in touch!

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Chris Sampson’s journal round-up for 19th June 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.

Health-related resource-use measurement instruments for intersectoral costs and benefits in the education and criminal justice sectors. PharmacoEconomics [PubMed] Published 8th June 2017

Increasingly, people are embracing a societal perspective for economic evaluation. This often requires the identification of costs (and benefits) in non-health sectors such as education and criminal justice. But it feels as if we aren’t as well-versed in capturing these as we are in the health sector. This study reviews the measures that are available to support a broader perspective. The authors search the Database of Instruments for Resource Use Measurement (DIRUM) as well as the usual electronic journal databases. The review also sought to identify the validity and reliability of the instruments. From 167 papers assessed in the review, 26 different measures were identified (half of which were in DIRUM). 21 of the instruments were only used in one study. Half of the measures included items relating to the criminal justice sector, while 21 included education-related items. Common specifics for education included time missed at school, tutoring needs, classroom assistance and attendance at a special school. Criminal justice sector items tended to include legal assistance, prison detainment, court appearances, probation and police contacts. Assessments of the psychometric properties was found for only 7 of the 26 measures, with specific details on the non-health items available for just 2: test-retest reliability for the Child and Adolescent Services Assessment (CASA) and validity for the WPAI+CIQ:SHP,V2 (there isn’t room on the Internet for the full name). So there isn’t much evidence of any validity for any of these measures in the context of intersectoral (non-health) costs and benefits. It’s no doubt the case that health-specific resource use measures aren’t subject to adequate testing, but this study has identified that the problem may be even greater when it comes to intersectoral costs and benefits. Most worrying, perhaps, is the fact that 1 in 5 of the articles identified in the review reported using some unspecified instrument, presumably developed specifically for the study or adapted from an off-the-shelf instrument. The authors propose that a new resource use measure for intersectoral costs and benefits (RUM ICB) be developed from scratch, with reference to existing measures and guidance from experts in education and criminal justice.

Use of large-scale HRQoL datasets to generate individualised predictions and inform patients about the likely benefit of surgery. Quality of Life Research [PubMed] Published 31st May 2017

In the NHS, EQ-5D data are now routinely collected from patients before and after undergoing one of four common procedures. These data can be used to see how much patients’ health improves (or deteriorates) following the operations. However, at the individual level, for a person deciding whether or not to undergo the procedure, aggregate outcomes might not be all that useful. This study relates to the development of a nifty online tool that a prospective patient can use to find out the expected likelihood that they will feel better, the same or worse following the procedure. The data used include EQ-5D-3L responses associated with almost half a million unilateral hip or knee replacements or groin hernia repairs between April 2009 and March 2016. Other variables are also included, and central to this analysis is a Likert scale about improvement or worsening of hip/knee/hernia problems compared to before the operation. The purpose of the study is to group people – based on their pre-operation characteristics – according to their expected postoperative utility scores. The authors employed a recursive Classification and Regression Tree (CART) algorithm to split the datasets into strata according to the risk factors. The final set of risk variables were age, gender, pre-operative EQ-5D-3L profile and symptom duration. The CART analysis grouped people into between 55 and 60 different groups for each of the procedures, with the groupings explaining 14-27% of the variation in postoperative utility scores. Minimally important (positive and negative) differences in the EQ-5D utility score were estimated with reference to changes in the Likert scale for each of the procedures. These ranged in magnitude from 0.041 to 0.106. The resulting algorithms are what drive the results delivered by the online interface (you can go and have a play with it). There are a few limitations to the study, such as the reliance on complete case analysis and the fact that the CART analysis might lack predictive ability. And there’s an interesting problem inherent in all of this, that the more people use the tool, the less representative it will become as it influences selection into treatment. The validity of the tool as a precise risk calculator is quite limited. But that isn’t really the point. The point is that it unlocks some of the potential value of PROMs to provide meaningful guidance in the process of shared decision-making.

Can present biasedness explain early onset of diabetes and subsequent disease progression? Exploring causal inference by linking survey and register data. Social Science & Medicine [PubMed] Published 26th May 2017

The term ‘irrational’ is overused by economists. But one situation in which I am willing to accept it is with respect to excessive present bias. That people don’t pay enough attention to future outcomes seems to be a fundamental limitation of the human brain in the 21st century. When it comes to diabetes and its complications, there are lots of treatments available, but there is only so much that doctors can do. A lot depends on the patient managing their own disease, and it stands to reason that present bias might cause people to manage their diabetes poorly, as the value of not going blind or losing a foot 20 years in the future seems less salient than the joy of eating your own weight in carbs right now. But there’s a question of causality here; does the kind of behaviour associated with time-inconsistent preferences lead to poorer health or vice versa? This study provides some insight on that front. The authors outline an expected utility model with quasi-hyperbolic discounting and probability weighting, and incorporate a present bias coefficient attached to payoffs occurring in the future. Postal questionnaires were collected from 1031 type 2 diabetes patients in Denmark with an online discrete choice experiment as a follow-up. These data were combined with data from a registry of around 9000 diabetes patients, from which the postal/online participants were identified. BMI, HbA1c, age and year of diabetes onset were all available in the registry and the postal survey included physical activity, smoking, EQ-5D, diabetes literacy and education. The DCE was designed to elicit time preferences using the offer of (monetary) lottery wins, with 12 different choice sets presented to all participants. Unfortunately, despite the offer of a real-life lottery award for taking part in the research, only 79 of 1031 completed the online DCE survey. Regression analyses showed that individuals with diabetes since 1999 or earlier, or who were 48 or younger at the time of onset, exhibited present bias. And the present bias seems to be causal. Being inactive, obese, diabetes illiterate and having lower quality of life or poorer glycaemic control were associated with being present biased. These relationships hold when subject to a number of control measures. So it looks as if present bias explains at least part of the variation in self-management and health outcomes for people with diabetes. Clearly, the selection of the small sample is a bit of a concern. It may have meant that people with particular risk preferences (given that the reward was a lottery) were excluded, and so the sample might not be representative. Nevertheless, it seems that at least some people with diabetes could benefit from interventions that increase the salience of future health-related payoffs associated with self-management.

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