Chris Sampson’s journal round-up for 28th October 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.

Spatial competition and quality: evidence from the English family doctor market. Journal of Health Economics [RePEc] Published 17th October 2019

Researchers will never stop asking questions about the role of competition in health care. There’s a substantial body of literature now suggesting that greater competition in the context of regulated prices may bring some quality benefits. But with weak indicators of quality and limited generalisability, it isn’t a closed case. One context in which evidence has been lacking is in health care beyond the hospital. In the NHS, an individual’s choice of GP practice is perhaps the context in which quality can be observed and choice most readily (and meaningfully) exercised. That’s where this study comes in. Aside from the horrible format of a ‘proper economics’ paper (where we start with spoilers and climax with robustness tests), it’s a good read.

The study relies on a measure of competition based on the number of rival GPs within a 2km radius. Number of GPs, that is, rather than number of practices. This is important, as the number of GPs per practice has been increasing. About 75% of a practice’s revenues are linked to the number of patients registered, wherein lies the incentive to compete with other practices for patients. And, in this context, research has shown that patient choice is responsive to indicators of quality. The study uses data for 2005-2012 from all GP practices in England, making it an impressive data set.

The measures of quality come from the Quality and Outcomes Framework (QOF) and the General Practice Patient Survey (GPPS) – the former providing indicators of clinical quality and the latter providing indicators of patient experience. A series of OLS regressions are run on the different outcome measures, with practice fixed effects and various characteristics of the population. The models show that all of the quality indicators are improved by greater competition, but the effect is very small. For example, an extra competing GP within a 2km radius results in 0.035% increase in the percentage of the population for whom the QOF indicators have been achieved. The effects are a little stronger for the patient satisfaction indicators.

The paper reports a bunch of important robustness checks. For instance, the authors try to test whether practices select their locations based on the patient casemix, finding no evidence that they do. The authors even go so far as to test the impact of a policy change, which resulted in an exogenous increase in the number of GPs in some areas but not others. The main findings seem to have withstood all the tests. They also try out a lagged model, which gives similar results.

The findings from this study slot in comfortably with the existing body of research on the role of competition in the NHS. More competition might help to achieve quality improvement, but it hardly seems worthy of dedicating much effort or, importantly, much expense to the cause.

Worth living or worth dying? The views of the general public about allowing disabled children to die. Journal of Medical Ethics [PhilPapers] [PubMed] Published 15th October 2019

Recent years have seen a series of cases in the UK where (usually very young) children have been so unwell and with such a severe prognosis that someone (usually a physician) has judged that continued treatment is not warranted and that the child should be allowed to die. These cases have generated debate and outrage in the media. But what do people actually think?

This study recruited members of the public in the UK (n=130) to an online panel and asked about the decisions that participants would support. The survey had three parts. The first part set out six scenarios of hospitalised infants, which varied in terms of the infants’ physical and sensory abilities, cognitive capacity, level of suffering, and future prospects. Some of the cases approximated real cases that have received media coverage, and the participants were asked whether they thought that withdrawing treatment was justified in each case. In the second part of the survey, participants were asked about the factors that they believed were important in making such decisions. In the third part, participants answered a few questions about themselves and answered the Oxford Utilitarianism Scale.

The authors set up the concept of a ‘life not worth living’, based on the idea that net future well-being is ‘negative’, and supposing the individual’s own judgement were they able to provide it. In the first part of the survey, 88% indicated that life would be worse than death in at least one of the cases. In such cases, 65% thought that treatment withdrawal was ethically obligatory, while 33% thought that either decision was acceptable. Pain was considered the most important factor in making such decisions, followed by the presence of pleasure. Perhaps predictably for health economists familiar with the literature, about 42% of people thought that resources should be considered in the decision, while 40% thought they shouldn’t.

The paper includes an extensive discussion, with plenty of food for thought. In particular, it discusses the ways in which the findings might inform the debate between the ‘zero line view’, whereby treatment should be withdrawn at the point where life has no benefit, and the ‘threshold view’, which establishes a grey zone of ethical uncertainty, in which either decision is ethically acceptable. To some extent, the findings of this study support the need for a threshold approach. Ethical questions are rarely black and white.

How is the trade-off between adverse selection and discrimination risk affected by genetic testing? Theory and experiment. Journal of Health Economics [PubMed] [RePEc] Published 1st October 2019

A lot of people are worried about how knowledge of their genetic information could be used against them. The most obvious scenario is one in which insurers increase premiums – or deny coverage altogether – on the basis of genetic risk factors. There are two key regulatory options in this context – disclosure duty, whereby individuals are obliged to tell insurers about the outcome of genetic tests, or consent law, whereby people can keep the findings to themselves. This study explores how people behave under each of these regulations.

The authors set up a theoretical model in which individuals can choose whether to purchase a genetic test that can identify them as being either high-risk or low-risk of developing some generic illness. The authors outline utility functions under disclosure duty and consent law. Under disclosure duty, individuals face a choice between the certainty of not knowing their risk and receiving pooled insurance premiums, or a lottery in which they have to disclose their level of risk and receive a higher or lower premium accordingly. Under consent law, individuals will only reveal their test results if they are at low risk, thus securing lower premiums and contributing to adverse selection. As a result, individuals will be more willing to take a test under consent law than under disclosure duty, all else equal.

After setting out their model (at great length), the authors go on to describe an experiment that they conducted with 67 economics students, to elicit preferences within and between the different regulatory settings. The experiment was set up in a very generic way, not related to health at all. Participants were presented with a series of tasks across which the parameters representing the price of the test and the pooled premium were varied. All of the authors’ hypotheses were supported by the experiment. More people took tests under consent law. Higher test prices reduce the number of people taking tests. If prices are high enough, people will prefer disclosure duty. The likelihood that people take tests under consent law is increasing with the level of adverse selection. And people are very sensitive to the level of discrimination risk under disclosure duty.

It’s an interesting study, but I’m not sure how much it can tell us about genetic testing. Framing the experiment as entirely unrelated to health seems especially unwise. People’s risk preferences may be very different in the domain of real health than in the hypothetical monetary domain. In the real world, there’s a lot more at stake.

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Chris Sampson’s journal round-up for 2nd July 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.

Choice in the presence of experts: the role of general practitioners in patients’ hospital choice. Journal of Health Economics [PubMed] [RePEc] Published 26th June 2018

In the UK, patients are in principle free to choose which hospital they use for elective procedures. However, as these choices operate through a GP referral, the extent to which the choice is ‘free’ is limited. The choice set is provided by the GP and thus there are two decision-makers. It’s a classic example of the principal-agent relationship. What’s best for the patient and what’s best for the local health care budget might not align. The focus of this study is on the applied importance of this dynamic and the idea that econometric studies that ignore it – by looking only at patient decision-making or only at GP decision-making – may give bias estimates. The author outlines a two-stage model for the choice process that takes place. Hospital characteristics can affect choices in three ways: i) by only influencing the choice set that the GP presents to the patient, e.g. hospital quality, ii) by only influencing the patient’s choice from the set, e.g. hospital amenities, and iii) by influencing both, e.g. waiting times. The study uses Hospital Episode Statistics for 30,000 hip replacements that took place in 2011/12, referred by 4,721 GPs to 168 hospitals, to examine revealed preferences. The choice set for each patient is not observed, so a key assumption is that all hospitals to which a GP made referrals in the period are included in the choice set presented to patients. The main findings are that both GPs and patients are influenced primarily by distance. GPs are influenced by hospital quality and the budget impact of referrals, while distance and waiting times explain patient choices. For patients, parking spaces seem to be more important than mortality ratios. The results support the notion that patients defer to GPs in assessing quality. In places, it’s difficult to follow what the author did and why they did it. But in essence, the author is looking for (and in most cases finding) reasons not to ignore GPs’ preselection of choice sets when conducting econometric analyses involving patient choice. Econometricians should take note. And policymakers should be asking whether freedom of choice is sensible when patients prioritise parking and when variable GP incentives could give rise to heterogeneous standards of care.

Using evidence from randomised controlled trials in economic models: what information is relevant and is there a minimum amount of sample data required to make decisions? PharmacoEconomics [PubMed] Published 20th June 2018

You’re probably aware of the classic ‘irrelevance of inference’ argument. Statistical significance is irrelevant in deciding whether or not to fund a health technology, because we ought to do whatever we expect to be best on average. This new paper argues the case for irrelevance in other domains, namely multiplicity (e.g. multiple testing) and sample size. With a primer on hypothesis testing, the author sets out the regulatory perspective. Multiplicity inflates the chance of a type I error, so regulators worry about it. That’s why triallists often obsess over primary outcomes (and avoiding multiplicity). But when we build decision models, we rely on all sorts of outcomes from all sorts of studies, and QALYs are never the primary outcome. So what does this mean for reimbursement decision-making? Reimbursement is based on expected net benefit as derived using decision models, which are Bayesian by definition. Within a Bayesian framework of probabilistic sensitivity analysis, data for relevant parameters should never be disregarded on the basis of the status of their collection in a trial, and it is up to the analyst to properly specify a model that properly accounts for the effects of multiplicity and other sources of uncertainty. The author outlines how this operates in three settings: i) estimating treatment effects for rare events, ii) the number of trials available for a meta-analysis, and iii) the estimation of population mean overall survival. It isn’t so much that multiplicity and sample size are irrelevant, as they could inform the analysis, but rather that no data is too weak for a Bayesian analyst.

Life satisfaction, QALYs, and the monetary value of health. Social Science & Medicine [PubMed] Published 18th June 2018

One of this blog’s first ever posts was on the subject of ‘the well-being valuation approach‘ but, to date, I don’t think we’ve ever covered a study in the round-up that uses this method. In essence, the method is about estimating trade-offs between (for example) income and some measure of subjective well-being, or some health condition, in order to estimate the income equivalence for that state. This study attempts to estimate the (Australian) dollar value of QALYs, as measured using the SF-6D. Thus, the study is a rival cousin to the Claxton-esque opportunity cost approach, and a rival sibling to stated preference ‘social value of a QALY’ approaches. The authors are trying to identify a threshold value on the basis of revealed preferences. The analysis is conducted using 14 waves of the Australian HILDA panel, with more than 200,000 person-year responses. A regression model estimates the impact on life satisfaction of income, SF-6D index scores, and the presence of long-term conditions. The authors adopt an instrumental variable approach to try and address the endogeneity of life satisfaction and income, using an indicator of ‘financial worsening’ to approximate an income shock. The estimated value of a QALY is found to be around A$42,000 (~£23,500) over a 2-year period. Over the long-term, it’s higher, at around A$67,000 (~£37,500), because individuals are found to discount money differently to health. The results also demonstrate that individuals are willing to pay around A$2,000 to avoid a long-term condition on top of the value of a QALY. The authors apply their approach to a few examples from the literature to demonstrate the implications of using well-being valuation in the economic evaluation of health care. As with all uses of experienced utility in the health domain, adaptation is a big concern. But a key advantage is that this approach can be easily applied to large sets of survey data, giving powerful results. However, I haven’t quite got my head around how meaningful the results are. SF-6D index values – as used in this study – are generated on the basis of stated preferences. So to what extent are we measuring revealed preferences? And if it’s some combination of stated and revealed preference, how should we interpret willingness to pay values?

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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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