Alastair Canaway’s journal round-up for 31st October 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.

Ethical hurdles in the prioritization of oncology care. Applied Health Economics and Health Policy [PubMedPublished 21st October 2016

Recently between health economists, there has been significant scrutiny and disquiet directed towards the Cancer Drugs Fund with Professor Karl Claxton describing it as “an appalling, unfair use of NHS resources”. With the latest reorganization of the Cancer Drugs Fund in mind, this article examining the ethical issues surrounding prioritisation of cancer care was of particular interest. As all health economists will tell you, there is an opportunity cost with any allocation of scarce resources. Likewise, with prioritisation of specific disease groups, there may be equity issues with specific patients’ lives essentially being valued more greatly than those suffering other conditions. This article conducts a systematic review of the oncology literature to examine the ethical issues surrounding inequity in healthcare. The review found that public and political attention often focuses on ‘availability’ of pharmacological treatment in addition to factors that lead to good outcomes. The public and political focus on availability can have perverse consequences as highlighted by the Cancer Drugs Fund: resources are diverted towards availability and away from other more cost-effective areas, and in turn this may have had a detrimental effect on care for non-cancer patients. Additionally, by approving high cost, less cost-effective agents, strain will be placed upon health budgets and causing problems for existing cost-effectiveness thresholds. If prioritisation for cancer drugs is to be pursued then the authors suggest that the question of how to fund new therapies equitably will need to be addressed. Although the above issues will not be new to most, the paper is still worth reading as it: i) gives an overview of the different prioritisation frameworks used across Europe, ii) provides several suggestions for how, if prioritization is to be pursued, it can be done in a fairer manner rather than simply overriding typical HTA decision processes, iii) considers the potential legal consequences of prioritisation and iv) the impact of prioritisation on the sustainability of healthcare funding.

Doctor-patient differences in risk and time preferences: a field experiment. Journal of Health Economics Published 19th October 2016

The patient-doctor agency interaction, and associated issues due to asymmetrical information is something that was discussed often during my health economics MSc, but rarely during my day to day work. Despite being very familiar with supplier induced demand, differences in risk and time preferences in the patient-doctor dyad wasn’t something I’d considered in recent times. Upon reading, immediately, it is clear that if risk and time preferences do differ, then what is seen as the optimal treatment for the patient may be very different to that of the doctor. This may lead to poorer adherence to treatments and worse outcomes. This paper sought to investigate whether patients and their doctors had similar time and risk preferences using a framed field experiment with 300 patients and 67 doctors in Athens, Greece in a natural clinical setting. The authors claim to be the first to attempt this, and have three main findings: i) there were significant time preference differences between the patients and doctors – doctors discounted future health gains and financial outcomes less heavily than patients; ii) there were no significant differences in risk preferences for health with both doctors and patients being mildly risk averse; iii) there were however risk preference differences for financial impacts with doctors being more risk averse than patients. The implication of this paper is that there is potential for improvements in doctor-patient communication for treatments, and as agents for patients, doctors should attempts to gauge their patient’s preferences and attitudes before recommending treatment. For those who heavily discount the future it may be preferable to provide care that increases the short term benefits.

Hospital productivity growth in the English NHS 2008/09 to 2013/14 [PDF]. Centre for Health Economics Research Paper [RePEcPublished 21st October 2016

Although this is technically a ‘journal round-up’, this week I’ve chosen to include the latest CHE report as I think it is something which may be of wider interest to the AHEBlog community. Given limited resources, there is an unerring call for both productivity and efficiency gains within the NHS. The CHE report examines the extent to which NHS hospitals have improved productivity: have they made better use of their resources by increasing the number of patients they treat and the services they deliver for the same or fewer inputs. To assess productivity, the report uses established methods: Total Factor Productivity (TFP) which is the ratio of all outputs to all inputs. Growth in TFP is seen as being key to improving patient care with limited resources. The primary report finding was that TFP growth at the trust level exhibits ‘extraordinary volatility’. For example one year there maybe TFP growth followed by negative growth the next year, and then positive growth. The authors assert that much of the TFP growth measured is in fact implausible, and much of the changes are driven largely by nominal effects alongside some real changes. These nominal effects may be data entry errors or changes in accounting practices and data recording processes which results in changes to the timing of the recording of outputs and inputs. This is an important finding for research assessing productivity growth within the NHS. The TFP approach is an established methodology, yet as this research demonstrates, such methods do not provide credible measures of productivity at the hospital level. If hospital level productivity growth is to be measured credibly, then a new methodology will be required.

Credits

Chris Sampson’s journal round-up for 25th July 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.

The income-health relationship ‘beyond the mean’: new evidence from biomarkers. Health Economics [PubMed] Published 15th July 2016

Going ‘beyond the mean’ is becoming a big deal in health economics, as we get better data and develop new tools for analysis. In economic evaluation we’re finding our feet in the age of personalised medicine. As this new study shows, analogous changes are taking place in the econometrics literature. We all know that income correlates with measures of health, but we know a lot less about the nature of this correlation. If we want to target policy in the most cost-effective way, simply asserting that higher income (on average) improves health is not that useful. This study uses a new econometric technique known as the recentered influence function (RIF) to look at the income-health relationship ‘beyond the mean’. It considers blood-based biomarkers with known disease associations as indicators of health, specifically: cholesterol, HbA1c, Fibrinogen and Ferritin. Even for someone with limited willingness to engage with econometrics (e.g. me) the methods are surprisingly elegant and intuitive. In short, the analysis divides people (in terms of each biomarker) into quantiles. So, for example, we can look at the people with high HbA1c (related to diabetes) and see if the relationship with income is different to that for people with a low HbA1c. The study finds that the income-health relationship is non-linear across the health distribution, thus proving the merit of the RIF approach. Generally, the income gradients were higher at the top quintiles. This suggests that income may be more important in tipping a person over the edge – in terms of clinical cut-offs – than in affecting the health of people who are closer to the average. The analysis for cholesterol showed that looking only at the mean (i.e. income increases cholesterol) might hide a positive relationship for most of the distribution but a negative relationship at the top end. This could translate into very different policy implications. The study carried out further decomposition analyses to look at gender differences, which support further differentiation in policy. This kind of analysis will become increasingly important in policy development and evaluation. We might start to see public interventions being exposed as useless for most people, and perhaps actively harmful for some, even if they look good on average.

Using patient-reported outcomes for economic evaluation: getting the timing right. Value in Health Published 15th July 2016

The estimation of QALYs involves an ‘area under the curve’ approach to outcome measurement. How accurately the estimate represents the ‘true’ number of QALYs (if there is such a thing) depends both on where the dots (i.e. data collection points) are and how we connect them. This study looks at the importance of these methodological decisions. Most of us (I think) would use linear interpolation between time points, but the authors also consider an alternative assumption that the health state utility value applies to the whole of the preceding period. The study looks at data for total knee arthroplasty with SF-12 data at 6 weeks, 3 and 6 months and then annually up to 5 years after the operation. The authors evaluated the use of alternative single postoperative SF-6D scores compared with using all of the data, and both linear and immediate interpolation. This gave 12 alternative scenarios. Collecting only at 3 months and using linear interpolation gave a surprisingly similar profile to the ‘true’ number of QALYs, at only about 5% too high. Collecting only at 6 weeks would underestimate QALY gain by 41%, while 6 months and 12 months would be 18% too high and 8% too low, respectively. It’s easy to see that the more data you can collect, the more accurate will be your results. This study shows how important it can be to collect health state data at the most appropriate time. 3 months seems to be the figure for total knee arthroplasty, but it will likely differ for other interventions.

Should the NHS abolish the purchaser-provider split? BMJ [PubMed] Published 12th July 2016

The NHS in England (notably not Scotland or Wales) operates with what’s known as the ‘internal market’, which separates the NHS’s functions as purchasers of health care and as providers of health care. In this BMJ ‘Head to Head’, Alan Maynard argues that it ought to be abolished, while Michael Dixon (a GP) defends its maintenance. Maynard argues that the internal market has been an expensive experiment, and that the results of the experiment have not been well-recorded. The Care Quality Commission and Monitor – organisations supporting the internal market – cost around £300 million to run in 2014/15. Dixon argues that the purchaser-provider split offered “refreshingly new accountability” to local commissioners with front-line experience rather than to the Department of Health. Though Dixon seems to be defending an idealised version of commissioning, rather than what is actually observed in practice. Neither party’s argument is particularly compelling because neither draws on any strong empirical findings. That’s because convincing evidence doesn’t exist either way.

The impact of women’s health clinic closures on preventive care. American Economic Journal: Applied Economics [RePEcPublished July 2016

More than the UK, the US has a problem with anti-abortion campaigns having political influence to the extent that they affect the availability of health services for women. This study is interested in cancer screenings and routine check-ups, which aren’t politically contentious. The authors obtain data that include clinic locations and survey responses from the Behavioural Risk Factor Surveillance System. The analysis relates to Texas and Wisconsin, which are states that implemented major funding cuts to family planning services and women’s health centres between 2007 and 2012. 25% of clinics in Texas closed during this period. As centres close, and women are required to travel further, we’d expect use of services to decline. There might also be knock-on effects in terms of waiting times and prices at the remaining centres. The analyses focus on the effect of distance to the nearest facility on use of preventive services, controlling for demographics and fixed effects relating to location and time. The principal finding is that an increase in distance to a woman’s nearest facility is likely to reduce use of preventive care, namely Pap tests and clinical breast exams. A 100-mile increase in the distance to the nearest centre was associated with a 7.4% percentage point drop in propensity to receive a breast exam in the past year, and 8.7% for Pap tests. Furthermore, the analysis shows that the impact is greater for individuals with lower educational attainment, particularly in the case of mammography. These findings demonstrate the threat to women’s health posed by political posturing.

Photo credit: Antony Theobald (CC BY-NC-ND 2.0)

Paul Mitchell’s journal round-up for 25th April 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.

Cost of care for cancer patients in England: evidence from population-based patient-level data. British Journal of Cancer [PubMedPublished 12th April 2016

It is tempting to be sceptical of some of the economic costing of health conditions that is conducted in the academic literature, with often heroic assumptions made to hyperbolise the burden of disease X on society. However, the analysis conducted in this study on the costs of cancer care in England could not be labelled as one of them, and it gives a good example of making the most of routinely collected data to estimate the costs of conditions related to hospital care. By combining data from the National Cancer Data Repository and the Hospital Episode Statistics (an administrative dataset that records all hospital episodes in England), the authors are able to conduct long-term cost analysis that the authors argue has been restricted to analysis in the United States previously. The authors estimate the cost of breast, colorectal, lung and prostate cancer diagnosis in the period of 2001-2010. As well as estimating the cost per cancer per year, they also undertake a curious “phase of care” costing, broken up into three phases: 1. Initial (first six months post diagnosis), 2. Terminal (final 12 months of life) and 3. Continuum (time period between initial and terminal). The authors also conduct subgroup analysis by age (18-64 vs 65 years and older) and cancer stage, where available. In total, the authors find that the four cancers under examination cost approximately 3% (£1.5bn) of the English hospital care budget in 2010. The authors also find a higher increment in cost in treating the 18-64 age group in the initial phase post diagnosis compared to the 65 years and older age group, that the authors apportion to a higher probability of surgery in younger people. Although the authors are right to claim their costing methodology offers advances on more top-down approaches conducted previously, a number of factors remain unaccounted for in this analysis. They do acknowledge the missing primary and social care services in this analysis, but the lack of costing of pharmaceutical intervention in cancer when it is likely to make up a significant percentage of total costs is something that needs to be considered in future analysis to estimate the overall cost associated with the four cancers. Nonetheless, the analysis presented here does show what can be done by making the most of data that is currently available.

Shaping the research agenda to estimate relevant cost-effectiveness thresholds for health technology assessment decision making: report from the ABPI. OHE Consulting Reports Published 18th April 2016

The cost-effectiveness threshold for spending on the English NHS has been subject to much debate recently, with research findings led by University of York health economists suggesting the threshold should be reduced from £20,000 to £13,000 per quality-adjusted life year gained, arguing that this is a more accurate representation of the cost of displacing current health care services with new interventions (Claxton et al. 2015). Among the leading critiques of this research finding has been the Office of Health Economics, and in this study they have conducted interviews and a workshop to identify alternative ways of setting the cost-effectiveness threshold. In 2015, 15 leading UK health economists were interviewed for their views on how they felt the cost-effectiveness threshold should be set. The majority of the economists interviewed felt that the threshold should represent the shadow price opportunity cost of investment, as opposed to society’s willingness to pay for QALY gains. Only one economist felt the evidence provided in a cost per QALY economic evaluation gave sufficient evidence to make a decision, with over 1 in 3 arguing for the need to also consider some form of equity considerations. Another key finding was that half of the economists believe that cost-effectiveness should be further extended from new interventions to existing services. Although the paper has not been through a peer review process, with questionable methodology in the interview guide potentially containing leading questions, there is much still to be gained from this study for readers interested in how experienced health economists survey current practice. Particularly, it is important for any economist working in evaluations to know the limits on the generalisability of standard cost-effectiveness studies. A workshop with some of the interviewed economists was conducted following the interviews to identify key areas for improving cost-effectiveness research. I think three areas identified warrant immediate attention in the health economics community. Cost-effectiveness analysis is typically performed for national guidelines but it would be of benefit to consider how cost-effectiveness can also be made more applicable at the regional commissioning level, as well as the individual clinician level. Finally, given budget impact is not accounted for in standard economic evaluation, as highlighted by the recent example of the cost-effective but expensive hepatitis C drug, affordability is a key area of concern for the discipline supposed to deal with scarcity. Any takers?

Comprehensively measuring health-related subjective well-being: dimensionality analysis for improved outcome assessment in health economics. Value in Health [PubMedPublished 28th January 2016

One focus in the previous OHE study looked at trying to measure value beyond the QALY outcome. Recent economic attempts to incorporate broader outcome assessments have looked at measuring a person’s capability to achieve in life or an individual’s subjective wellbeing (SWB), both novel approaches drawing from different theoretical bases. On first reading, a new approach appears to be proposed in this recent study, where the authors argue instead for a focus on health-related subjective well-being (HR-SWB). Their argument for this proposal lies in the need to take greater account of the mental and social aspects of health than current measures used to generate QALYs do (e.g. EQ-5D), in order to more accurately measure health as defined in the 1940s by the WHO. In this paper, the authors test a 21 domain, 56 item HR-SWB questionnaire they have previously developed in a Dutch general population sample. They undertake factor analysis to try and pull out the distinctive aspects of health their wide ranging questionnaire is currently picking up. They test it with a large number of previously validated measures including ones of health status (EQ-5D-3L), capability (ICECAP-O) and SWB (SWLS). From the analysis undertaken, a five factor loading appears to the authors as the best fit. They state the five factors focus on “physical independence”, “positive affect/happiness”, “negative affect/feeling lost and lonely”, “autonomy”, and “personal growth”. Only one of the validated measures that focuses on emotional wellbeing was found to be associated with all five factors, with the EQ-5D not loading onto the “negative affect/feeling lost and lonely”, and both the ICECAP-O and SWLS not loading onto the “physical independence” factor. Overall, the HR-SWB measure was best explained by the SWB measure (SWLS, R2=0.71), with the EQ-5D (R2=0.45) and ICECAP-O (R2=0.53) not performing as well. When referring to SWB, the authors are not referring to it in the same way as to how welfare economists are developing the approach as a measure of individual utility (more broadly defined than health-related utility for QALY measurement). The authors now plan to reduce their lengthy questionnaire further into a HR-SWB-5D health utility instrument for generating QALYs with 5-10 items. On that basis, the authors clearly see their measure as one of health and not wellbeing more generally, so they may want to revisit the terminology they have used, as it could be easily misinterpreted.