Chris Sampson’s journal round-up for 8th January 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.

An empirical comparison of the measurement properties of the EQ-5D-5L, DEMQOL-U and DEMQOL-Proxy-U for older people in residential care. Quality of Life Research [PubMed] Published 5th January 2018

There is now a condition-specific preference-based measure of health-related quality of life that can be used for people with cognitive impairment: the DEMQOL-U. Beyond the challenge of appropriately defining quality of life in this context, cognitive impairment presents the additional difficulty that individuals may not be able to self-complete a questionnaire. There’s some good evidence that proxy responses can be valid and reliable for people with cognitive impairment. The purpose of this study is to try out the new(ish) EQ-5D-5L in the context of cognitive impairment in a residential setting. Data were taken from an observational study in 17 residential care facilities in Australia. A variety of outcome measures were collected including the EQ-5D-5L (proxy where necessary), a cognitive bolt-on item for the EQ-5D, the DEMQOL-U and the DEMQOL-Proxy-U (from a family member or friend), the Modified Barthel Index, the cognitive impairment Psychogeriatric Assessment Scale (PAS-Cog), and the neuropsychiatric inventory questionnaire (NPI-Q). The researchers tested the correlation, convergent validity, and known-group validity for the various measures. 143 participants self-completed the EQ-5D-5L and DEMQOL-U, while 387 responses were available for the proxy versions. People with a diagnosis of dementia reported higher utility values on the EQ-5D-5L and DEMQOL-U than people without a diagnosis. Correlations between the measures were weak to moderate. Some people reported full health on the EQ-5D-5L despite identifying some impairment on the DEMQOL-U, and some vice versa. The EQ-5D-5L was more strongly correlated with clinical outcome measures than were the DEMQOL-U or DEMQOL-Proxy-U, though the associations were generally weak. The relationship between cognitive impairment and self-completed EQ-5D-5L and DEMQOL-U utilities was not in the expected direction; people with greater cognitive impairment reported higher utility values. There was quite a lot of disagreement between utility values derived from the different measures, so the EQ-5D-5L and DEMQOL-U should not be seen as substitutes. An EQ-QALY is not a DEM-QALY. This is all quite perplexing when it comes to measuring health-related quality of life in people with cognitive impairment. What does it mean if a condition-specific measure does not correlate with the condition? It could be that for people with cognitive impairment the key determinant of their quality of life is only indirectly related to their impairment, and more dependent on their living conditions.

Resolving the “cost-effective but unaffordable” paradox: estimating the health opportunity costs of nonmarginal budget impacts. Value in Health Published 4th January 2018

Back in 2015 (as discussed on this blog), NICE started appraising drugs that were cost-effective but implied such high costs for the NHS that they seemed unaffordable. This forced a consideration of how budget impact should be handled in technology appraisal. But the matter is far from settled and different countries have adopted different approaches. The challenge is to accurately estimate the opportunity cost of an investment, which will depend on the budget impact. A fixed cost-effectiveness threshold isn’t much use. This study builds on York’s earlier work that estimated cost-effectiveness thresholds based on health opportunity costs in the NHS. The researchers attempt to identify cost-effectiveness thresholds that are in accordance with different non-marginal (i.e. large) budget impacts. The idea is that a larger budget impact should imply a lower (i.e. more difficult to satisfy) cost-effectiveness threshold. NHS expenditure data were combined with mortality rates for different disease categories by geographical area. When primary care trusts’ (PCTs) budget allocations change, they transition gradually. This means that – for a period of time – some trusts receive a larger budget than they are expected to need while others receive a smaller budget. The researchers identify these as over-target and under-target accordingly. The expenditure and outcome elasticities associated with changes in the budget are estimated for the different disease groups (defined by programme budgeting categories; PBCs). Expenditure elasticity refers to the change in PBC expenditure given a change in overall NHS expenditure. Outcome elasticity refers to the change in PBC mortality given a change in PBC expenditure. Two econometric approaches are used; an interaction term approach, whereby a subgroup interaction term is used with the expenditure and outcome variables, and a subsample estimation approach, whereby subgroups are analysed separately. Despite the limitations associated with a reduced sample size, the subsample estimation approach is preferred on theoretical grounds. Using this method, under-target PCTs face a cost-per-QALY of £12,047 and over-target PCTs face a cost-per-QALY of £13,464, reflecting diminishing marginal returns. The estimates are used as the basis for identifying a health production function that can approximate the association between budget changes and health opportunity costs. Going back to the motivating example of hepatitis C drugs, a £772 million budget impact would ‘cost’ 61,997 QALYs, rather than the 59,667 that we would expect without accounting for the budget impact. This means that the threshold should be lower (at £12,452 instead of £12,936) for a budget impact of this size. The authors discuss a variety of approaches for ‘smoothing’ the budget impact of such investments. Whether or not you believe the absolute size of the quoted numbers depends on whether you believe the stack of (necessary) assumptions used to reach them. But regardless of that, the authors present an interesting and novel approach to establishing an empirical basis for estimating health opportunity costs when budget impacts are large.

First do no harm – the impact of financial incentives on dental x-rays. Journal of Health Economics [RePEc] Published 30th December 2017

If dentists move from fee-for-service to a salary, or if patients move from co-payment to full exemption, does it influence the frequency of x-rays? That’s the question that the researchers are trying to answer in this study. It’s important because x-rays always present some level of (carcinogenic) risk to patients and should therefore only be used when the benefits are expected to exceed the harms. Financial incentives shouldn’t come into it. If they do, then some dentists aren’t playing by the rules. And that seems to be the case. The authors start out by establishing a theoretical framework for the interaction between patient and dentist, which incorporates the harmful nature of x-rays, dentist remuneration, the patient’s payment arrangements, and the characteristics of each party. This model is used in conjunction with data from NHS Scotland, with 1.3 million treatment claims from 200,000 patients and 3,000 dentists. In 19% of treatments, an x-ray occurs. Some dentists are salaried and some are not, while some people pay charges for treatment and some are exempt. A series of fixed effects models are used to take advantage of these differences in arrangements by modelling the extent to which switches (between arrangements, for patients or dentists) influence the probability of receiving an x-ray. The authors’ preferred model shows that both the dentist’s remuneration arrangement and the patient’s financial status influences the number of x-rays in the direction predicted by the model. That is, fee-for-service and charge exemption results in more x-rays. The combination of these two factors results in a 9.4 percentage point increase in the probability of an x-ray during treatment, relative to salaried dentists with non-exempt patients. While the results do show that financial incentives influence this treatment decision (when they shouldn’t), the authors aren’t able to link the behaviour to patient harm. So we don’t know what percentage of treatments involving x-rays would correspond to the decision rule of benefits exceeding harms. Nevertheless, this is an important piece of work for informing the definition of dentist reimbursement and patient payment mechanisms.

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Paul Mitchell’s journal round-up for 26th December 2016

Every Monday (even if it’s Boxing Day here in the UK) 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.

Out-migration and attrition of physicians and dentists before and after EU accession (2003 and 2011): the case of Hungary. European Journal of Health Economics [PubMedPublished 2nd December 2016

Medical staff migration is an important cross-national policy issue given the international shortage of supply of doctors to meet healthcare demand. This study uses a large administrative survey collected in Hungary from 2004-2011 and focuses on the trends of medical doctors (GPs, specialists, dentists) since Hungary joined the EU in 2004 and the introduction of full freedom of movement between Hungary with Austria and Germany in 2011. The author conducted a time-to-event analysis with monthly collection of data on a person’s occupation used as a guide for outward-migration. A competing-risks model was used to also consider medical doctors exiting the profession, becoming inactive or dying. From the 18,266 medical doctors found in this sample over the nine year period, 12% migrated, 17% exited the profession and 14% became inactive. A five-fold increase in migration was seen when the restrictions on freedom of movement between Hungary and Austria/Germany were lifted, a worrying sign of brain drain from Hungary. For those who stayed but exited the profession, relative income is argued to have been a contributory factor, with incomes increasing by on average 40% in their new line of work (although this does not account for the “thank you money” received by doctors in Hungary for healthcare access). Generous maternity leave was argued to play a key role in absence from employment. A recognised limitation in this study is the inability to conduct robust analysis on the migration patterns of new medical graduates who are likely to be more prone to migration than their established colleagues (estimated to be 40% of all medical graduates in Hungary between 2007-2010 who migrated, before restrictions on freedom of movement between Austria and Germany were lifted). Nonetheless, the study still manages to shine a light on the external (competing against countries with larger economies) but also the internal (“attrition and feminisation of workforce”) challenges to national doctor staffing policy.

Does the proportion of pay linked to performance affect the job satisfaction of general practitioners? Social Science & Medicine [PubMedPublished 24th November 2016

The impact of pay for performance (P4P) on healthcare practice has been subject to much debate surrounding the pros and cons of incentives for medical staff to achieve specific goals. This study focuses on the impact that the introduction of the Quality and Outcomes Framework (QOF) for GPs in the UK in 2004 had on their subsequent job satisfaction. Job satisfaction for GPs is argued to be an important topic area due to it having an important role in retaining GPs and the quality of care they provide to their patients. Using linked data from the the GP Worklife Survey and the QOF, that rewards GPs performance based on clinical, organisation, additional services and patient experience indicators, across three time points (2004, 2005 and 2008), the authors model the relationship between P4P exposure (i.e. the proportion of income related to performance) and job satisfaction. Using a continuous difference-in-difference model with a random effects regression, the authors find that P4P exposure has no significant effect on job satisfaction after 1 and 4 years following the introduction of the QOF P4P system. The introduction of the QOF did lead to a large increase in GP life satisfaction; this is likely to be due to the large increase in average income for GPs following the introduction of QOF. The authors argue that their findings suggest GP job satisfaction is unlikely to be affected by changes in P4P exposure, so long as the final income the GP receives remains constant. Given the generous increases on GP final income from the initial QOF, it remains to be seen how generalisable these results would be to P4P systems that did not lead to such large increases in staff income.

Country-level cost-effectiveness thresholds: initial estimates and the need for further research. Value in Health [PubMed] Published 14th December 2016

National thresholds used to determine if a health intervention is cost-effective have been under scrutiny in the UK in recent years. It has been argued on the grounds of healthcare opportunity costs that the NICE £20,000-30,000 per QALY gained threshold is too high, with an estimate of £13,000 per QALY gain proposed instead. Until now, less attention has been paid to international cost-effectiveness thresholds recommended by the WHO, who have argued for a threshold between one and three times the GDP of a country. This study provides preliminary estimates of cost-effectiveness thresholds across a number of countries with varying levels of national income. Using estimates from the recent £13,000 per QALY gain threshold study in England, a ratio between the supply-side threshold with the consumption value of health was estimated and used as a basis to calculate other national thresholds. The authors use a range of income elasticity estimates for the value placed on a statistical life to take account of uncertainty around these values. The results suggest that even the lower end of the WHO recommended threshold range of 1x national GDP is likely to be an overestimate in most countries. It would appear something closer to 50% of GDP may be a better estimate, albeit with a great amount of uncertainty and variation between high and low income countries. The importance of these estimates according to the authors is that the application of the current WHO thresholds could lead to policies that reduce instead of increase population health. However, the threshold estimates from this study rely on a number of assumptions based on UK data that may not provide an accurate estimate when setting cost-effectiveness thresholds at an international level.

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