Paul Mitchell’s journal round-up for 15th May 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.

Informal care: choice or constraint. Scandinavian Journal of Caring Sciences [PubMed] Published 12th April 2017

The provision of social care in the UK has become a major economic issue, with recent increases in government spending and local authority taxation to help ease the burden on both the health and social care system in the short term. This study examines some of the issues surrounding informal carers (i.e. care of a family member), estimated to be approximately 10% of the UK population. In particular, it focuses on the role of choice and constraints involved with the decision to become a carer. Using a cross-sectional survey for a UK city, choice of caring was explored in terms of responses to care provision provided, asking if it was a free choice initially to provide care, and if there were constraints in terms of duty, lack of others or financial resources for paid care. The analysis focused on how perceived choice in the caring role was associated with socio-demographics and the type of caring role performed, as well as the role of perceived choice in caring and their wellbeing. Out of the 798 respondents to all four questions on caring choice, about 1 in 3 reported an entirely free choice in the decision, with half reporting having a free choice but also a constraint in terms of duty, other available carers or financial resources. Less than 1 in 5 reported not having a free choice. Only carers with bad health or receiving state benefits had an association with a constrained caring role. The more intense the care role was also associated with a more constrained choice. Higher levels of choice were associated with higher levels of wellbeing across measures of happiness, life satisfaction and capability. In multivariable regression analysis, it was found that having a free choice in the initial caring decision resulted in a higher impact on life satisfaction than educational qualifications and home ownership, whilst improved capability of comparable levels to that of home ownership, all else being equal. The authors thus recommend enhanced choice as a way for policy to improve carers wellbeing. Although the authors acknowledge limitations with the study design being cross-sectional and geographically limited to one city, the study shows there is plenty of scope for understanding the determinants of informal caring and consequences for those carers in much greater detail in future national surveys to help address policy in this area in the medium to longer term.

Experienced utility or decision utility for QALY calculation? Both. Public Health Ethics [PhilPapersPublished 6th May 2017

How health states should be valued in population health metrics, like QALYs and DALYs, will not be an unfamiliar topic of discussion for regular readers of this blog. Instead of arguing for decision utility (i.e. accounting for general population preferences for avoiding health states) or experienced utility (i.e. accounting for patient experiences of health states), the authors in this paper argue for a combined approach, reviving a suggestion previously put forward by Lowenstein & Ubel. The authors neatly summarise some of the issues of relying on either decision utility or experienced utility approaches alone and instead argue for better informed decision utility exercises by using deliberative democracy methods where experienced utility in health states are also presented. Unfortunately, there is little detail of how this process might actually work in practice. There are likely to be issues of what patient experiences are presented in such an exercise and how other biases that may influence decision utility responses are controlled for in such an approach. Although I am generally in favour of more deliberative approaches to elicit informed values for resource allocation, I find that this paper makes a convincing case for neither of the utility approaches to valuation, rather than both.

The value of different aspects of person-centred care: a series of discrete choice experiments in people with long-term conditions. BMJ Open [PubMed] Published 26th April 2017

The term “person-centred care” is one which is gaining some prominence in how healthcare is provided. What it means, and how important different aspects of person-centred care are, is explored in this study using discrete choice experiments (DCEs). Through focus groups and drawing from the authors’ own experience in this area, four aspects of person-centred care for self-management of chronic conditions make up the attributes in the DCE across two levels: (i) information (same information for all/personalised information); (ii) situation (little account of current situation/suggestions that fit current situation); (iii) living well (everyone wants the same from life/works with patient for what they want from life); (iv) communication (neutral professional way/friendly professional way). A cost attribute was also attached to the DCE that was given to patient groups with chronic pain and chronic lung disease. The overall findings suggest that person-centred care focused on situation and living well were valued most with personal communication style valued the least. Latent class analysis also suggested that 1 in 5 of those sampled valued personalised information the most. Those with lower earnings were likely to look to reduce the cost attribute the most. The authors conclude that the focus on communication in current clinician training on person-centred care may not be what is of most value to patients. However, I am not entirely convinced by this argument, as it could be that communication was not seen as an issue by the respondents, perhaps somewhat influenced due to the skills clinicians already have obtained in this area. Clearly, these process aspects of care are difficult to develop attributes for in DCEs, and the authors acknowledge that the wording of the “neutral” and “high” levels may have biased responses. I also found that dropping the “negative” third level for each of the attributes unconvincing. It may have proved more difficult to complete than two levels, but it would have shown in much greater depth how much value is attached to the four attributes relative to one another.

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

Is foreign direct investment good for health in low and middle income countries? An instrumental variable approach. Social Science & Medicine [PubMed] Published 28th March 2017

Foreign direct investment (FDI) is considered a key benefit of globalisation in the economic development of countries with developing economies. The effect FDI has on the population health of countries is less well understood. In this paper, the authors draw from a large panel of data, primarily World Bank and UN sources, for 85 low and middle income countries between 1974 and 2012 to assess the relationship between FDI and population health, proxied by life expectancy at birth, as well as child and adult mortality data. They explain clearly the problem of using basic regression analysis in trying to explain this relationship, given the problem of endogeneity between FDI and health outcomes. By introducing two instrumental variables, using grossed fixed capital formation and volatility of exchange rates in FDI origin countries, as well as controlling for GDP per capita, education, quality of institutions and urban population, the study shows that FDI is weakly statistically associated with life expectancy, estimated to amount to 4.15 year increase in life expectancy during the study period. FDI also appears to have an effect on reducing adult mortality, but a negligible effect on child mortality. They also produce some evidence that FDI linked to manufacturing could lead to reductions in life expectancy, although these findings are not as robust as the other findings using instrumental variables, so they recommend this relationship between FDI type and population health to be explored further. The paper also clearly shows the benefit of robust analysis using instrumental variables, as the results without the introduction of these variables to the regression would have led to misleading inferences, where no relationship between life expectancy and FDI would have been found if the analysis did not adjust for the underlying endogeneity bias.

Uncovering waste in US healthcare: evidence from ambulance referral patterns. Journal of Health Economics [PubMed] Published 22nd March 2017

This study looks to unpick some of the reasons behind the estimated waste in US healthcare spending, by focusing on mortality rates across the country following an emergency admission to hospital through ambulances. The authors argue that patients admitted to hospital for emergency care using ambulances act as a good instrument to assess hospital quality given the nature of emergency admissions limiting the selection bias of what type of patients end up in different hospitals. Using linear regressions, the study primarily measures the relationship between patients assigned to certain hospitals and the 90-day spending on these patients compared to mortality. They also consider one-year mortality and the downstream payments post-acute care (excluding pharmaceuticals outside the hospital setting) has on this outcome. Through a lengthy data cleaning process, the study looks at over 1.5 million admissions between 2002-2011, with a high average age of patients of 82 who are predominantly female and white. Approximately $27,500 per patient was spent in the first 90 days post-admission, with inpatient spending accounting for the majority of this amount (≈$16,000). The authors argue initially that the higher 90-day spending in some hospitals only produces modestly lower mortality rates. Spending over 1 year is estimated to cost more than $300,000 per life year, which the authors use to argue that current spending levels do not lead to improved outcomes. But when the authors dig deeper, it seems clear there is an association between hospitals who have higher spending on inpatient care and reduced mortality, approximately 10% lower. This leads to the authors turning their attention to post-acute care as their main target of reducing waste and they find an association between mortality and patients receiving specialised nursing care. However, this target seems somewhat strange to me, as post-acute care is not controlled for in the same way as their initial, insightful approach to randomising based on ambulatory care. I imagine those in such care are likely to be a different mix from those receiving other types of care post 90 days after the initial event. I feel there really is not enough to go on to make recommendations about specialist nursing care being the key waste driver from their analysis as it says nothing, beyond mortality, about the quality of care these elderly patients are receiving in the specialist nurse facilities. After reading this paper, one way I would suggest in reducing inefficiency related to their primary analysis could be to send patients to the most appropriate hospital for what the patient needs in the first place, which seems difficult given the complexity of the private and hospital provided mix of ambulatory care offered in the US currently.

Population health and the economy: mortality and the Great Recession in Europe. Health Economics [PubMed] Published 27th March 2017

Understanding how economic recessions affect population health is of great research interest given the recent global financial crisis that led to the worst downturn in economic performance in the West since the 1930s. This study uses data from 27 European countries between 2004 and 2010 collected by WHO and the World Bank to study the relationship between economic performance and population health by comparing national unemployment and mortality rates before and after 2007. Regression analyses appropriate for time-series data are applied with a number of different specifications applied. The authors find that the more severe the economic downturn, the greater the increase in life expectancy at birth. Additional specific health mortality rates follow a similar trend in their analysis, with largest improvements observed in countries where the severity of the recession was the highest. The only exception the authors note is data on suicide, where they argue the relationship is less clear, but points towards higher rates of suicide with greater unemployment. The message the authors were trying to get across in this study was not very clear throughout most of the paper and some lay readers of the abstract alone could easily be misled in thinking recessions themselves were responsible for better population health. Mortality rates fell across all six years, but at a faster rate in the recession years. Although the results appeared consistent across all models, question marks remain for me in terms of their initial variable selection. Although the discussion mentions evidence that suggests health care may not have a short-term effect on mortality, they did not consider any potential lagged effect record investment in healthcare as a proportion of GDP up until 2007 may have had on the initial recession years. The authors rule out earlier comparisons with countries in the post-Soviet era but do not consider the effect of recent EU accession for many of the countries and more regulated national policies as a consequence. Another issue is the potential of countries’ mortality rates to improve, where countries with existing lower life expectancy have more room for moving in the right direction. However, one interesting discussion point raised by the authors in trying to explain their findings is the potential impact of economic activity on pollution levels and knock-on health impacts from this (and to a lesser extent occupational health levels), that may have some plausibility in better mortality rates linked to physical health during recessions.

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Paul Mitchell’s journal round-up for 2nd January 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.

Age effects in mortality risk valuation. European Journal of Health Economics [PubMed] [RePEcPublished 7th December 2016

Placing values on statistical life years has important public policy implications in measuring who benefits and how much they benefit from interventions. The authors of this study provide what they describe as the most comprehensive evidence to date against a constant value for a statistical life year, an assumption they argue is also applicable when calculating QALYs. Using a Spanish household survey collected over a large sample size (approximately 6,000 individuals), the authors study the relationship between willingness to pay (WTP) and age, by estimating individual WTP for reduction in risk of mortality due to acute myocardial infarction. Three different WTP elicitation procedures were performed. Parametric, semi-nonparametric and non-parametric models using marginal and total approaches were applied to understand the relationship using many alternative methods. Binary variables for income (proxied on a measure of self-perceived social status), education (>lower secondary level) and gender were also included as controls for the models. The results of the linear model show that WTP is lower as age increases. Those with higher income (i.e. social status) and education have higher WTP, while gender is not significant in any model. Sensitivity tests were as hypothesised. The non-parametric model produces similar results to the others, albeit with a higher senior discount. The senior discount is not independent of the income variable. From this, the authors estimate the value of a statistical life year for an 85 year old to be 3.5 times higher than that of a 20 year old. The authors are keen to highlight the strengths of their findings with a large sample size allowing for the robustness of results to be tested across a number of different model types. However, they do flag up the lack of comparability with previous studies that have focused on risk reductions with a lower probability of mortality. The assumption that the authors make that their findings for life years have direct applicability for QALYs is somewhat questionable, particularly for non-acute conditions and QALYs calculated for them. The rationale behind the three types of preference elicitation methods and how/why they were chosen is not apparent in the paper itself. The social status measure they use as a proxy for income is also questionable, and appeared to be applied to maximise sample size. If data for real income was used or imputation of income was included for missing data, it would be interesting to see what impact this may have had on their study findings.

Preferences for public involvement in health service decisions: a comparison between best-worst scaling and trio-wise stated preference elicitation techniques. European Journal of Health Economics [PubMedPublished 10th December 2016

Public involvement in health care is something that has become increasingly recognised as important to do and to be informed by public perspectives when making important decisions for their community. How and where that public involvement should feed into decision making is less well understood. In this study, the authors compare two methods, best worst scaling (BWS) case 2, and a new method the authors call ‘trio-wise’ where the choice task is presented in an equilateral triangle. Using ‘trio-wise’, respondents are able to click in any part of the triangle; this the authors argue gives additional insight on the strength of a respondent’s preferences and also accommodates indifferent preferences. Public preferences are sought using these two methods to understand what aspects of public involvement are most important. Eight general characteristics are included in the exercises. Respondents completed either BWS or the ‘trio-wise’ task (not both) using web based surveys. Approximately 1,700 individuals per arm were sampled. Only three of the eight general characteristics could be completed at any one time due to the trio-wise triangle approach. There was some evidence of position bias for both exercises. The authors say that weak preferences were observed using the trio-wise approach but this could be due to difficulty participants faced in choosing which generic characteristic was more important without further information. Impact and focus of public involvement are found to be the most important characteristics across both BWS and trio-wise. The authors find preference intensity has no bearing on choice probabilities, but this could be an artefact of the weak preferences observed in the sample. Although I can see the appeal of using the trio-wise approach when there are only three characteristics, BWS is advantageous in tasks with more characteristics. Indeed it feels that the findings from this experiment were impeded by the use of the trio-wise approach when much more useful information on guiding future public involvement practice could have been gathered using either BWS or a discrete choice experiment (DCE) across all eight characteristics and the options of public involvement within each characteristic.

How do individuals value health states? A qualitative investigation. Social Science & Medicine [PubMedPublished 22nd November 2016

The valuation tasks of health states used to generate QALYs have been previously found to be complex tasks for members of the general public to complete, who have little experience of such health states. This qualitative study seeks to gain a better understanding as to how the general public complete such tasks. Using a purposive sample, 21 individuals were asked to complete eight DCEs and three TTO tasks, based on the EQ-5D-5L valuation protocol. Participants were asked to complete the valuation tasks using think aloud, followed by semi-structured interviews. Three main themes emerged from the framework analysis undertaken on the interview transcripts. Firstly, individuals had to interpret a health state, using their imagination and experience to help visualise a realistic health state with those problems. Knowledge, understanding of descriptive system, additional information for a health state, re-writing of health states and problems with EQ-5D labels all impacted this process. The second theme was called conversion factors, which the authors took to mean in this context the personal and social factors that affected how participants valued health states. Personal interests, values and circumstances were said to have an effect on the interpretation of a health state. The final theme was based on the consequences of health states, that tended to focus on non-health effects caused by health problems, such as activities, enjoyment, independence, relationships, dignity and avoiding being a burden. The authors subsequently developed a three-stage explanatory account as to how people valued health states based on the interview findings. Although I would have some concerns about the generalisability of these findings to general public valuation studies, given the highly educated sample, it does highlight some issues about what health economists might implicitly think individuals are doing when completing such tasks compared to what they actually are doing. There are clearly problems for individuals completing such hypothetical health states, with the authors suggesting a more reflective and deliberative approach to overcome such problems. The authors also raise an interesting comment as to whether participants actually do weigh the consequences of health states and follow compensatory decision-making or instead are using simplifying heuristics based on one attribute, which I agree is an area that requires further investigation.

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