The fifth IRDES Workshop on Applied Health Economics and Policy Evaluation, will take place in Paris, France, on June 20th-21st 2019. The workshop is organized by IRDES, Institute for Research and Information in Health Economics, and the Chaire Santé Dauphine.
Submission and selection of papers. You are invited to submit a full paper before January 14th 2019. Papers will be selected by the scientific committee on the basis of a full or advanced draft papers, written in English. Papers should include empirical material, and only unpublished papers at the time of the submission will be accepted. The submission should contain author’s name(s) and affiliation(s), a structured abstract and keywords (up to five).
Registration and fees. Registration fees are 200 euros. Only authors or coauthors can apply for registration. PhD students or early career researchers may benefit from free registration upon request.
Program. The workshop will cover the following topics, with an emphasis on Public Policies analysis and evaluation: Social Health Inequalities, Health Services Utilization, Insurance, Health Services Delivery and Organization, Specific Populations: The Elderly, Migrants, High Needs-High Costs Patients, Low Income Households…. About 16 papers will be selected. Each paper will be allocated 20 minutes for presentation and 20 minutes for discussion (introduced by a participant or a member of the scientific committee).
Scientific committee. Damien Bricard (IRDES), Andrew Clark (Paris School of Economics), Brigitte Dormont (Paris Dauphine University and Chaire santé Dauphine), Paul Dourgnon (IRDES), Agnès Gramain (Université Lorraine), Julien Mousquès (IRDES), Aurélie Pierre (IRDES), Erin Strumpf (McGill University, Montreal), Matt Sutton (University of Manchester)
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.
Assessing capability in economic evaluation: a life course approach? The European Journal of Health Economics [PubMed] Published 8th January 2019
If you have spent any time on social media in the last week there is a good chance that you will have seen the hashtag #10yearchallenge. This hashtag is typically accompanied by two photos of the poster; one recent, and one from 10 years ago. Whilst the minority of these posts suggest that the elixir of permanent youth has been discovered and is being hidden away by a select group of people, the majority show clear signs of ageing. As time passes, we change. Our skin becomes wrinkled, our hair may become grey, and we may become heavier. What these pictures don’t show, is how we change internally – and I don’t mean biologically. As we become older, and we experience life, so the things we think are important change. Our souls become wrinkled, and our minds become heavier.
The first paper in this week’s round-up is founded on this premise, albeit grounded in the measurement of capability well-being across the life course, rather than a hashtag. The capabilities approach is grounded in the normative judgement that the desirability of policy outcomes should be evaluated by what Sen called the ‘capabilities’ they provide – “the functionings, or the capabilities to function” they give people, where functionings for a person are defined as “the various things that he or she manages to do or be in leading a good life” (Sen, 1993). The author (Joanna Coast) appeals to her, and others’, work on the family of ICECAP measures (capability measures), in order to argue that the capabilities we value changes across the stage of life we are experiencing. For example, she notes that the development work for the ICECAP-A (adults) resulted in the choice of an ‘achievement’ attribute in that instrument, whilst for ICECAP-O (older people) an alternative ‘role’ attribute was used – with the achievement attribute primarily linked to having the ability to make progress in life, and the role attribute linked to having the ability to do things that make you feel valued. Similarly, she notes that the attributes that emerged from development work on the ICECAP-SCM (supportive care – a term for the end of life) are different to those from ICECAP-A (adults), with dignity coming to the forefront as a valued attribute towards the end of life. The author then goes on to suggest that it would be normatively desirable to capture how the capabilities we value changes over the life-course, suggests this could be done with a range of different measures, and highlights a number of problems associated with this (e.g. when does a life-stage start and finish?).
You should read this paper. It is only four pages long and definitely worth your time. If you have spent enough time on social media to know what the #10yearchallenge is, then you definitely have time to read it. I think this is a really interesting topic and a great paper. It has certainly got me thinking more about capabilities, and I will be keeping an eye out for future papers on this in future.
Future directions in valuing benefits for estimating QALYs: is time up for the EQ-5D? Value in Health Published 17th January 2019
If EQ-5D were a person, I think I would be giving it a good hug right now. Every time my turn to write this round-up comes up there seems to be a new article criticising it, pointing out potential flaws in the way it has been valued, or proposing a new alternative. If it could speak, I imagine it would tell us it is doing its best – perhaps with a small tear in its eye. It has done what it can to evolve, it has tried to change, but as we approach its 30th birthday, and exciting new instruments are under development, the authors of the second paper in this week’s round-up question – “Is time up for the EQ-5D?”
If you are interested in the valuation of outcomes, you should probably read this paper. It is a really neat summary of recent developments in the assessment and valuation of the benefits of healthcare, and gives a good indication of where the field may be headed. Before jumping into reading the paper, it is worth dwelling on its title. Note that the authors have used the term “valuing benefits for estimating QALYs” and not “valuing health states for estimating QALYs”. This is telling, and reflects the growing interest in measuring, and valuing, the benefits of healthcare based upon a broader conception of well-being, rather than simply health as represented by the EQ-5D. It is this issue that rests at the heart of the paper, and is probably the biggest threat to the long-term domination of EQ-5D. If it wasn’t designed to capture the things we are now interested in, then why not modify it further, or go back to the drawing board and start again?
I am not going to attempt to cover all the points made in the paper, as I can’t do it justice in this blog; but in summary, the authors review a number of ways this could be done, outline recent developments in the way the subsequent instrument could be valued, and detail the potential advantages, disadvantages, and challenges of moving to a new instrument. Ultimately, the authors conclude that the future of the valuation of outcomes – be that with EQ-5D or something else, depends upon a number of judgements, including whether non-health factors are considered to be relevant when valuing the benefits of healthcare. If they are then EQ-5D isn’t fit for purpose, and we need a new instrument. Whilst the paper doesn’t provide a definitive answer to the question “Is Time Up for the EQ-5D?”, the fact that NICE, the EuroQol group, two of the authors of this paper, and a whole host of others, are currently collaborating on a new measure, which captures both health and non-health outcomes, indicates that EQ-5D may well be nearing the end of its dominance. I look forward to seeing how this work progresses over the next few years.
The association between economic uncertainty and suicide in the short-run. Social Science and Medicine [PubMed] [RePEc] Published 24th November 2018
As I write this, the United Kingdom is 10 weeks away from the date we are due to leave the European Union, and we are still uncertain about how, and potentially even whether, we will finally leave. The uncertainty created by Brexit covers both economic and social spheres, and impacts many of those in the United Kingdom, and many beyond who have ties to us. I am afraid the next paper isn’t a cheery one, but given this situation, it is a timely one.
In the final paper in this round-up, the authors explore the link between economic uncertainty and short-term suicide rates. This is done by linking the UK EPU index of economic uncertainty – an index generated based upon the articles published in 650 UK newspapers – to the daily suicide rates in England and Wales between 2001 and 2015. The authors find evidence of an increase in suicide rates on the days on which the EPU index was higher, and also of a lagged effect on the day after a spike in the index. Over the course of a year, this effect means a one standard deviation increase in the EPU is expected to lead to 11 additional deaths in that year. In comparison to the number of deaths per year from cardiovascular disease, and cancer, this effect is relatively modest, but is nevertheless concerning given the nature of the way in which these people are dying.
I am not going to pretend I enjoyed reading this paper. Technically it is good, and it is an interesting paper, but the topic was just a bit too dark and too relevant to our current situation. Whilst reading I couldn’t help but wonder whether I am going to be reading a similar paper linking Brexit uncertainty to suicide at some point in the future. Fingers crossed this isn’t the case.
On the third Thursday of every month, we speak to a recent graduate about their thesis and their studies. This month’s guest is Dr Firdaus Hafidz who has a PhD from the University of Leeds. If you would like to suggest a candidate for an upcoming Thesis Thursday, get in touch.
What are some of the key features of health and health care in Indonesia?
Indonesia is a diverse country, with more than 17 thousand islands and 500 districts. Thus, there is a wide discrepancy of health outcomes across Indonesia, which also reflects the country’s double burden of both communicable and emerging non-communicable diseases. Communicable diseases such as tuberculosis, diarrhoea and lower respiratory tract infections remain as significant issues in Indonesia, especially in remote areas. At the same time, non-communicable diseases are becoming a major public health problem, especially in urban areas.
Total healthcare expenditure per capita grew rapidly, but in certain outcomes, such as maternal mortality rate, Indonesia performs less well than other low- and middle-income countries. Health facilities represent the largest share of healthcare expenditures, but utilisation is still considered low in both hospitals and primary healthcare facilities. Given the scarcity of public healthcare resources, out-of-pocket expenditure remains considerably higher than the global average.
To reduce financial barriers, the Government of Indonesia introduced health insurance in 1968. Between 2011 and 2014, there were three major insurance schemes: 1) Jamkesmas – poor scheme; 2) Jamsostek – formal sector workers scheme; and 3) Askes – civil servant scheme. In 2014, the three schemes were combined into a single-entity National Health Insurance scheme.
What methods can be used to measure the efficiency of health care in low and middle-income countries?
We reviewed measurements of efficiency in empirical analyses conducted in low- and middle-income countries. Methods, including techniques, variables, and efficiency indicators were summarised. There was no consensus on the most appropriate technique to measure efficiency, though most existing studies have relied on ratio analysis and data envelopment analysis because it is simple, easy to compute, low-cost and can be performed on small samples. The physical inputs included the type of capital (e.g. the number of beds and size of health facilities) and the type of labour (e.g. the number of medical and non-medical staff). Most of the published literature used health services as outputs (e.g. the number of outpatient visits, admission and inpatient days). However, because of poor data availability, fewer studies used case-mix and quality indicators to adjust outputs. So most of the studies in the literature review assumed that there was no difference in the severity and effectiveness of healthcare services. Despite the complexity of the techniques, researchers are responsible to provide interpretable results to the policymakers to guide their decisions for a better health policy on efficiency. Adopting appropriate methods that have been used globally would be beneficial to benchmark empirical studies.
Were you able to identify important sources of inefficiency in Indonesia?
We used several measurement techniques including frontier analysis and ratio analysis. We explored contextual variables to assess factors determining efficiency. The range of potential models produced help policymakers in the decision-making process according to their priority and allow some control over the contextual variables. The results revealed that the efficiency of primary care facilities can be explained by population health insurance coverage, especially through the insurance scheme for the poor. Geographical factors, such as the main islands (Java or Bali), better access to health facility, and location in an urban area also have a strong impact on efficiency. At the hospitals, the results highlighted higher efficiency levels in larger hospitals; they were more likely to present in deprived areas with low levels of education; and they were located on Java or Bali. Greater health insurance coverage also had a positive and significant influence on efficiency.
How could policymakers improve the efficiency of health care in Indonesia or other similar settings?
I think there are several ideas. First, we need to have a careful tariff adjustment as we found an association between low unit costs and high efficiency scores. Case base group tariffs need to account for efficiency scores to prevent unnecessary incentives for the providers, exacerbating inefficiency in the health system.
Secondly, we need flexibility in employment contracts, particularly for the less productive civil servant worker so the less productive worker could be reallocated. We also need a better remuneration policy to attract skilled labour and improve health facilities efficiency.
From the demand side, reducing physical barriers by improving infrastructure could increase efficiency in the rural health care facilities through higher utilisation of care. Facilities with very low utilisation rates still incur a fixed cost and thus create inefficiency. Through the same argument we also need to reduce financial barriers using incentives programmes and health insurance, thus patients who are economically disadvantaged can access healthcare services.
How would you like to see other researchers build on your work?
Data quality is crucial in secondary data analysis research, and it was quite a challenge in an Indonesian setting. Meticulous data management is needed to mitigate data errors such as inconsistency, outliers and missing values.
As this study used a 2011 cross-sectional dataset, replicating this study using a more recent and even longitudinal data would highlight changes in efficiency due to policy changes or interventions. Particularly interesting is the effect of the 2014 implementation of Indonesian national health insurance.
My study has some limitations and thus warrants further investigation. The stochastic frontier analysis failed to identify any inefficiency at hospitals when outpatient visits were included. The statistical errors of the frontier function cannot be distinguished from the inefficiency effect of the model. It might be related to the volume and heterogeneity of outpatient services which swamps the total volume of services and masks any inefficiency.