Chris Sampson’s journal round-up for 4th February 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.

Patient choice and provider competition – quality enhancing drivers in primary care? Social Science & Medicine Published 29th January 2019

There’s no shortage of studies in economics claiming to identify the impact (or lack of impact) of competition in the market for health care. The evidence has brought us close to a consensus that greater competition might improve quality, so long as providers don’t compete on price. However, many of these studies aren’t able to demonstrate the mechanism through which competition might improve quality, and the causality is therefore speculative. The research reported in this article was an attempt to see whether the supposed mechanisms for quality improvement actually exist. The authors distinguish between the demand-side mechanisms of competition-increasing quality-improving reforms (i.e. changes in patient behaviour) and the supply-side mechanisms (i.e. changes in provider behaviour), asserting that the supply-side has been neglected in the research.

The study is based on primary care in Sweden’s two largest cities, where patients can choose their primary care practice, which could be a private provider. Key is the fact that patients can switch between providers as often as they like, and with fewer barriers to doing so than in the UK. Prospective patients have access to some published quality indicators. With the goal of maximum variation, the researchers recruited 13 primary health care providers for semi-structured interviews with the practice manager and (in most cases) one or more of the practice GPs. The interview protocol included questions about the organisation of patient visits, information received about patients’ choices, market situation, reimbursement, and working conditions. Interview transcripts were coded and a framework established. Two overarching themes were ‘local market conditions’ and ‘feedback from patient choice’.

Most interviewees did not see competitors in the local market as a threat – conversely, providers are encouraged to cooperate on matters such as public health. Where providers did talk about competing, it was in terms of (speed of) access for patients, or in competition to recruit and keep staff. None of the interviewees were automatically informed of patients being removed from their list, and some managers reported difficulties in actually knowing which patients on their list were still genuinely on it. Even where these data were more readily available, nobody had access to information on reasons for patients leaving. Managers saw greater availability of this information as useful for quality improvement, while GPs tended to think it could be useful in ensuring continuity of care. Still, most expressed no desire to expand their market share. Managers reported using marketing efforts in response to greater competition generally, rather than as a response to observed changes within their practice. But most relied on reputation. Some reported becoming more service-minded as a result of choice reforms.

It seems that practices need more information to be able to act on competitive pressures. But, most practices don’t care about it because they don’t want to expand and they face no risk of there being a shortage of patients (in cities, at least). And, even if they did want to act on the information, chances are it would just create an opportunity for them to improve access as a way of cherry-picking younger and healthier people who demand convenience. Primary care providers (in this study, at least) are not income maximisers, but satisficers (they want to break-even), so there isn’t much scope for reforms to encourage providers to compete for new patients. Patient choice reforms may improve quality, but it isn’t clear that this has anything to do with competitive pressure.

Maximising the impact of patient reported outcome assessment for patients and society. BMJ [PubMed] Published 24th January 2019

Patient-reported outcome measures (PROMs) have been touted as a way of improving patient care. Yet, their use around the world is fragmented. In this paper, the authors make some recommendations about how we might use PROMs to improve patient care. The authors summarise some of the benefits of using PROMs and discuss some of the ways that they’ve been used in the UK.

Five key challenges in the use of PROMs are specified: i) appropriate and consistent selection of the best measures; ii) ethical collection and reporting of PROM data; iii) data collection, analysis, reporting, and interpretation; iv) data logistics; and v) a lack of coordination and efficiency. To address these challenges, the authors recommend an ‘integrated’ approach. To achieve this, stakeholder engagement is important and a governance framework needs to be developed. A handy table of current uses is provided.

I can’t argue with what the paper proposes, but it outlines an idealised scenario rather than any firm and actionable recommendations. What the authors don’t discuss is the fact that the use of PROMs in the UK is flailing. The NHS PROMs programme has been scaled back, measures have been dropped from the QOF, the EQ-5D has been dropped from the GP Patient Survey. Perhaps we need bolder recommendations and new ideas to turn the tide.

Check your checklist: the danger of over- and underestimating the quality of economic evaluations. PharmacoEconomics – Open [PubMed] Published 24th January 2019

This paper outlines the problems associated with misusing methodological and reporting checklists. The author argues that the current number of checklists available in the context of economic evaluation and HTA (13, apparently) is ‘overwhelming’. Three key issues are discussed. First, researchers choose the wrong checklist. A previous review found that the Drummond, CHEC, and Philips checklists were regularly used in the wrong context. Second, checklists can be overinterpreted, resulting in incorrect conclusions. A complete checklist does not mean that a study is perfect, and different features are of varying importance in different studies. Third, checklists are misused, with researchers deciding which items are or aren’t relevant to their study, without guidance.

The author suggests that more guidance is needed and that a checklist for selecting the correct checklist could be the way to go. The issue of updating checklists over time – and who ought to be responsible for this – is also raised.

In general, the tendency seems to be to broaden the scope of general checklists and to develop new checklists for specific methodologies, requiring the application of multiple checklists. As methods develop, they become increasingly specialised and heterogeneous. I think there’s little hope for checklists in this context unless they’re pared down and used as a reminder of the more complex guidance that’s needed to specify suitable methods and achieve adequate reporting. ‘Check your checklist’ is a useful refrain, though I reckon ‘chuck your checklist’ can sometimes be a better strategy.

A systematic review of dimensions evaluating patient experience in chronic illness. Health and Quality of Life Outcomes [PubMed] Published 21st January 2019

Back to PROMs and PRE(xperience)Ms. This study sets out to understand what it is that patient-reported measures are being used to capture in the context of chronic illness. The authors conducted a systematic review, screening 2,375 articles and ultimately including 107 articles that investigated the measurement properties of chronic (physical) illness PROMs and PREMs.

29 questionnaires were about (health-related) quality of life, 19 about functional status or symptoms, 20 on feelings and attitudes about illness, 19 assessing attitudes towards health care, and 20 on patient experience. The authors provide some nice radar charts showing the percentage of questionnaires that included each of 12 dimensions: i) physical, ii) functional, iii) social, iv) psychological, v) illness perceptions, vi) behaviours and coping, vii) effects of treatment, viii) expectations and satisfaction, ix) experience of health care, x) beliefs and adherence to treatment, xi) involvement in health care, and xii) patient’s knowledge.

The study supports the idea that a patient’s lived experience of illness and treatment, and adaptation to that, has been judged to be important in addition to quality of life indicators. The authors recommend that no measure should try to capture everything because there are simply too many concepts that could be included. Rather, researchers should specify the domains of interest and clearly define them for instrument development.

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Simon McNamara’s journal round-up for 21st January 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.

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.

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Thesis Thursday: Firdaus Hafidz

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.

Title
Assessing the efficiency of health facilities in Indonesia
Supervisors
Tim Ensor, Sand Tubeuf
Repository link
http://etheses.whiterose.ac.uk/id/eprint/21575

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.