from The Academic Health Economists’ Blo… at http://bit.ly/2ZLWrRY on April 29, 2019 at 12:24PM
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.
Here comes the SUN: self‐assessed unmet need, worsening health outcomes, and health care inequity. Health Economics [PubMed] Published 24th April 2019
How should we measure inequity in health care? Often, it is measured on the basis of health care use, and the extent to which people with different socioeconomic circumstances – conditional on their level of need – access services. One problem with this approach is that differences might not only reflect barriers to access but also heterogeneity in preferences. If people of lower socioeconomic status prefer to access services less (conditional on need), then this is arguably an artificial signal of inequities in the system. Instead, we could just ask people. But can self-assessed unmet need provide a valid and meaningful measure of inequity?
In this study, the researchers looked at whether self-reported unmet need can predict deterioration in health. The idea here is that we would expect there to be negative health consequences if people genuinely need health care but cannot access it. The Canadian National Population Health Survey asks whether, during the preceding 12 months, the individual needed health care but did not receive it, with around 10% reporting unmet need. General health outcomes are captured by self-assessed health and by the HUI3, and there are also variables for specific chronic conditions. A few model specifications, controlling for a variety of health-related and demographic variables, are implemented. For the continuous variables, the authors use a fixed effects model with lagged health, and for the categorical outcomes they used a random effects probit.
The findings are consistent across models and outcomes. People who report self-assessed unmet need are more likely to have poorer health outcomes in subsequent periods, in terms of both general health and the number of self-reported chronic conditions. This suggests that self-assessed unmet need is probably a meaningful indicator of barriers to access in health care. I’m not aware of any UK-based surveys that include self-assessed unmet need, but this study provides some reason to think that they should.
Cost effectiveness of treatments for diabetic retinopathy: a systematic literature review. PharmacoEconomics [PubMed] Published 22nd April 2019
I’ve spent a good chunk of the last 8 years doing research in the context of diabetic eye disease. Over that time, treatment has changed, and there have been some interesting controversies relating to the costs of new treatments. So this review is timely.
There are four groups of treatments that the authors consider – laser, anti-VEGF eye injections, corticosteroids, and surgery. The usual databases were searched, turning up 1915 abstracts, and 17 articles were included in the review. That’s not a lot of studies, which is why I’d like to call the authors out for excluding one HTA report, which I assume was Royle et al 2015 and which probably should have been included. The results are summarised according to whether the evaluations were of treatments for diabetic macular oedema (DMO) or proliferative diabetic retinopathy (PDR), which are the two main forms of sight-threatening diabetic eye disease. The majority of studies focussed on DMO. As ever, in reviews of this sort, the studies and their findings are difficult to compare. Different methods were employed, for different purposes. The reason that there are so few economic evaluations in the context of PDR is probably that treatments have been so decisively shown to be effective. Yet there is evidence to suggest that, for PDR, the additional benefits of injections do not justify the much higher cost compared with laser. However, this depends on the choice of drug that is being injected, because prices vary dramaticly. For DMO, injections are cost-effective whether combined with laser or not. The evidence on corticosteroids is mixed and limited, but there is promise in recently-developed fluocinolone implants.
Laser might still be king in PDR, and early surgical intervention is also still cost-effective where indicated. For DMO, the strongest evidence is in favour of using an injection (bevacizumab) that can only be used off-label. You can blame Novartis for that, or you can blame UK regulators. Either way, there’s good reason to be angry about it. The authors of this paper clearly have a good understanding of the available treatments, which is not always the case for reviews of economic evaluations. The main value of this study is as a reference point for people developing research in this area, to identify the remaining gaps in the evidence and appropriately align (or not) with prevailing methods.
Exploring the impacts of the 2012 Health and Social Care Act reforms to commissioning on clinical activity in the English NHS: a mixed methods study of cervical screening. BMJ Open [PubMed] Published 14th April 2019
Not everybody loves the Health and Social Care Act of 2012. But both praise and criticism of far-reaching policies like this are usually confined to political arguments. It’s nice to see – and not too long after the fact – some evidence of its impact. In this paper, we learn about the impact of the Act on cervical screening activity.
The researchers used both qualitative and quantitative methods in their study in an attempt to identify whether the introduction of the Act influenced rates of screening coverage. With the arrival of the Act, responsibility for commissioning screening services shifted from primary care trusts to regional NHS England teams, while sexual health services were picked up by local authorities. The researchers conducted 143 (!) interviews with commissioners, clinicians, managers, and administrators from various organisations. Of these, 93 related to the commissioning of sexual health services, with questions regarding the commissioning system before and after the introduction of the Act. How did participants characterise the impact of the Act? Confusion, complexity, variability, uncertainty, and the idea that these characteristics could result in a drop in screening rates.
The quantitative research plan, and in particular the focus on cervical screening, arose from the qualitative findings. The quantitative analysis sought to validate the qualitative findings. But everyone had the Act dropped on them at the same time (those wily politicians know how to evade blame), so the challenge for the researchers was to identify some source of variation that could represent exposure to the effects of the Act. Informed by the interviewees, the authors differentiated between areas based on the number of local authorities that the clinical commissioning group (CCG) had to work with. Boundaries don’t align, so while some CCGs only have to engage with one local authority, some have to do so with as many as three, increasing the complexity created by the Act. As a kind of control, the researchers looked at the rate of unassisted births, which we wouldn’t expect to have been affected by the introduction of the Act. From this, they estimated the triple difference in cervical screening rates before and after the introduction of the Act, between CCGs with one or more than one local authority, minus the difference in the unassisted birth rate. Screening rates (and unassisted delivery rates) were both declining before the introduction of the Act. Without any adjustment, screening rates before and after the introduction of the act decreased by 0.39% more for GP practices in those CCGs that had to work with multiple local authorities. Conversely, unassisted delivery rates actually increased by a similar amount. The adjusted impact of the Act on screening rates was a drop of around 0.62%.
Clearly, there are big disclaimers attached to findings from a study of this sort, though the main finding seems to be robust to a variety of specifications. Any number of other things could explain the change in screening rates over the period, which the researchers couldn’t capture. But the quantitative findings are backed-up by the qualitative reports, making this a far more convincing piece of work. There’s little doubt that NHS redisorganisations of this kind create challenges in the short term, and we can now see the impact that this has on the provision of care.
Public involvement in health outcomes research: lessons learnt from the development of the recovering quality of life (ReQoL) measures. Health and Quality of Life Outcomes [PubMed] Published 11th April 2019
We’ve featured a few papers from the ReQoL project on this blog. The researchers developed several outcome measures to be used in the context of mental health. A couple of weeks ago, we also featured a paper turning a sceptical eye to the idea of co-production, whereby service users or members of the public are not simply research participants but research partners. This paper describes the experience of coproduction in the context of the ReQoL study. The authors are decidedly positive about co-production.
The logic behind the involvement of service users in the development of patient-reported outcome measures is obvious; measures need to be meaningful and understandable to patients, and enabling service users to inform research decisions could facilitate that. But there is little guidance on co-production in the context of developing patient-reported outcomes. Key decisions in the development of ReQoL were made by a ‘scientific group’, which included academics, clinicians, and seven expert service users. An overlapping ‘expert service user group’ also supported the study. In these roles, service users contributed to all stages of the research, confirming themes and items, supporting recruitment, collecting and analysing data, agreeing the final items for the measures, and engaging in dissemination activities. It seems that the involvement was in large part attendance at meetings, discussing data and findings to achieve an interpretation that includes the perspectives of services users. This resulted in decisions – about which items to take forward – that probably would not have been made if the academics and clinicians were left to their own devices. Service users were also involved in the development of research materials, such as the interview topic guide. In some examples, however, it seems like the line between research partner and research participant was blurred. If an expert service user group is voting on candidate items and editing them according to their experience, this is surely a data collection process and the services users become research subjects.
The authors describe the benefits as they saw them, in terms of the expert service users’ positive influence on the research. The costs and challenges are also outlined, including the need to manage disagreements and make additional preparations for meetings. We’re even provided with the resource implications in terms of the additional days of work. The comprehensive description of the researchers’ experiences in this context and the recommendations that they provide make this paper an important companion for anybody designing a research study to develop a new patient-reported outcome measure.