Every Monday our authors provide a round-up of the latest peer-reviewed journal publications. We cover all issues of major health economics journals as well as some other notable releases. 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.
Volume 21, Issue 5
Most journals are publishing articles relevant to the COVID pandemic, and this issue of EJHE is no exception. There’s an editorial on modelling and uncertainty in the context of COVID. The authors outline the basics of disease modelling for COVID-19 and highlight best practices for a system dynamics model. The issue also includes a willingness to pay study, which I discussed in an earlier blog post, looking at support for an early warning system for infectious diseases in Europe.
Most of the other articles that caught my eye were on the topic of mental health.
An econometric analysis investigates the impact of waiting time targets for early intervention for psychosis in the UK. A two-week target was introduced in the NHS in 2015. The authors matched people using these services to people accessing other community services and identified the difference-in-difference after the introduction of the policy. Targets increased the likelihood that people waited less than two weeks. However, the authors also analysed waiting times at the provider level and found no overall improvement across the distribution, compared with the control group.
Another evaluative study is concerned with the delivery of mental health services in Germany. The authors explored the impact on costs of two programmes, one based on a GP gatekeeper model and another based on building collaborative care into a GP programme. Analysing claims data, the researchers found that the collaborative care model was associated with people having fewer sick days, compared with the GP model and with usual care. Only small differences were found for outpatient costs. The main challenge for me with this study is in understanding the interventions. I’m not sure that the findings have any relevance outside of Germany.
There’s a study of EQ-5D valuation methods that I’ve seen discussed at a couple of conferences in recent years. The researchers present a new solution to the problem of anchoring discrete choice experiment data to a 0-1 scale. It’s a simple solution (unlike many others), based on asking people to value health states – along with the ‘dead’ state – using a visual analogue scale. In my view, the main problem with the method is that values are not estimated in relation to time. Yet, time is the thing to which health states need to be anchored, because QALYs depend on it.
Keeping with the quality of life theme, I was also drawn to a study of the impact of complications and comorbidities for people with type 2 diabetes. Using an observational study with 938 people in Greece, the authors identify that stroke had the biggest negative impact on health-related quality of life, followed by retinopathy and neuropathy. But, as studies of this nature so often find, individuals’ characteristics such as age and gender were far more important predictors.
Volume 18, Issue 4
There are a couple of articles on COVID in the latest AHEHP. A commentary piece discusses the lessons for the Italian health service. There’s also a research article assessing the effectiveness of lockdown measures. The authors established a panel of country-level observations for the number of new cases and analysed the impact of lockdown measures using a generalised estimating equation model. Overall, lockdown is shown to be effective, with the benefit persisting to 20 days beyond the introduction of measures. For me, the study starts to unravel in observing that lockdown acted to increase the number of cases in countries in Europe. There is no identification of causality here. The authors’ claim to have ‘proven’ the effectiveness of lockdown is not justified.
A couple of model-based economic evaluations caught my eye. One is an evaluation of internet-based cognitive behavioural therapy for depression, finding it to be more effective and less costly than face-to-face therapy. The main reason for this is that the authors tried to take into account the fact that people have to wait longer for face-to-face therapy: 20 weeks compared with 3 weeks for internet-based therapy. Thus, even if face-to-face therapy is more effective when accessed, the amount of time spent in a depressed state can be lower for internet-based therapy.
There is also an evaluation of electrocardiogram (ECG) screening strategies for atrial fibrillation. The analysis is based on a previously developed model that simulates the probability of various events. The authors compared no screening with the use of either a 12-lead ECG for one-time screening or a hand-held ECG used intermittently over a 14-day period. Both screening scenarios were more cost-effective than no screening, with the hand-held extended screening programme coming out on top thanks to it being 4.8 times more likely to detect non-valvular atrial fibrillation. But, as with all evaluations of screening programmes, the challenge is to understand the long-term impact of the different outcomes, especially false positives. More evidence would be needed before screening could be widely adopted.
This issue also includes several articles that I’ve discussed on the blog before. One is a study comparing decisions by the Institute for Clinical and Economic Review with other published research. I have a few reservations about that study. Another is a ‘practical application’ article on government spending multiplier effects, which I discussed in an earlier blog post, and which has arguably become more pertinent thanks to COVID. Finally, there is a study of the British Sign Language version of the EQ-5D-5L, which I discussed in January.