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.
Medical Decision Making
Volume 40, Issue 4
The latest issue of MDM includes a dozen articles on topics as diverse as preference elicitation, cost-effectiveness modelling, and clinical decision-making tools. I’ll just highlight a handful.
There’s an article from members of the team who came up with the infamous £12,936 per QALY cost-effectiveness threshold for the English NHS. In this new study, the researchers conducted an expert elicitation exercise. They wanted to test the validity of some of the assumptions used in the original threshold estimation study, particularly in relation to the estimation of benefits in terms of QALYs. The results imply that the original assumptions are conservative, in that the parameters elicited from the experts would imply greater benefits per pound of expenditure and therefore a threshold even lower than their original estimate. But there are lots of problems with this conclusion… expect to read more on this paper from me in the near future.
Another study that will be of interest to cost-effectiveness modellers explores different approaches to measuring uncertainty when extrapolating trial results. The researchers conducted a simulation study and found that allowing for sampling uncertainty as well as parameter uncertainty expanded confidence intervals 6-fold. Several methods are tested and the authors provide Stata code so you can go and do it yourself.
This issue includes three articles on the valuation of health outcomes. One study reports on a valuation of the ICECAP-A and ICECAP-O capability measures using experienced utility. Despite that arguably being a contradiction in terms (Sen may not approve), the study reveals some useful tendencies. Elicited values for the ICECAP-O (for older people) were more similar to values based on decision utility than were values for the ICECAP-A (for adults). For the ICECAP-A, experienced utility gave more weight to stability and enjoyment while giving less weight to attachment and autonomy, relative to decision utility.
Continuing the theme of health state valuation, but of the EQ-5D, a simulation study looks at the impact of model specification when combining time trade-off and discrete choice experiment data. Data were simulated that included nonlinear relationships, heteroscedastic errors, and correlated responses, and value sets were estimated using various hybrid models. Inevitably, the study shows that it’s best not to ignore the characteristics of the data. Using a misspecified hybrid model is likely to give poorer predictions than a model that uses TTO data alone.
With the EQ-5D continuing to be used in every imaginable context and for every imaginable purpose, a valuable study in this issue looks at whether its use to measure hospital performance might misrepresent patients’ preferences. If reported outcomes for hospitals are based on societal values for EQ-5D health states, and these differ from patients’ values, we might have a problem. The authors estimated hospitals’ rankings when alternative valuation methods were used and found that the rankings can change. However, by looking at visual analogue scale data, the authors assert that the source of values (i.e. patient or public) does not seem to drive the differences. These findings imply that any concern should be of a technical nature rather than a normative one.
International Journal of Health Economics and Management
Volume 20, Issue 2
Thanks to the coronavirus pandemic, many people are thinking hard about the relationship between health, health care, and the economy. The latest issue of IJHEM includes new research on this topic, focussing on the role of human capital in mediating the relationship between health expenditure and economic growth. The study uses a panel threshold model for 21 developing countries from 2000 to 2016. Human capital is measured by tertiary education enrollment rates. In countries with a low level of human capital, health expenditures are negatively correlated with economic growth. In countries with high human capital, the reverse is true.
This issue also includes a couple of papers on market structure in the dental industry in the US. One study uses annual survey data for 1983 to 2012 to explore pricing behaviour and the demand for services. The researchers find that hygienist services tend to be priced very close to marginal cost, while dental services are priced higher and have a lower price elasticity of demand. The authors speculate that hygienist services may be used as loss leaders. The other study looks at consolidation in dental insurance, finding that greater concentration in dental insurers is associated with larger dental practices. These findings may help to explain recent trends.
The other two studies in the issue relate to the health insurance market in the US. One study shows that the demand for insurance increased following the introduction of quality reporting for Veterans Affairs (VA) hospitals. Another study takes on the hard task of trying to estimate the overall welfare effects of the Affordable Care Act, finding it to be very beneficial to people on low incomes and the chronically ill, while most people experience losses.
Credits
I didn’t realise that there are some countries where health-care spending can damage economic growth. I can’t see the full article. In a nutshell, what is the reason for that? I would hazard a guess that it crowds out other spending in the economy and, with lower human-capital levels, there are fewer productivity gains from the improved health.
Yeah, it seems pretty sketchy. The theory is that more welfare expenditure makes people less likely to save and to invest in the stuff that is ‘good for the economy’. I find it hard to believe that’s true but, even if it is, I find it hard to care about GDP.