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.
Ethical hurdles in the prioritization of oncology care. Applied Health Economics and Health Policy [PubMed] Published 21st October 2016
Recently between health economists, there has been significant scrutiny and disquiet directed towards the Cancer Drugs Fund with Professor Karl Claxton describing it as “an appalling, unfair use of NHS resources”. With the latest reorganization of the Cancer Drugs Fund in mind, this article examining the ethical issues surrounding prioritisation of cancer care was of particular interest. As all health economists will tell you, there is an opportunity cost with any allocation of scarce resources. Likewise, with prioritisation of specific disease groups, there may be equity issues with specific patients’ lives essentially being valued more greatly than those suffering other conditions. This article conducts a systematic review of the oncology literature to examine the ethical issues surrounding inequity in healthcare. The review found that public and political attention often focuses on ‘availability’ of pharmacological treatment in addition to factors that lead to good outcomes. The public and political focus on availability can have perverse consequences as highlighted by the Cancer Drugs Fund: resources are diverted towards availability and away from other more cost-effective areas, and in turn this may have had a detrimental effect on care for non-cancer patients. Additionally, by approving high cost, less cost-effective agents, strain will be placed upon health budgets and causing problems for existing cost-effectiveness thresholds. If prioritisation for cancer drugs is to be pursued then the authors suggest that the question of how to fund new therapies equitably will need to be addressed. Although the above issues will not be new to most, the paper is still worth reading as it: i) gives an overview of the different prioritisation frameworks used across Europe, ii) provides several suggestions for how, if prioritization is to be pursued, it can be done in a fairer manner rather than simply overriding typical HTA decision processes, iii) considers the potential legal consequences of prioritisation and iv) the impact of prioritisation on the sustainability of healthcare funding.
Doctor-patient differences in risk and time preferences: a field experiment. Journal of Health Economics Published 19th October 2016
The patient-doctor agency interaction, and associated issues due to asymmetrical information is something that was discussed often during my health economics MSc, but rarely during my day to day work. Despite being very familiar with supplier induced demand, differences in risk and time preferences in the patient-doctor dyad wasn’t something I’d considered in recent times. Upon reading, immediately, it is clear that if risk and time preferences do differ, then what is seen as the optimal treatment for the patient may be very different to that of the doctor. This may lead to poorer adherence to treatments and worse outcomes. This paper sought to investigate whether patients and their doctors had similar time and risk preferences using a framed field experiment with 300 patients and 67 doctors in Athens, Greece in a natural clinical setting. The authors claim to be the first to attempt this, and have three main findings: i) there were significant time preference differences between the patients and doctors – doctors discounted future health gains and financial outcomes less heavily than patients; ii) there were no significant differences in risk preferences for health with both doctors and patients being mildly risk averse; iii) there were however risk preference differences for financial impacts with doctors being more risk averse than patients. The implication of this paper is that there is potential for improvements in doctor-patient communication for treatments, and as agents for patients, doctors should attempts to gauge their patient’s preferences and attitudes before recommending treatment. For those who heavily discount the future it may be preferable to provide care that increases the short term benefits.
Hospital productivity growth in the English NHS 2008/09 to 2013/14 [PDF]. Centre for Health Economics Research Paper [RePEc] Published 21st October 2016
Although this is technically a ‘journal round-up’, this week I’ve chosen to include the latest CHE report as I think it is something which may be of wider interest to the AHEBlog community. Given limited resources, there is an unerring call for both productivity and efficiency gains within the NHS. The CHE report examines the extent to which NHS hospitals have improved productivity: have they made better use of their resources by increasing the number of patients they treat and the services they deliver for the same or fewer inputs. To assess productivity, the report uses established methods: Total Factor Productivity (TFP) which is the ratio of all outputs to all inputs. Growth in TFP is seen as being key to improving patient care with limited resources. The primary report finding was that TFP growth at the trust level exhibits ‘extraordinary volatility’. For example one year there maybe TFP growth followed by negative growth the next year, and then positive growth. The authors assert that much of the TFP growth measured is in fact implausible, and much of the changes are driven largely by nominal effects alongside some real changes. These nominal effects may be data entry errors or changes in accounting practices and data recording processes which results in changes to the timing of the recording of outputs and inputs. This is an important finding for research assessing productivity growth within the NHS. The TFP approach is an established methodology, yet as this research demonstrates, such methods do not provide credible measures of productivity at the hospital level. If hospital level productivity growth is to be measured credibly, then a new methodology will be required.
Out of interest, do you know how the last paper differs from a paper with an almost identical title that we previously covered (https://aheblog.com/2016/04/07/you-wont-believe-what-these-nhs-productivity-statistics-mean-for-health-policy/)? Or is it just the unlucky case of two sets of researchers doing exactly the same work?