from The Academic Health Economists’ Blo… at https://bit.ly/2YOsHoV on August 31, 2020 at 12:00PM
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 39, Issue 8
This month’s Health Affairs includes two articles of particular relevance to the pandemic, from both the vaccine development and public health policy perspective. Sim et al. (with supporting contributors from the WHO, JHSPH, and Gates Foundation) assess the return on investment from immunisation against 10 key pathogens (Haemophilus influenzae type b, hepatitis B, human papillomavirus, Japanese encephalitis, measles, Neisseria meningitidis serotype A, Streptococcus pneumoniae, rotavirus, rubella, and yellow fever), in 94 low- and middle-income country settings (2011-2030). Previous studies by other authors have conducted similar analyses for 2011-2020 and costing data is updated for this paper.
As the ‘Decade of Vaccines’ draws to an end, they use both a cost-of-illness and value of a statistical life approach to evaluate the impact of vaccines, both from 2011-2020 and with projections through to 2030. They find that vaccine costs account for over 50% of total immunisation programme costs in LMIC settings (total costs of $24.6 in the first decade of life, increasing to $41.2 in the second decade of life). Their estimates suggest that vaccination averts $681.9 billion of economic burden in LMICs, with productivity loss comprising the main bulk of these economic benefits (98.9%).
Interestingly, immunisation against measles, in particular, drove the main findings of their results (76.4% of cost-of-illness economic benefits and 58.4% of value of a statistical life economic benefits). The overall ROI was estimated to be 22 using a cost-of-illness approach and 51.8 using a value of a statistical life approach, with the largest driver of uncertainty being GDP per capita. Using both approaches enables the authors to capture both immediate savings but also wider lifetime benefits, taking into account that some newer vaccines demonstrate lower marginal costs for each additional dose in the schedule. Nonetheless, this study demonstrates the increasing future gains expected from continued investment in vaccination programmes worldwide.
Consensus about the use of face masks during the current pandemic has gradually evolved, much of the debate has centred around the quality of the evidence available and the extent to which behavioural factors (and not only the medical literature) need to be considered. Nonetheless, even within countries, there has often been inconsistency in policy approaches. In the United States, the government gave advice from April 3rd for all to wear cloth face coverings where close contact with others in public spaces was unavoidable, citing evidence from presymptomatic/asymptomatic people. However, Lyu & Wehby exploit a natural experiment which arose as a result of each state deciding upon their face mask policy at differing time points. Fifteen states issued guidance on the wearing of face masks prior to the official CDC guidance (from April 8 – May 15). Using an event study methodology, they examined the effect of face cover mandates on the daily country-level COVID-19 growth rate, using a reference period of 1-5 days prior to the change in face mask orders changing. They were also able to examine the difference between states which only mandated for employees in certain environments to wear face masks versus blanket advice for all members of the public to wear masks. Their study adds to the overwhelming evidence that face mask usage can reduce transmission, and that enforcing masks only in workplaces is not as effective. The benefits of wearing face masks increased over time (up to 21+ days) and the magnitude of the effect was found to be comparable to as much as 19% of social distancing measures.
Volume 58, Issue 8
As the US elections draw closer, this study from this month’s Medical Care explores one particular facet of Obama’s Affordable Care Act, now 10 years old. From 2013-2016, 10.9 million more Americans benefited from Medicaid coverage as a result of the ACA; one of the provisions, Hospital Presumptive Eligibility (HPE), allowed hospitals to apply for the ability to register patients for temporary Medicaid coverage, dependent upon specified criteria. States previously did have this ability (including the enrolment of pregnant women and children for Child Health Insurance Program benefits), however the ACA broadened the criteria to include adults under 64 who fell below a given income threshold. Their study focuses on California, as it was one of the first states to implement the expansion in Medicaid provision.
Using data from Hospital Annual Financial Disclosure Reports linked to HPE data (for 462 hospitals, 363 with non-missing data), for 12 years prior to the introduction of ACA and 2 years thereafter, they compared gross and net patient revenue as well as uncompensated medical costs. By the end of 2018, 29,000 adults and 4,900 children were enrolled in HPE in California. Larger hospitals were significantly more likely to enrol on the HPE scheme, whereas smaller hospitals, those covering specialty areas, and paediatric hospitals were less likely. Hospitals who received a greater proportion of their revenue from Medicaid prior to HPE were subsequently more likely to enrol in HPE after the ACA; HPE enrolment was associated with a 9.7% increase in net Medicaid revenue, equivalent to a $6.15 million average increase. The data therefore strongly suggest that HPE allowed hospitals to be reimbursed for care which would previously have been uncompensated. Although there were strong associations between HPE-enrolled hospitals, which were associated with large populations of uninsured individuals, there were equally large hospitals – geographically close to large uninsured populations – that did not register for HPE. Further work needs to be done to examine the reasons why this was the case.