HEDS is part of the School of Health and Related Research (ScHARR) at the University of Sheffield. We undertake research, teaching, training and consultancy on all aspects of health related decision science, with a particular emphasis on health economics, HTA and evidence synthesis.

Thursday, 7 January 2021

We start the new year with our regular monthly trawl for new publications from HEDS in collaboration with colleagues in ScHARR and further afield and it has reaped a tremendous amount of fresh research. Many of these are currently in press, so you can find much of our work in its open access form via our institutional repository. Find them here: http://eprints.whiterose.ac.uk/view/iau/Sheffield=2EHRR.html

Biesty, L., Meskell, P., Glenton, C., Delaney, H., Smalle, M., Booth, A., Chan, X. H. S., Devane, D., & Houghton, C. (2020). A QuESt for speed : rapid qualitative evidence syntheses as a response to the COVID-19 pandemic. Systematic Reviews, 9(1). https://doi.org/10.1186/s13643-020-01512-5

International Journal of Health Policy and Management
International Journal of Health
Policy and Management

Booth, A., Laar, A., Barnes, A., Akparibo, R., Graham, F., Bash, K., Asiki, G., & Holdsworth, M. (n.d.). Policy Action within urban African Food Systems to Promote Healthy Food Consumption: a realist synthesis in Ghana and Kenya. International Journal of Health Policy and Management.

        Dodd, P., Yuen, C., Jayasooriya, S., van der Zalm, M., & Seddon, J. (n.d.). Quantifying the global number of tuberculosis survivors: a modelling study. Lancet Infectious Diseaseshttp://eprints.whiterose.ac.uk/168718/

        Gray, L. (2020). BMI trajectories, mortality and comorbidity in older adults. Value in Health, 23(Supplement 2), S608–S608. https://doi.org/10.1016/j.jval.2020.08.1242

Hardern, C., Lee, D., Sly, I., & Kearns, B. (2020). EX2 Structural Uncertainty in Survival Extrapolation: Exploring the IMPACT of FOUR MODEL Averaging Methods and Adjusting for DATA Maturity. Value in Health, 23, S402–S402. https://doi.org/10.1016/j.jval.2020.08.027

Jen-Yu Amy, C., Latimer, N. R., Gillespie, D., & Chilcott, J. (2020). PMU17 Prevalence, Characteristics and Key Issues of Modelling Treatment Sequences in Health Economic Evaluations: A Systematic Review of Nice Technology Appraisals. In Value in Health (Vol. 23, pp. S606–S606). Elsevier BV. https://doi.org/10.1016/j.jval.2020.08.1229

Jin, H., Tappenden, P., MacCabe, J. H., Robinson, S., McCrone, P., & Byford, S. (n.d.). Cost and health impacts of adherence to the National Institute for Health and Care Excellence schizophrenia guideline recommendations. The British Journal of Psychiatry, 1–6. https://doi.org/10.1192/bjp.2020.241 

Value in Health journal
Value in Health

Kearns, B., Cooper, K., & Cantrell, A. (2020). PMU13 Schizophrenia Treatment with Second-Generation Antipsychotics: A MULTI-Country Evaluation of the Costs of Cardiovascular and Metabolic Adverse Events and Weight GAIN. Value in Health, 23, S605–S605. https://doi.org/10.1016/j.jval.2020.08.1225 abstract

Kearns, B., Cooper, K., Cantrell, A., & Thomas, C. (n.d.). Schizophrenia treatment with second-generation antipsychotics: a multi-country comparison of the costs of cardiovascular and metabolic adverse events and weight gain. Neuropsychiatric Disease and Treatment.

Martin, C., Shrestha, A., Morgan, J., Bradburn, M., Herbert, E., Burton, M., Todd, A., Walters, S., Ward, S., Holmes, G., Reed, M., Collins, K., Robinson, T. G., Ring, A., Cheung, K. L., Audisio, R., Gath, J., Revell, D., Green, T., … Wyld, L. (2020). Treatment choices for older women with primary operable breast cancer and cognitive impairment: Results from a prospective, multicentre cohort study. Journal of Geriatric Oncology. https://doi.org/10.1016/j.jgo.2020.12.006

Matza, L. S., Stewart, K. D., Lloyd, A., Rowen, D., & Brazier, J. (n.d.). Vignette-Based Utilities: Usefulness, Limitations, and Methodological Recommendations. Value in Health.

McNamara, S., Tsuchiya, A., & Holmes, J. (2020). Does the UK-public’s aversion to inequalities in health differ by group-labelling and health-gain type? A choice-experiment. Social Science & Medicine. https://doi.org/10.1016/j.socscimed.2020.113573

Mshelia, S. E., Analo, C. V, & Booth, A. (n.d.). Factors influencing the utilisation of facility-based delivery in Nigeria: a qualitative evidence synthesis. Journal of Global Health Reports. https://doi.org/10.29392/001c.17961

Mukuria, C., Rowen, D., Brazier, J. E., McGarry, L., Quittner, A., Lou, Y., Sosnay, P., & Acaster, S. (2020). PR1 Comparison of the Psychometric Performance of a New Condition-Specific Preference-Based Measure Derived from the Cfq-R (CFQ-R-8D) to EQ-5D-3L and SF-6D to Evaluate Health-Related Quality-of Life (HRQOL) in People with Cystic Fibrosis (CF). Value in Health, 23, S689–S689. https://doi.org/10.1016/j.jval.2020.08.1732

Development and Psychopathology journal
Development and 

 Newton, K., Taylor Buck, E., Weich, S., & Uttley, L. (2020). A review and analysis of the components of potentially effective perinatal mental health interventions for infant development and mother-infant relationship outcomes. Development and Psychopathology. https://doi.org/10.1017/s0954579420001340

        Peasgood, T., Mukuria, C., Carlton, J., Connell, J., & Brazier, J. (n.d.). Criteria for item selection for a preference-based measure for use in economic evaluation. Quality of Life Research. https://doi.org/10.1007/s11136-020-02718-9

         Richards, D., Enrique, A., Eilert, N., Franklin, M., Palacios, J., Duffy, D., Earley, C., Chapman, J., Jell, G., Sollesse, S., & Timulak, L. (2020). Author Correction: A pragmatic randomized waitlist-controlled effectiveness and cost-effectiveness trial of digital interventions for depression and anxiety. Npj Digital Medicine, 3(1). https://doi.org/10.1038/s41746-020-0298-3

Romero, C. P., Marinho, D. S., Castro, R., de Aguiar Pereira, C. C., Silva, E., Caetano, R., Silva Elias, F. T., Chilcott, J., & Dixon, S. (2020). Cost-effectiveness analysis of point-of-care rapid testing versus laboratory-based testing for antenatal screening of syphilis in Brazil. Value in Health Regional Issues, 23, 61–69. https://doi.org/10.1016/j.vhri.2020.03.004

Scarisbrick, J., Schmidt, F., Turini, M. M., D’agostino, P., Thornton, S., Evans, J., Ader, J., van Hest, N., & Brazier, J. E. (2020). PRO140 Health-Related Quality of Life Associated with Mycosis Fungoides-Type Cutaneous T-Cell Lymphoma Patients: Determination of Utility Values from a UK-Based Clinician Questionnaire. Value in Health, 23, S715–S715. https://doi.org/10.1016/j.jval.2020.08.1876

Schneider, P. P., Smith, R. A., Bullas, A. M., Quirk, H., Bayley, T., Haake, S. J., Brennan, A., & Goyder, E. (2020). Multiple deprivation and geographic distance to community physical activity events — achieving equitable access to parkrun in England. Public Health, 189, 48–53. https://doi.org/10.1016/j.puhe.2020.09.002

Shah, K., Bennett, B., Lenny, A., Longworth, L., Brazier, J. E., Oppe, M., Pickard, A. S., & Shaw, J. W. (2020). PCN48 Adapting Preference-Based Utility Measures to Capture the Impact of Cancer Treatment-Related Symptoms. Value in Health, 23, S430–S430. https://doi.org/10.1016/j.jval.2020.08.185

Image of Obesity Reviews Journal
Obesity Reviews

Srivastava, T., Latimer, N. R., & Tappenden, P. (2020). PMU78 Estimation of Transition Probabilities for State-Transition Models: A Review of NICE Appraisals. In Value in Health (Vol. 23, pp. S615–S616). Elsevier BV. https://doi.org/10.1016/j.jval.2020.08.1290

Tai, T.-A., Latimer, N., Benedict, A., Kiss, Z., & Nikolaou, A. (2020). Prevalence of immature survival data for anti-cancer drugs presented to the National Institute for Health and Care Excellence and impact on decision making. Value in Health. https://doi.org/10.1016/j.jval.2020.10.016 

Trübswasser, U., Verstraeten, R., Salm, L., Holdsworth, M., Baye, K., Booth, A., Feskens, E. J. M., Gillespie, S., & Talsma, E. F. (n.d.). Factors influencing obesogenic behaviours of adolescent girls and women in low‐ and middle‐income countries: A qualitative evidence synthesis. Obesity Reviews, obr.13163. https://doi.org/10.1111/obr.13163


Monday, 7 December 2020

What has 2020 done to the UK’s alcohol consumption?

 What has 2020 done to the UK’s alcohol consumption?

Alcohol stats expert Colin Angus trawls through a lot of data to work out Brits’ drinking habits in this exceptional year

Image of Colin Angus
Colin Angus

02 December 2020 – To say 2020 has been tumultuous would be something of an understatement. It’s been a strange old year full of crisis and, well, more crisis. If stereotypes are to be believed, then the pub or the drinks cabinet is one of the first ports of call for the British when hard times strike. So it might seem reasonable to suspect that we’ve all been drinking more this year. Yet at the same time, pubs have been closed, or severely restricted, since late March, and we drink a lot in pubs. So maybe we’re drinking less overall?

Mixed messages

We’ve certainly been given conflicting messages about alcohol sales over the course of the year. Back in March when lockdown was announced there were media reports about panic buying and images of bare shelves in supermarkets. There were also a series of stories driven by market research company data which reported that alcohol sales had risen, maybe by as much as 58%. However these stories all focused exclusively on shop-bought alcohol. In 2019, 28% of alcohol sold in Great Britain was bought and drunk in pubs, clubs, cafés and restaurants. If the pubs were closed, we could all buy 40% more alcohol from the supermarket and barely end up drinking more than before.

Alongside these stories, we’ve seen a large number of surveys during and after lockdown which have asked respondents whether they think they’ve been drinking more or less than before the pandemic. You might be suspicious, and with good reason, about the accuracy of measures like this, but the picture they painted, almost unanimously, was one of mixed effects. Some people reported that they had been drinking less or had even given up alcohol entirely, while others reported that they were drinking more than usual. Often there was some degree of polarisation, with people who were drinking within the UK drinking guidelines of 14 units of alcohol a week before lockdown began being much more likely to say they were drinking the same or less, while heavier drinkers were more likely to have increased their drinking. This polarisation was reinforced by a more robust study which found that, in April, the number of people who reported attempting to cut down their drinking increased significantly, while at the same time, so did the number of people reporting that they were drinking at high-risk levels. Taken together, it was hard to make sense of this data. As somebody who has spent more time than most looking at alcohol consumption patterns and data over the last decade, my suspicion was that we were probably drinking less on average, but that some people, particularly heavier drinkers, were drinking more.

Image of alcohol graph

Show me the numbers

With this suspicion in mind, I was surprised to see the Office for Budget Responsibility state in their latest economic forecast, published last week, that “The loss in [alcohol duty] receipts from closures of pubs and restaurants has been more than offset by higher sales in supermarkets and other shops”. Luckily, HMRC published their quarterly alcohol duty bulletin a few days later, so I didn’t have to wait long to see where this claim came from.

Sure enough, HMRC state that they collected £313m more in alcohol duty in April-October 2020 than in the same period in 2019, an increase of 4.5%. So, does this mean that alcohol sales have gone up by 4.5%? Well, no. This figure doesn’t account for inflation. If we look at the longer-term trend in alcohol duty receipts, we can see that in cash terms (i.e. before adjusting for inflation) they have been rising steadily for years, while in real terms (i.e. after adjusting for inflation) they have been pretty stable for at least a decade.

Image of an alcohol graph

One other limitation of this approach is that it only compares 2020 with 2019. Alcohol sales can be quite volatile depending on various factors, including the weather, major sporting events and economic conditions. So to get a better sense of whether 2020 has seen unusually high (or low) alcohol sales, I think it makes more sense to take an average of the data for 2015-19 and compare to that. This is the same approach that the Office for National Statistics have been using to look at excess mortality during the pandemic. So what does this tell us?

Well, by this measure, alcohol duty revenue in 2020 has actually fallen slightly, by just under 1%. But there are some interesting patterns in this. Duty receipts fell very sharply in March and April and then we see much more revenue collected than usual in June and August. It’s tempting to interpret this as showing that we were all very abstemious during lockdown and then had a bit of a party once restrictions were lifted, but that’s not quite right. These numbers reflect the actual payments received by HMRC from the alcohol industry. Usually these are collected within a month of the alcohol being cleared for sale, but in exceptional circumstances it is possible to negotiate a payment extension of up to three months. HMRC themselves highlight this as the likely cause for these unusual spikes – they really relate to alcohol sold a few months previously, but where payment was deferred due to the financial pressures that lockdown imposed on many alcohol producers. This suggests that the dip in March and April was maybe not as big as it seems in reality.

Image of an alcohol duty graph

Luckily, HMRC also provide data on how much alcohol has been cleared for sale. As beer and spirits are taxed based on their alcohol content, we have great data on the volume of alcohol being sold as these two products. Wine and cider, however, are taxed on the basis of their
product volume, so we have to make a few assumptions about their alcoholic strength. When we do this, a clearer picture emerges. The amount of alcohol cleared for sale did dip in March, but only very slightly, and this has been more than offset by higher than usual clearances in July – September. Now these figures reflect the amount of alcohol released for sale, not the amount sold, nor the amount actually drunk. It could be that all of this extra alcohol is just stacked up on supermarket shelves, or in our drinks cabinets, but that seems fairly unlikely to me. It is probably true that some pubs did have to throw away some products, particularly beer, which had spoilt during the spring lockdown. In fact, they are entitled to claim back the duty they have paid on this spoilt alcohol. This means that it's likely that the increase in alcohol sales in 2020, compared with previous years, is slightly less than 3.4%, but it's unlikely to be much less.

Image of ethanol clearances by HMRC graph

Have different products been affected differently?

As HMRC report their data separately for beer, cider, spirits and wine, we can actually look at how these different types of alcohol have been affected differently. Looking at revenue, you can see a huge fall in revenue from beer sales during the spring lockdown. In relative terms cider has actually seen an even bigger fall, although it makes up a much smaller proportion of the market. At the same time, duty revenue from wine has picked back up after a dip in the spring, while spirits revenue has increased by almost 9% over the year.

Image of Total HMRC revenue from alcohol duty

Looking at the figures for alcohol clearances, the picture is very similar, although the drop for beer is much smaller.

Image of a graph of total ethanol clearances reported by HMRC

Some of these changes are more surprising than others. We would expect beer sales to be most affected by the closure of pubs as typically almost half of all beer sold is drunk in the on-trade (pubs, bars, restaurants and cafés). A much smaller proportion of spirits and wine sales comes from the on-trade, but the fact that we have seen clearances of these products increase this year suggests that either beer drinkers denied the opportunity to have a few pints in their local have switched to spirits, or that people who drank predominantly spirits anyway have increased their consumption from previous years.

Image of a graph - The British drink beer in pubs, but wine and spirits at home


In fact some of these product-level changes could well just be continuations of pre-existing trends. Monthly clearances of cider have been falling for years and spirits have been rising, driven to some extent by the ‘gin boom’, since 2015. It certainly does look as though there might have been some switching between beer and wine. Or perhaps beer drinkers are the ones who are taking the opportunity to try and drink a little less, while wine drinkers are drinking more.

Image of a graph - longer term trends in alcohol clearance by product


After all of these graphs, what do we really know about drinking in 2020? Alcohol consumption probably did fall overall at the start of lockdown in the spring, but we seem to have more than made up for it in the latter part of the summer and overall alcohol sales have increased in 2020 compared with previous years. Due to the various restrictions and enforced closures that have affected pubs across the UK this year, it seems very likely that 2020 has been a bonanza year for alcohol sales in supermarkets. We have also seen some quite large shifts away from beer and towards wine and particularly spirits. It will be interesting to see whether these are sustained once things (hopefully) start returning to normal in 2021. Finally, it’s important to remember that HMRC data reflects the total revenue and alcohol clearances across the whole population. Whether the small increase in overall alcohol sales reflects a small increase across the whole population, or a large increase in a small number of heavy drinkers, will have a large bearing on what the longer term alcohol-related health impacts of these changes are, and that’s something that we won’t start to find out for some time yet.

Written by Colin Angus, research fellow at the Sheffield Alcohol Research Group within The School of Health and Related Research.

All IAS Blogposts are published with the permission of the author. The views expressed are solely the author's own and do not necessarily represent the views of the Institute of Alcohol Studies.

The piece was originally published by The Institute of Alcohol Studies and republished by theirs and Colin Angus' kind permission.

Thursday, 19 November 2020

Update to the Methods of Health Technology Evaluation for NICE


The NICE Decision Support Unit (DSU) has made substantial contributions to every update of NICE’s “Methods for Technology Appraisal” since the unit started in 2003. Given that the last update to this document was in 2013, an update is long overdue. Over the past two years we’ve been engaged in a series of projects to help inform the update that NICE has just put out for consultation and there is an incredible amount of our previous work that was referred to as part of the update process.

This time round, the scope extends beyond Technology Appraisals and encompasses Medical Technologies, Diagnostics and Highly Specialised Technologies. The DSU, including our members based at the Universities of Sheffield, York, Leicester and Bristol, have undertaken a series of studies that were used to help inform discussions on the methods update. These are now available via our website and cover a real variety of areas, some of which are recurrent themes for both ourselves and NICE, whilst others are novel. Examples include:

- when and how should cost-minimisation methods be used,

- whether unrelated future health care costs should be included in cost effectiveness analyses,

- the use of non-standard survival analysis methods,

- the types of “modifiers” to decisions in addition to cost effectiveness information,

- how to measure and value quality of life in more complex situations such as when only limited data are available, for assessing health technologies for children, or when needing to map from different variants of the EQ5D.

- how to use qualitative evidence in the HTA process

- And a whole series of thorny issues in relation to evidence synthesis such as combining observational and randomised evidence, surrogate outcomes and evidence for diagnostics.

Of course, the work of the DSU is only one of many inputs to the changes NICE are proposing but we are pleased to continue to play an important role in the update process. The consultation is now live here where you can find a list of proposed changes and related documents. We’d encourage you to contribute to the consultation exercise. Head to our website here for more information on our reports or more information about our work more generally.  

Wednesday, 18 November 2020

Valuing health outcomes for health technology assessment workshop

This workshop was designed by the University of Sheffield and the University of Shandong.  The workshop was held in Jinan, China, on the 16th and 17th November.  30 delegates from around China gathered to hear talks by academics from Shandong and Tianjin universities.  Professors Simon Dixon, John Brazier and Dr Praveen Thokala gave presentation online.  The event was led by Professor Sun Qiang from Shandong University.
The partnership aims to create long-term, sustainable collaboration in health economics, which will give UK and Chinese academics the means to work together on world-class educational and research outcomes that would otherwise not be possible working in isolation.
The workshops are part of the UK-China Health and Economy Partnership, which is a collaboration between leading Chinese and UK universities.  The UK-China Health and Economy Partnership is a novel knowledge transfer partnership that will promote long-term collaboration between Bournemouth University, University of York, University of Sheffield and University of Leeds in the UK and Fudan University, Shandong University and Zhejiang University in China.

The Partnership is funded by GSK and the British Council.  
Details of the workshop can be found online here.