Health policy analysis
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Our research methods help policy makers make fairer decisions with better health outcomes.

The problem. Existing analyses focus on a mythical average citizen.

The solution. We develop ways of analysing who gains and loses from health policies.

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Years of Good Life Based on Consumption and Health: A Practical Well-Being Metric for Economic Evaluation

Cookson, R. A., Cotton-Barrett, O., Adler, M., Asaria, M. & T, O., Apr 2020, (Accepted/In press) Measuring the Global Burden of Disease: Philosophical Dimensions. Eyal, N., Hurst, S. A., Murray, C. J. L., Schroeder, S. A. & Wikler, D. (eds.). Oxford: Oxford University Press

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Publication details

Title of host publication Measuring the Global Burden of Disease: Philosophical Dimensions
Date Accepted/In press (current) - Apr 2020
Date Published - Jul 2020
Publisher Oxford: Oxford University Press
Editors N Eyal, S.A. Hurst, C.J.L Murray, S.A. Schroeder, D. Wikler
Original language English
ISBN (Print) 9780190082543

Publication details

Journal Medical Decision Making
Date Accepted/In press - 1 Oct 2019
Date E-pub ahead of print - 15 Feb 2020
Date Published (current) - Feb 2020
Issue number 2
Volume 40
Number of pages 13
Pages (from-to) 170-182
Early online date 15/02/20
Original language English


Background. A common aim of health expenditure is to reduce unfair inequalities in health. Although previous research has attempted to estimate the total health effects of changes in health expenditure, little is known about how changes affect different groups in the population. Methods. We propose a general framework for disaggregating the total health effects of changes in health expenditure by social groups. This can be performed indirectly when the estimate of the total health effect has first been disaggregated by a secondary factor (e.g., disease area) that can be linked to social characteristics. This is illustrated with an application to the English National Health Service. Evidence on the health effects of expenditure across 23 disease areas is combined with data on the distribution of disease-specific hospital utilization by age, sex, and area-level deprivation. Results. We find that the health effects from NHS expenditure changes are produced largely through disease areas in which individuals from more deprived areas account for a large share of health care utilization, namely, respiratory and neurologic disease and mental health. We estimate that 26% of the total health effect from a change in expenditure would accrue to the fifth of the population living in the most deprived areas, compared with 14% to the fifth living in the least deprived areas. Conclusions. Our approach can be useful for evaluating the health inequality impacts of changing health budgets or funding alternative health programs. However, it requires robust estimates of how health expenditure affects health outcomes. Our example analysis also relied on strong assumptions about the relationship between health care utilization and health effects across population groups.

Bibliographical note

This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.

Universal or targeted cardiovascular screening? Modelling study using a sector-specific distributional cost effectiveness analysis

Collins, B., Kypridemos, C., Cookson, R., Parvulescu, P., McHale, P., Guzman-Castillo, M., Bandosz, P., Bromley, H., Capewell, S. & O'Flaherty, M., 1 Jan 2020

Article in Preventive medicine

Publication details

Journal Preventive medicine
Date Accepted/In press - 23 Oct 2019
Date E-pub ahead of print - 31 Oct 2019
Date Published (current) - 1 Jan 2020
Volume 130
Early online date 31/10/19
Original language English


Distributional cost effectiveness analysis is a new method that can help to redesign prevention programmes by explicitly modelling the distribution of health opportunity costs as well as the distribution of health benefits. Previously we modelled cardiovascular disease (CVD) screening audit data from Liverpool, UK to see if the city could redesign its cardiovascular screening programme to enhance its cost effectiveness and equity. Building on this previous analysis, we explicitly examined the distribution of health opportunity costs and we looked at new redesign options co-designed with stakeholders. We simulated four plausible scenarios: a) no CVD screening, b) ‘current’ basic universal CVD screening as currently implemented, c) enhanced universal CVD screening with ‘increased’ population-wide delivery, and d) ‘universal plus targeted’ with top-up delivery to the most deprived fifth. We also compared assumptions around whether displaced health spend would come from programmes that might benefit the poor more and how much health these programmes would generate. The main outcomes were net health benefit and change in the slope index of inequality (SII) in QALYs per 100,000 person years. ‘Universal plus targeted’ dominated ‘increased’ and ‘current’ and also reduced health inequality by −0.65 QALYs per 100,000 person years. Results are highly sensitive to assumptions about opportunity costs and, in particular, whether funding comes from health care or local government budgets. By analysing who loses as well as who gains from expenditure decisions, distributional cost effectiveness analysis can help decision makers to redesign prevention programmes in ways that improve health and reduce health inequality.

Bibliographical note

© 2019 The Authors.


EQUIPOL is supported by the University of York, the Wellcome Trust (Grant No. 205427/Z/16/Z) and the NIHR (SRF-2013-06-015).

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