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Reputations count: why benchmarking performance is improving health care across the world

Published online by Cambridge University Press:  16 March 2018

Gwyn Bevan*
Affiliation:
Professor of Policy Analysis, Department of Management, London School of Economics and Political Science, London, UK
Alice Evans
Affiliation:
Lecturer in the Social Science of Development, Department of International Development, King’s College London, London, UK
Sabina Nuti
Affiliation:
Professor of Health Management, Laboratorio Management e Sanità, Institute of Management, Scuola Superiore Sant’Anna, Pisa, Italy
*
*Correspondence to: Gwyn Bevan, Professor of Policy Analysis, Department of Management, London School of Economics and Political Science, London WC2A 2AE, UK. Email: [email protected]

Abstract

This paper explores what motivates improved health care performance. Previously, many have thought that performance would either improve via choice and competition or by relying on trust and altruism. But neither assumption is supported by available evidence. So instead we explore a third approach of reciprocal altruism with sanctions for unacceptably poor performance and rewards for high performance. These rewards and sanctions, however, are not monetary, but in the form of reputational effects through public reporting of benchmarking of performance. Drawing on natural experiments in Italy and the United Kingdom, we illustrate how public benchmarking can improve poor performance at the national level through ‘naming and shaming’ and enhance good performance at the sub-national level through ‘competitive benchmarking’ and peer learning. Ethnographic research in Zambia also showed how reputations count. Policy-makers could use these effects in different ways to improve public services.

Type
Articles
Copyright
© Cambridge University Press 2018 

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Footnotes

This paper is a revised version of a paper presented at the LSEHSC International Health Policy Conference 2017, London School of Economics and Political Science, 16–19 February 2017.

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