Research: increasing value, reducing waste The new venture from the evidencebased medicine movement promises to clean up the waste in biomedical research. The Lancet Series entitled Research: increasing value, reducing waste had such a promising title;1,2 what’s not to like? The authors claim that 85% of the investment in biomedical research is wasted because of inadequate production and reporting of research and that this accounts for its failure to deliver more clinical benefits. The group of authors is composed mostly of experts in qualitative research, concerned with reporting systematic reviews of previous work and so with study design and reporting methods that facilitate this. There will always be unanimity that reducing waste is good. Deciding what is wasteful in science might be more difficult. The middle period of the 20th century was one of remarkable medical progress when design and reporting methods would have been less regulated than now. The decrease in clinical discovery during the past three decades might have had more to do with the reconfiguration of clinical practice and clinical science, which occurred during that period. Ironically, these changes were also argued for by the group’s much-heralded icon, Archie Cochrane, who claimed that research done in the health service made no contribution to medical advances, was wasteful, and should be replaced by applied or qualitative research.3 The Lancet Series on research is emblematic of these changes: the views of a group largely composed of qualitative researchers cannot reflect those of the wider biomedical community. Consequently, its understanding of the purposes of different forms of research and the distinction between qualitative research and investigative science might be limited. The Series might have benefited from a stronger www.thelancet.com Vol 383 March 29, 2014

representation of clinicians and investigative scientists. But perhaps clinicians today might be more concerned with campaigns against the failures in public health that threaten to overwhelm their health service and the epidemics of obesity and misuse of tobacco and alcohol. I declare that I have no competing interests.

Desmond John Sheridan [email protected] Imperial College London, Faculty of Medicine, London W2 1NY, UK 1

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Macleod MR, Michie S, Roberts I, et al. Biomedical research: increasing value, reducing waste. Lancet 2014; 383: 101–04. Glasziou P, Altman DG, Bossuyt P, et al. Reducing waste from incomplete or unusable reports of biomedical research. Lancet 2014; 383: 267–76. Cochrane AL. Effectiveness and efficiency: random reflections on health services, 2nd edn. London: Nuffield Provincial Trust, 1972: 12, 44, 81, 83.

I read with interest the recent Lancet Series on research. The Series papers are of great interest and I hope they will be very influential, but there is a gap in the Series—namely, any contribution of economics to this fundamentally economic issue. The Series broadly considers the issue of technical efficiency—ie, either minimising the cost to obtain a given outcome, for example through avoidance of waste while undertaking a trial,1 or maximising the value of the research subject to the funds available by ensuring completeness of reporting both of trial results and associated protocols.2 Issues outside the control of individual researchers that might increase technical efficiency (such as appropriate regulation) are also considered in the Series. Iain Chalmers and colleagues 3 cover the issue of how to decide which research questions need answering, suggesting a number of approaches, particularly involving input from patients. Burden of disease is mentioned as an alternative. In addition to the limitations raised by the authors, this method has been criticised in the economics literature because

of its focus on the size of a problem, rather than ability to do anything about it or degree of uncertainty around treatment decisions.4 However, one important area omitted in the Series is the step between deciding which research questions need answering and how to do that research efficiently. This issue is that of allocative efficiency—ie, because we cannot fund all research that is worthwhile, which would provide the best return on investment for society as a whole? Methods exist to predict the expected value (in terms of health gain) of a particular research project. When this gain is compared with the cost, a set of projects can be selected that maximises expected health gain subject to the budget.5 Economics has various methods available that can assist with the decisions faced by research funding panels (and others interested in how public money is spent). While such technical solutions cannot—and should not—replace careful discussion within funding panels, they can provide a rational framework and starting point to help allocate scarce research funds to the greatest benefit of society. Drawing on economic theories and methods in future discussions could well help to shed light on possible approaches to assist clinicians, managers, patients, and others with these difficult decisions.

Phil Fisk/Science Photo Library

Correspondence

For the Lancet Series Research:

increasing value, reducing waste see http://www.thelancet. com/series/research

I declare that I have no competing interests.

Edward Wilson [email protected] Cambridge Centre for Health Services Research, Institute of Public Health, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0SR, UK 1

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Ioannidis JPA, Greenland S, Hlatky MA, et al. Increasing value and reducing waste in research design, conduct, and analysis. Lancet 2014; 383: 166–75. Glasziou P, Altman DG, Bossuyt P, et al. Reducing waste from incomplete or unusable reports of biomedical research. Lancet 2014; 383: 267–76. Chalmers I, Bracken MB, Djulbegovic B, et al. How to increase value and reduce waste when research priorities are set. Lancet 2014; 383: 156–65. Fleurence RL, Torgerson DJ. Setting priorities for research. Health Policy 2004; 69: 1–10.

Submissions should be made via our electronic submission system at http://ees.elsevier.com/ thelancet/

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Claxton K. The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologies. J Health Econ 1999; 18: 341–64.

Katie Harron, *Ruth Gilbert [email protected] UCL Institute of Child Health, London WC1N 1EH, UK 1

Initiatives to widen the use of administrative data could help to reduce waste in research. 1–3 We suggest recording consent to research in patients’ routinely captured administrative health data to increase value (through improved accountability) and reduce waste (through improved safety surveillance and secondary research). Consent to research is relevant to patients’ health, service providers, planners and funders, and to research. Consent could be routinely recorded in the same way as other health-care procedures without explicit consent other than the generic opt-out applied to all health records.4 No information would be recorded from the study other than the study identifier. In terms of accountability, recording of consent would allow regulatory authorities, service and research funders, and journal editors to audit research undertaken. For example, regulators could assess whether research for licensing of drugs or devices was done in appropriate or representative populations, and journal editors could detect fraud. Most importantly, surveillance for some adverse events could be collected by outcomes captured in longitudinal linked administrative health-care data. In terms of secondary research, outcomes not considered in the original research but captured by administrative data could be investigated, provided investigators release minimum data (with proportionate requirements for consent), such as treatment allocation, for linkage to the patient’s health-care records. Building on the UK Government’s investment in wider use of linked administrative data, linkages could extend to data beyond health, such as school achievement, employment, or social care.2 We declare that we have no competing interests.

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Salman RA-S, Beller E, Kagan J, et al. Increasing value and reducing waste in biomedical research regulation and management. Lancet 2014; 383: 176–85. Economic and Social Research Council. The Big Data Family is born. http://www.esrc.ac.uk/ news-and-events/press-releases/28673/thebig-data-family-is-borndavid-willetts-mpannounces-the-esrc-big-data-network.aspx (accessed Jan 13, 2014). Medical Research Council. £20 million for new health informatics research institute. http:// www.mrc.ac.uk/Newspublications/News/ MRC009207 (accessed Jan 13, 2014). Greenhalgh T, Wood GW, Bratan T, Stramer K, Hinder S. Patients’ attitudes to the summary care record and HealthSpace: qualitative study. BMJ 2008; 336: 1290–95.

the proband and the institution doing the research. From a legal perspective, the responsibility to protect privacy cannot be delegated from the research institution to third parties without contracting them. An adequate approach needs to balance transparency and data safety to minimise the risk of data misuse. New platforms like DataSHIELD4 allow for shared participant-level data analyses and avoid uncontrolled access to individual data. We declare that we have no competing interests.

*Henry Völzke, Carsten O Schmidt, Wolfgang Hoffmann [email protected]

An-Wen Chan and colleagues campaign for publication of original, participant-level data to minimise bias in biomedical research. Recently, examination programmes of population studies have became more and more comprehensive. Thus, latest examinations for the Study of Health in Pomerania2 took 25 h, and there are millions of variables per participant, including information about socioeconomic status, behavioural factors, molecular markers, subclinical disorders, and clinical diseases. Chan and colleagues 1 support publication of individual data in an anonymised fashion. In view of the bulk of variables in comprehensive population research, however, datasets are never really anonymised. Matching age and sex with only one to two continuously distributed variables allows third parties to create a combined dataset from different sources. Application of data mining as a method to select disease predictors from comprehensive datasets3 would even require the publication of most, if not all, individual data. Knowledge of some key indicators and study participation are then sufficient to identify the person behind the proband, especially from studies with large sampling fraction from the target population. In many countries, privacy and data safety are regulated between 1

Institute for Community Medicine, University Medicine Greifswald, D-17487 Greifswald, Germany 1

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Chan AW, Song F, Vickers A, et al. Increasing value and reducing waste: addressing inaccessible research. Lancet 2014; 383: 257–66. Volzke H, Alte D, Schmidt CO, et al. Cohort profile: the Study of Health in Pomerania. Int J Epidemiol 2011; 40: 294–307. Volzke H, Schmidt CO, Baumeister SE, et al. Personalized cardiovascular medicine: concepts and methodological considerations. Nat Rev Cardiol 2013; 10: 308–16. Doiron D, Burton P, Marcon Y, et al. Data harmonization and federated analysis of population-based studies: the BioSHaRE project. Emerg Themes Epidemiol 2013; 10: 12.

Artificial labels for research publications are not helpful for medical science. A recommendation made by Iain Chalmers and colleagues1 applies to all research: proposals for research, and research itself, should be “justified by systematic reviews showing what is already known”. More than 200 years ago, the very first sentence of the first article in the first issue of The New England Journal of Medicine read: “In our inquiries into any particular subject of medicine, our labours will generally be shortened and directed to their proper objects, by a knowledge of preceding discoveries”.2 Yet, a subtle but crucial impediment to such condition sine qua none might be the prevailing labelling of, and differentiation between, original and explicitly (or implicitly) other www.thelancet.com Vol 383 March 29, 2014

Research: increasing value, reducing waste.

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