HEALTH ECONOMICS ANALYSIS PLANS- WHERE ARE WE NOW?

Author(s)

Thorn JC1, Ridyard CH2, Hughes D2, Wordsworth S3, Mihaylova B3, Noble S1, Hollingworth W1
1University of Bristol, Bristol, UK, 2Bangor University, Bangor, UK, 3University of Oxford, Oxford, UK

Background: The use of statistical analysis plans (SAPs), drawn up in advance of the analysis phase, is an accepted means of reducing bias in reporting the results of randomised controlled trials (RCTs). However, while health economics analysis plans (HEAPs) to guide trialists in conducting economic evaluations alongside RCTs are becoming more widespread, they lag behind SAPs in terms of standardisation and acceptance, and there is a fundamental question over whether they add value to the trial process. Aim: To map current practice and beliefs about the appropriate implementation (or otherwise) of HEAPs, with a view to drawing up good practice guidelines in future work. Methods: A workshop was held to discuss issues around HEAPs, providing a forum in which health economists (predominantly university-based) and other interested parties engaged in applied economic evaluations could open a dialogue on appropriate methods of standardisation. Sessions were presented on experiences of using HEAPs in trials, and participants discussed topics including the appropriate content of HEAPs, the circumstances in which changes are permissible and the appropriate oversight and governance. Results: There are few guidelines available to aid health economists in compiling HEAPs. There is currently substantial variation in the structure, format and content of HEAPs, and there are questions over their purpose and appropriate methods of oversight. Although concerns remain over the impact of the bureaucratic burden involved in producing a plan in advance (particularly given the relatively small health economic workforce), the potential loss of useful post hoc analyses if a plan is too rigid, and the timing of completion, there was a general feeling that HEAPs would be useful. Conclusion: Clarity on the appropriate usage of HEAPs would be advantageous. We plan to conduct a Delphi survey of practising health economists to determine suitable content for a HEAP.

Conference/Value in Health Info

2016-10, ISPOR Europe 2016, Vienna, Austria

Value in Health, Vol. 19, No. 7 (November 2016)

Code

PRM221

Topic

Methodological & Statistical Research

Topic Subcategory

Confounding, Selection Bias Correction, Causal Inference

Disease

Multiple Diseases

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