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Open Access Correspondence

Reporting guidelines for modelling studies

Carol Bennett12* and Douglas G Manuel123456

Author Affiliations

1 Clinical Epidemiology Program, Ottawa Hospital Research Institute, 1053 Carling Avenue, Ottawa, K1Y 4E9, Canada

2 ICES@uOttawa, Institute for Clinical Evaluative Sciences, 1053 Carling Avenue, Ottawa, K1Y 4E9, Canada

3 Department of Family Medicine, University of Ottawa, Ottawa, K1H 8M5, Canada

4 CT Lamont Primary Health Care Research Centre, University of Ottawa, Ottawa, ON, Canada

5 Bruyere Research Institute, University of Ottawa, Ottawa, ON, Canada

6 Department of Epidemiology and Community Medicine, The University of Ottawa, Ottawa, ON, Canada

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BMC Medical Research Methodology 2012, 12:168  doi:10.1186/1471-2288-12-168

Published: 7 November 2012

Abstract

Background

Modelling studies are used widely to help inform decisions about health care and policy and their use is increasing. However, in order for modelling to gain strength as a tool for health policy, it is critical that key model factors are transparent so that users of models can have a clear understanding of the model and its limitations.Reporting guidelines are evidence-based tools that specify minimum criteria for authors to report their research such that readers can both critically appraise and interpret study findings. This study was conducted to determine whether there is an unmet need for population modelling reporting guidelines.

Methods

We conducted a review of the literature to identify: 1) guidance for reporting population modelling studies; and, 2) evidence on the quality of reporting of population modelling studies. Guidance for reporting was analysed using a thematic approach and the data was summarised as frequencies. Evidence on the quality of reporting was reviewed and summarized descriptively.

Results

There were no guidelines that specifically addressed the reporting of population modelling studies. We identified a number of reporting guidelines for economic evaluation studies, some of which had sections that were relevant population modelling studies. Amongst seven relevant records, we identified 69 quality criteria that have distinct reporting characteristics. We identified two papers that addressed reporting practices of modelling studies. Overall, with the exception of describing the data used for calibration, there was little consistency in reporting.

Conclusions

While numerous guidelines exist for developing and evaluating health technology assessment and economic evaluation models, which by extension could be applicable to population modelling studies, there is variation in their comprehensiveness and in the consistency of reporting these methods. Population modelling studies may be an area which would benefit from the development of a reporting guideline.