How Qualitative Methods Can be Used to Inform Model Development

Samantha Husbands, Sue Jowett, Pelham M. Barton, Joanna Coast

Research output: Contribution to journalArticle (Academic Journal)peer-review

16 Citations (Scopus)
343 Downloads (Pure)


Decision-analytic models play a key role in informing healthcare resource allocation decisions. However, there are ongoing concerns with the credibility of models. Modelling methods guidance can encourage good practice within model development, but its value is dependent on its ability to address the areas that modellers find most challenging. Further, it is important that modelling methods and related guidance are continually updated in light of any new approaches that could potentially enhance model credibility.

The objective of this paper was to highlight the ways in which qualitative methods have been used and recommended to inform decision-analytic model development and enhance modelling practices. With reference to the literature, the paper discusses two key ways in which qualitative methods can be, and have been, applied. The first approach involves using qualitative methods to understand and inform general and future processes of model development, and the second, using qualitative techniques to directly inform the development of individual models. The literature suggests that qualitative methods can improve the validity and credibility of modelling processes by providing a means to understand existing modelling approaches that identifies where problems are occurring and further guidance is needed. It can also be applied within model development to facilitate the input of experts to structural development. We recommend that current and future model development would benefit from the greater integration of qualitative methods, specifically by studying ‘real’ modelling processes, and by developing recommendations around how qualitative methods can be adopted within everyday modelling practice.
Original languageEnglish
Pages (from-to)607-612
Number of pages6
Issue number6
Early online date20 Mar 2017
Publication statusPublished - 1 Jun 2017


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