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Abstract
Background: Health technology assessments (HTA) include a systematic review of the clinical effectiveness evidence and a cost-effectiveness model. The development of the cost-effectiveness model usually requires additional information beyond clinical efficacy. Depending on the timing, size and number of information requirements the reviewer can be faced with considerable difficulties ensuring that the reviewing is done in a timely and systematic fashion. There is tension in terms of the need to ensure that this process is transparent and reproducible. Different model parameters may require different levels of resource depending on their importance. While there has been research on searching for model parameters, there is little guidance regarding to best practice in the selection and use of evidence within models. Methods: A focus group was held with 15 experienced systematic reviewers, information specialists and health economic modellers. Framework analysis was used to draw out emergent themes from the transcribed data. Results: Six key themes were identified including: current practice for reviewing for model parameters, level of information required for parameters, timing of the reviewing, ideal practice, areas for further research and problem structuring. Reviewing, searching and modelling need to be seen as integrated tasks and the whole team should be involved in the structuring of the decision problem. Good communication was deemed to be essential and more time should be spent on the most important parameters. The ability to make assessments on the quality of information was also considered important. Future research needs include training for focussed searching, problem structuring, quality assessment and the validation of parameter estimates. Conclusions: This preliminary investigation highlights several key concerns and indeed potential deficiencies in the process of identifying, selecting and using evidence to inform model parameters. Guidance should focus on how this process may be best operationalised.