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Background: In an era of scarce and competing priorities for implementation, choosing what to implement is a key decision point for many behavioural change projects. The values and attitudes of the professionals and managers involved inevitably impact the priority attached to decision options. Reliably capturing such values is challenging. Methods: This paper presents an approach for capturing and incorporating professional values into the prioritization of healthcare innovations being considered for adoption. Conjoint Analysis (CA) was used in a single UK Primary Care Trust to measure the priorities of healthcare professionals working with women with postnatal depression. Rating-based CA data was gathered using a questionnaire and then mapped onto 12 interventions being considered as a means of improving the management of postnatal depression. Results: The 'impact on patient care' and the 'quality of supporting evidence' associated with the potential innovations were the most influential in shaping priorities. Professionals were least influenced by whether an innovation was an existing national or local priority, or whether current practice in the Trust was meeting minimum standards. Ranking the 12 innovations by the preferences of potential adopters revealed 'guided self help' was the top priority for implementation and 'screening questions for post natal depression' the least. When other factors were considered (such as the presence of routine data or planned implementation activity elsewhere in the Trust), the project team chose to combine the eight related treatments and implement these as a single innovation referred to as 'psychological therapies'. Conclusions: Using Conjoint Analysis to prioritise potential innovation implementation options is a feasible means of capturing the utility of stakeholders and thus increasing the chances of an innovation being adopted. There are some practical barriers to overcome such as increasing response rates to conjoint surveys before routine and unevaluated use of this technique should be considered [ABSTRACT FROM AUTHOR]

Background: Exploring barriers to the uptake of research based recommendations into practice is an important part of the development of implementation programmes. Techniques to identify barriers can include use of theory-informed questionnaires and qualitative interviews. Conceptualising and measuring theory-informed factors, and engaging health professionals' to uncover all potential barriers, can be a difficult task. This paper presents a case study of the process of trying to identify, systematically, the key factors influencing health professionals' referrals for women diagnosed with mild to moderate postnatal depression for psychological treatment. The paper illustrates how the factors were conceptualised and measured and explores the real world challenges experienced, with implications for future implementation studies. Methods: Theory-informed factors were conceptualised and measured using a questionnaire and interviews. The questionnaire was piloted, before being administered to general practitioners, practice nurses and health visitors working in general practices in one area of the UK NHS. The interviews were conducted with a small sample of general practitioners who had not completed the questionnaire, further exploring factors influencing their referral decisions in the local context. Results: The response rate to the questionnaire was low (19%), despite selecting the recommendation to target through engagement with local stakeholders and surveying local health professionals, and despite using two reminders, an incentive prize, and phone calls to practice managers to bolster response rates. Conclusions: Two significant challenges to achieving higher response rates and successfully exploring local context were identified: the difficulties of developing a robust- but feasible- questionnaire to explore theory-informed factors, and targeting recommendations that are important to policy makers, but which health professionals view as unimportant. This case study highlights the "trade-off" between scientifically rigorous collection of data against the pragmatism and flexibility requirements of "real world" implementation. Future implementation studies should explore different ways of identifying factors influencing the adoption of recommendations to bridge this gulf. [ABSTRACT FROM AUTHOR]