Projection of participant recruitment to primary care research: a qualitative study.

backgroundRecruitment to clinical trials remains a challenge, particularly in primary care settings. Initial projections of participant recruitment need to be as accurate as possible in order to avoid the financial, clinical and ethical costs of trial extensions or failures. However, estimation of recruitment rates is challenging and often poorly executed, if attempted at all. We used qualitative methods to explore the experiences and views of researchers on the planning of recruitment in this setting.

methodsParticipants had registered accrual to a UK-based primary care research study between April 2009 and March 2012. We conducted nine interviews with chief investigators or study managers, using a semi-structured topic guide. Analysis was conducted using the framework approach.

resultsThree themes are presented: 1) the factors affecting recruitment rates, 2) the use of planning techniques, and 3) influences on poor estimation. 1) A large number of factors affecting recruitment rates were discussed, including those relating to the study protocol, the clinical setting and the research setting. Use of targeted mail-outs to invite apparently eligible individuals to participate was preferred in order to eliminate some of the uncertainty in the recruitment rate associated with opportunistic clinician referrals. 2) The importance of pilot work was stressed. We identified significant uncertainty as to how best to schedule trial timelines to maximise efficiency. 3) Several potential sources of bias involved in the estimation of recruitment rates were explored and framed as technological, psychological or political factors.

conclusionsWe found a large number of factors that interviewees felt impact recruitment rates to primary care research and highlighted the complexity of realistic estimation. Suitable early planning of the recruitment process is essential, and there may be potential to improve the projection of trial timelines by reducing biases involved in the process. Further research is needed to develop formal approaches that would be suitable for use in this setting.