Factors affecting prescriber implementation of computer-generated medication recommendations in the SENATOR trial: A qualitative study

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Dalton, Kieran
O'Mahony, Denis
Cullinan, Shane
Byrne, Stephen
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Springer Nature Switzerland AG
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Background: The SENATOR trial intervention included the provision of computer-generated medication recommendations to physician prescribers caring for hospitalised older adults (≥ 65 years), with the aim of reducing in-hospital adverse drug reactions. Interim data analysis during the trial revealed that the prescriber implementation rates of the computer-generated STOPP/START recommendations were lower than expected across all six trial sites. Aim: The aim of this qualitative study was to identify the factors affecting prescriber implementation of the medication recommendations in the SENATOR trial. Methods: Semi-structured interviews were conducted with trial researchers and physician prescribers who were provided with SENATOR recommendations. Content analysis was used to identify the most relevant domains from the Theoretical Domains Framework (TDF) that affected recommendation uptake. Results: Ten trial researchers and fourteen prescribers were interviewed across the six trial sites. Eight TDF domains were found to be most relevant in affecting prescriber implementation: ‘environmental context and resources’, ‘goals’, ‘intentions’, ‘knowledge’, ‘beliefs about consequences’, ‘memory, attention and decision processes’, ‘social/professional role and identity’, and ‘social influences’. Interviewees felt that there was often a disconnect between the time prescribers were reviewing the patient and the point at which the recommendations were provided. However, when recommendations were reviewed, prescriber inertia was highly pervasive, with a particular reluctance to make pharmacotherapy changes outside their own specialty. Implementation was facilitated by recommendations reaching a ‘decision-maker’, but this was often not possible as the software could not evaluate the entire clinical context of patients, and thus frequently produced recommendations of low clinical relevance. Conclusion: This study has demonstrated that the clinical relevance of the SENATOR prescribing recommendations was a significant factor affecting their implementation. Whilst software refinement will be necessary to improve the quality of recommendations, future interventions will need to be multifaceted to overcome the complex prescriber specialty culture within the acute hospital environment.
Prescriber implementation , Medication recommendations
Dalton, K., O'Mahony, D., Cullinan, S. and Byrne, S. (2020) 'Factors affecting prescriber implementation of computer-generated medication recommendations in the SENATOR trial: A qualitative study', Drugs and Aging. doi: 10.1007/s40266-020-00787-6
© 2020, Springer Nature Switzerland AG. This is a post-peer-review, pre-copyedit version of an article published in Drugs and Aging. The final authenticated version is available online at: http://dx.doi.org/10.1007/s40266-020-00787-6