Abstract
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.
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Acknowledgements
The authors wish to thank all the interviewees who kindly agreed to participate in this study. In addition, the authors would like to acknowledge the SENATOR research teams at each of the six trial sites who facilitated the conduct of this study. Finally, the authors thank Jessica Coyne for her contribution to this work.
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Ethical Approval
Ethical approval for this study was granted by the Clinical Research Ethics Committee of the Cork Teaching Hospitals, Cork, Ireland. As well as this, local ethical approval was also granted at each RCT site where English was not the first language of participants (sites 3–6 in Table 1), with participant information sheets and consent forms also translated into the participants’ native language.
Funding
This qualitative study received funding from the SENATOR project, which was supported by the European Commission’s Seventh Framework Programme FP7/2007-2013 under Grant agreement number 305930. Kieran Dalton and Denis O’Mahony received funding for their normal roles within the SENATOR project, but no extra funding was received for their work on this qualitative study. The Commission had no part in the design of this study, the collection, analysis and interpretation of the data, the writing of the report, or the decision to submit the article for publication. This research was also supported by funding from a Study within a Trial (SWAT) award from the Heath Research Board Trials Methodology Research Network (HRB-TMRN).
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Dalton, K., O’Mahony, D., Cullinan, S. et al. Factors Affecting Prescriber Implementation of Computer-Generated Medication Recommendations in the SENATOR Trial: A Qualitative Study. Drugs Aging 37, 703–713 (2020). https://doi.org/10.1007/s40266-020-00787-6
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DOI: https://doi.org/10.1007/s40266-020-00787-6