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

Dalton, Kieran; O'Mahony, Denis; Cullinan, Shane; Byrne, Stephen

Access to this article is restricted until 12 months after publication by request of the publisher.. Restriction lift date: 2021-07-17

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

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dc.check.date	2021-07-17
dc.check.info	Access to this article is restricted until 12 months after publication by request of the publisher.	en
dc.contributor.author	Dalton, Kieran
dc.contributor.author	O'Mahony, Denis
dc.contributor.author	Cullinan, Shane
dc.contributor.author	Byrne, Stephen
dc.contributor.funder	Seventh Framework Programme	en
dc.contributor.funder	Health Research Board	en
dc.date.accessioned	2020-08-12T10:03:53Z
dc.date.available	2020-08-12T10:03:53Z
dc.date.issued	2020-07-17
dc.date.updated	2020-08-12T09:49:53Z
dc.description.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.	en
dc.description.sponsorship	Heath Research Board (Study within a Trial (SWAT) award from the Heath Research Board Trials Methodology Research Network (HRB-TMRN))	en
dc.description.status	Peer reviewed	en
dc.description.version	Accepted Version	en
dc.format.mimetype	application/pdf	en
dc.identifier.citation	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	en
dc.identifier.doi	10.1007/s40266-020-00787-6	en
dc.identifier.eissn	1179-1969
dc.identifier.issn	1170-229X
dc.identifier.journaltitle	Drugs and Aging	en
dc.identifier.uri	https://hdl.handle.net/10468/10383
dc.language.iso	en	en
dc.publisher	Springer Nature Switzerland AG	en
dc.relation.project	info:eu-repo/grantAgreement/EC/FP7::SP1::HEALTH/305930/EU/Development and clinical trials of a new Software ENgine for the Assessment & Optimization of drug and non-drug Therapy in Older peRsons/SENATOR	en
dc.rights	© 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	en
dc.subject	Prescriber implementation	en
dc.subject	Medication recommendations	en
dc.title	Factors affecting prescriber implementation of computer-generated medication recommendations in the SENATOR trial: A qualitative study	en
dc.type	Article (peer-reviewed)	en