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Would they trust it? An exploration of psychosocial and environmental factors affecting prescriber acceptance of computerised dose‐recommendation software
Author(s) -
Carland Jane E.,
Elhage Tania,
Baysari Melissa T.,
Stocker Sophie L.,
Marriott Deborah J.E.,
Taylor Natalie,
Day Richard O.
Publication year - 2021
Publication title -
british journal of clinical pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.216
H-Index - 146
eISSN - 1365-2125
pISSN - 0306-5251
DOI - 10.1111/bcp.14496
Subject(s) - psychosocial , software , medicine , workload , intervention (counseling) , medical education , psychology , computer science , nursing , psychiatry , programming language , operating system
Aims Dose‐prediction software can optimise vancomycin therapy, improving therapeutic drug monitoring processes and reducing drug toxicity. Success of software in hospitals may be dependent on prescriber uptake of software recommendations. This study aimed to identify the perceived psychosocial and environmental barriers and facilitators to prescriber acceptance of dose‐prediction software. Methods Semi‐structured interviews, incorporating prescribing scenarios, were undertaken with 17 prescribers. Participants were asked to prescribe the next maintenance dose of vancomycin for a scenario(s) and then asked if they would accept a recommendation provided by a dose‐prediction software. Interviews further explored opinions of dose‐prediction software. Interview transcripts were analysed using an inductive approach to identify themes and the Theoretical Domains Framework was used to synthesise barriers and facilitators to software acceptance. Results When presented with software recommendations, half of the participants were comfortable with accepting the recommendation. Key barriers to acceptance of software recommendations aligned with 2 Theoretical Domains Framework domains: Knowledge (uncertainty of software capability) and Beliefs about Consequences (perceived impact of software on clinical outcomes and workload). Key facilitators aligned with 2 domains: Beliefs about Consequences (improved efficiency) and Social Influences (influence of peers). A novel domain, Trust, was identified as influential. Conclusion Prescribers reported barriers to acceptance of dose‐prediction software aligned with limited understanding of, and scepticism about, software capabilities, as well as concerns about clinical outcomes. Identification of key barriers and facilitators to acceptance provides essential information to design of implementation strategies to support the introduction of this intervention into the workplace.