RT Journal Article
SR Electronic
T1 How might dynamic artificial intelligence (DynAIRx) be used to support prescribing to ensure efficient medication reviews?
JF The Annals of Family Medicine
JO Ann Fam Med
FD American Academy of Family Physicians
SP 4823
DO 10.1370/afm.22.s1.4823
VO 21
IS Supplement 3
A1 Abuzour, Aseel
A1 Wilson, Samantha
A1 Woodall, Alan
A1 Mair, Frances
A1 Bollegala, Danushka
A1 Cant, Harriet
A1 Gabbay, Mark
A1 Hama, Layik
A1 Leeming, Gary
A1 Maskell, Simon
A1 O’Connell, Maurice
A1 Popoola, Olusegun
A1 Relton, Samuel
A1 Shantsila, Eduard
A1 Sperrin, Matthew
A1 Buchan, Iain
A1 Walker, Lauren
YR 2023
UL http://www.annfammed.org/content/21/Supplement_3/4823.abstract
AB Context: The DynAIRx project aims to develop artificial intelligence (AI) tools to support medication reviews for patients with multimorbidity (people with ≥2 chronic conditions), targeting those at greatest risk of medicine-related harm. Challenges faced by healthcare professionals (HCPs) managing multimorbid patients include poor integration of health records across providers and few tools to assist in stratifying patients requiring medication reviews.Objective: To explore how medication reviews are currently being undertaken and how they might be augmented by AI.Study design and analysis: 5 semistructured interviews and 6 focus groups with HCPs (n=26); 2 focus groups with patients (n=10). These were transcribed verbatim and analysed using inductive thematic analysis.Setting: England. Focus groups were conducted via MicroSoft Teams with pharmacists, general practitioners, secondary care clinicians, and policy makers. Patient focus groups were conducted face-to-face.Population studied: The DynAIRx tool will target potentially problematic polypharmacy in 3 key multimorbidity groups: people with mental and physical health problems; those with ≥4 chronic conditions or taking ≥10 drugs; and older patients with frailty.Outcome measures: Report on barriers and facilitators to effective medicine reviews and potential implications for the implementation of new decision support tools.Results: Availability of staff, access to patient information, organisational contracts and patient demographics influenced uptake of medication reviews. Time was a major limiting factor due to the overwhelming density of information in electronic health records, especially for complex patients. Building continuity in medication reviews and adopting a team-based approach to dealing with complex multimorbid patients was emphasised. HCPs welcomed user-friendly digital tools with an intuitive interface that could be used to reduce “detective work” and enable shared decision making with patients. A timeline including diagnoses linked to medicines by indications and previous investigations was viewed as an early potential solution to reduce laborious searching. HCPs were generally positive about using AI tools to aid risk stratification of patients needing medication reviews but emphasised ease of use as important.Conclusions: These findings and those of an observational time-and-motion study will inform development of the DynAIRx prototype. HCPs seem receptive to such a tool.