Drug–drug interactions (DDIs) are common and can result in patient harm. Electronic health records warn clinicians about DDIs via alerts, but the clinical decision support they provide is inadequate. Little is known about clinicians’ real-world DDI decision-making process to inform more effective alerts.

Apply cognitive task analysis techniques to determine informational cues used by clinicians to manage DDIs and identify opportunities to improve alerts.

Clinicians submitted incident forms involving DDIs, which were eligible for inclusion if there was potential for serious patient harm. For selected incidents, we met with the clinician for a 60 min interview. Each interview transcript was analysed to identify decision requirements and delineate clinicians’ decision-making process. We then performed an inductive, qualitative analysis across incidents.

Inpatient and outpatient care at a major, tertiary Veterans Affairs medical centre.

Physicians, pharmacists and nurse practitioners.

Themes to identify informational cues that clinicians used to manage DDIs.

We conducted qualitative analyses of 20 incidents. Data informed a descriptive model of clinicians’ decision-making process, consisting of four main steps: (1) detect a potential DDI; (2) DDI problem-solving, sensemaking and planning; (3) prescribing decision and (4) resolving actions. Within steps (1) and (2), we identified 19 information cues that clinicians used to manage DDIs for patients. These cues informed their subsequent decisions in steps (3) and (4). Our findings inform DDI alert recommendations to improve clinicians’ decision-making efficiency, confidence and effectiveness.

Our study provides three key contributions. Our study is the first to present an illustrative model of clinicians’ real-world decision making for managing DDIs. Second, our findings add to scientific knowledge by identifying 19 cognitive cues that clinicians rely on for DDI management in clinical practice. Third, our results provide essential, foundational knowledge to inform more robust DDI clinical decision support in the future.

Breastfeeding has health benefits for infants and mothers, yet the UK has low rates with marked social inequalities. The Assets-based feeding help Before and After birth (ABA) feasibility study demonstrated the acceptability of a proactive, assets-based, woman-centred peer support intervention, inclusive of all feeding types, to mothers, peer supporters and maternity services. The ABA-feed study aims to assess the clinical and cost-effectiveness of the ABA-feed intervention compared with usual care in first-time mothers in a full trial.

A multicentre randomised controlled trial with economic evaluation to explore clinical and cost-effectiveness, and embedded process evaluation to explore differences in implementation between sites. We aim to recruit 2730 primiparous women, regardless of feeding intention. Women will be recruited at 17 sites from antenatal clinics and various remote methods including social media and invitations from midwives and health visitors. Women will be randomised at a ratio of 1.43:1 to receive either ABA-feed intervention or usual care. A train the trainer model will be used to train local Infant Feeding Coordinators to train existing peer supporters to become ‘infant feeding helpers’ in the ABA-feed intervention. Infant feeding outcomes will be collected at 3 days, and 8, 16 and 24 weeks postbirth. The primary outcome will be any breastfeeding at 8 weeks postbirth. Secondary outcomes will include breastfeeding initiation, any and exclusive breastfeeding, formula feeding practices, anxiety, social support and healthcare utilisation. All analyses will be based on the intention-to-treat principle.

The study protocol has been approved by the East of Scotland Research Ethics Committee. Trial results will be available through open-access publication in a peer-reviewed journal and presented at relevant meetings and conferences.

ISRCTN17395671.