Use of an ambient artificial intelligence tool to improve quality of clinical documentation

• Published in: Future Healthcare Journal
• Main Authors: Jasmine Balloch, Shankar Sridharan, Geralyn Oldham, Jo Wray, Paul Gough, Robert Robinson, Neil J. Sebire, Saleh Khalil, Elham Asgari, Christopher Tan, Andrew Taylor, Dominic Pimenta
• Format: Article
• Language: English
• Published: Elsevier 2024-09-01
• Subjects: Artificial intelligence; Ambient; Consultation; Clinical documentation; Electronic health records
• Online Access: http://www.sciencedirect.com/science/article/pii/S2514664524015479

Background: Electronic health records (EHRs) have contributed to increased workloads for clinicians. Ambient artificial intelligence (AI) tools offer potential solutions, aiming to streamline clinical documentation and alleviate cognitive strain on healthcare providers. Objective: To assess the clinical utility of an ambient AI tool in enhancing consultation experience and the completion of clinical documentation. Methods: Outpatient consultations were simulated with actors and clinicians, comparing the AI tool against standard EHR practices. Documentation was assessed by the Sheffield Assessment Instrument for Letters (SAIL). Clinician experience was measured through questionnaires and the NASA Task Load Index. Results: AI-produced documentation achieved higher SAIL scores, with consultations 26.3% shorter on average, without impacting patient interaction time. Clinicians reported an enhanced experience and reduced task load. Conclusions: The AI tool significantly improved documentation quality and operational efficiency in simulated consultations. Clinicians recognised its potential to improve note-taking processes, indicating promise for integration into healthcare practices.