Impact of an ambient digital scribe on typing and note quality: the AutoscriberValidate study

BackgroundTyping in the electronic health record (EHR) takes up healthcare providers time and cognitive space and constitutes a substantial administrative burden contributing to high burnout rates in healthcare. Ambient digital scribes may improve this problem. ObjectiveTo investigate the effect of the use of Autoscriber, an ambient digital scribe, on healthcare providers administrative workload and the quality of medical notes in the EHR. MethodsA study period of 26 weeks was randomized into weeks when healthcare providers were allowed to use Autoscriber (intervention weeks) and weeks when they were not (control weeks) in a 2:1 ratio. Workload was assessed by comparing the number of characters typed in the medical note during control weeks with the number of modifications that were made to the summary produced by Autoscriber during intervention weeks. Quality of the medical note was measured by having a large language model (LLM) count the number of hallucinations, incorrect negations, context conflation errors, speculations, other inaccuracies, omissions, succinctness errors, organization errors and terminology errors per medical note. ResultsBetween 1 November 2024 and 30 April 2025, 35 healthcare providers from 14 different specialties recorded 387 consultations in intervention weeks, and 142 in control weeks. The median number of characters typed per medical note was 1079 in control weeks and the median number of modifications necessary to produce the medical note was 351 in intervention weeks, compatible with a lower workload. All types of errors occurred significantly less frequently in notes made with the support of Autoscriber than in those without, except for speculations, where the difference did not reach statistical significance. ConclusionsThe use of Autoscriber resulted in a lower workload and a higher quality of the medical note.