Effect of Ambient Voice Technology, Natural Language Processing, and Artificial Intelligence on the Patient–Physician Relationship

Abstract

Background: The method of documentation during a clinical encounter may affect the patient-physician relationship. Objectives: Evaluate how the use of ambient voice recognition, coupled with natural language processing and artificial intelligence (DAX™) affects the patient-physician relationship is not known. Methods: A prospective observational study within a community teaching health system. The primary aim was evaluating any difference on the PDQR-9 scale between primary care encounters in which DAX™ was utilized for documentation as compared to those that did not. A signal arm open-label phase was also performed to query direct feedback from patients. Results: A total of 288 patients were include in the open-label arm and 304 patients were included in the masked phase of the study comparing encounters with and without DAX™ use. In the open label phase patients strongly agreed that the provider was more focused on them, spent less time typing and made the encounter feel more personable. In the masked phase of the study no difference was seen in the rank order of the total PDQR-9 score between patients whose encounters used DAX™ (median 45 [IQR 8]) and those which did not (median 45 [IQR 3.5]; p=0.31). The adjusted odds ratio for DAX™ use was 0.8 (95% CI 0.48-1.34) for the patient reporting complete satisfaction on how well their clinician listened to them during their encounter. Conclusion: Patients strongly agreed with the use of ambient voice recognition, coupled with natural language processing and artificial intelligence (DAX™) for documentation in primary care. However, no difference was detected in the patient-physician relationship on the PDQR-9 scale.