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A Voice-Enabled Clinical Assistant for Bedside Assessment
1  Department of Medicine, Dr. V.M. Government Medical College, Solapur, 413003, India
Academic Editor: James Chow

Abstract:

Introduction: The importance of bedside assessment in clinical decision making cannot be ignored, but the volume of documentation and information that is unnoticed and sporadic may slow down timely interventions. Digital tools which are voice-enabled provide hands-free support and enable the real-time capture of data, which may increase efficiency and accuracy. This paper will consider the practicality and effectiveness of a voice-based clinical assistant system to aid bedside evaluation in general medicine wards.

Methods: The pilot study was performed in two general medicine units over the period of eight weeks. The clinicians were provided with a tablet-based voice-activated assistant to record vital signs, capture clinical impressions, access patient history, and add reminders to routine rounds. The electronic health record (EHR) was connected to the system via safe APIs. The outcomes that were measured were documentation time, completeness of assessment records, user satisfaction, and occurrence of omission of clinical tasks. There was a pre-implementation and post-implementation comparison.

Results: The voice-enabled assistant led to a 32-percent decrease in documentation time and a 28-percent rise in the completeness of the bedside assessment notes. As a result of improved workflow and reduced cognitive load, clinicians rated usability scores highly, with the mean being 4.4/5. The rate of task omission, especially follow-up vital checks and drug reminders, reduced by 21 percent. There were no data-security breaches or system-related clinical errors.

Conclusions: The voice-based clinical assistant greatly simplified the bedside operations, increased the quality of documentation, and augmented compliance with normal clinical duties. These observations indicate that voice-based applications are able to reinforce real-time clinical assistance and add to safer and more efficient inpatient care. Greater multicentre analysis should be encouraged to determine scalability and long-term effects.

Keywords: Bedside assessment; Clinical decision-making; Voice-enabled clinical assistant; Real-time data capture; Clinical workflow

 
 
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