xRead - Incorporating Artificial Intelligence into Clinical Practice (March 2026)

Ng et al. BMC Medical Informatics and Decision Making

(2025) 25:236

Page 17 of 24

Key Findings Novel Features

This study establishes a hybrid method that simultaneously generates and

evaluates a digital scribe and electronic prescription for diabetes.

The study’s developed system provides the option to review and edit the system generated scribes and prescriptions, reducing the chance of error..

Measured outcomes using AMA Organiza tional Biopsy EHR-specific survey

Reported significant reduction in burnout among physicians, with burnout rates decreasing from 69–43%.

Study achieved a 92% survey completion rate, indicating strong engagement and

usability of ambient AI technology among participants, supporting its potential for broader implementation in healthcare settings.

Voice-driven intelligent system for generating medical scribes and pre

scriptions, demonstrating ease of use and proven viability; employed both extractive and abstractive summari zation, selecting an LSTM model for higher accuracy over traditional NLP approaches.

Clinicians using AI documenta tion tools experienced lower

frustration and less time spent on documentation.

Significant reduction in burnout as measured by the Stanford Professional Fulfillment Index (PFI); achieved by

reducing the burden of documenta tion and cognitive load required of clinicians during a consultation

AI Transcription

Proficiency (paper

specific outcomes)

NR NR Mean ratings for

scribe (mean ± SD): 4.33 ± 0.022

Number of attempts for performing the

assigned tasks for all

patients (mean ± SD): 1.285 ± 0.034 Task Completion

Time for performing the assigned tasks

for all patients (mean minutes ± SD): 2.28 ± 0.51

Number of asked help for performing the

assigned tasks for all

patients: 0.283 ± 0.024 Overall satisfaction (out of 5): 4.67

Easiness to use (out of 5): 4.22

Easiness to learn (out of 5): 4.27

Recommend to Oth ers (out of 5): 4.75

Time in documen tation, frustration levels NR Decreased documen tation time, frustra

tion, and after-hours EHR use

NR 4.16 (pre), 3.16 (post)* 5.0 (pre), 4.2 (post)

3.6 (pre), 2.5 (post)*

6.1 (pre), 6.5 (post)

Metric (F1 score,

Precision, Recall, WER)

Burnout score

(Stanford Profes

sional Fulfillment Index)

Work exhaustion score

Interpersonal dis

engagement score Professional fulfillment

Comparator Type Subcategories Performance Non-blinded comparison

Pre-intervention ver

sus post-intervention

NR Pre and

post-intervention

Standard

Handwritten scribe

Clinician

survey on EHR experience

Table 2 (continued)

Study Reference Islam et

al., 2024 [26]

Liu et

al., 2024 [27]

Misurac et al.,

2024

[28]