| CTRI Number |
CTRI/2026/04/107261 [Registered on: 01/04/2026] Trial Registered Prospectively |
| Last Modified On: |
07/04/2026 |
| Post Graduate Thesis |
No |
| Type of Trial |
Interventional |
|
Type of Study
|
Other (Specify) [Mixed Method Research] |
| Study Design |
Randomized, Parallel Group Trial |
|
Public Title of Study
|
Helping Nurses Adapt to Artificial Intelligence: A Study on AI-Assisted Patient Triage in Coimbatore Tertiary Care Hospitals
Participants: Nurses
Intervention: AI-assisted triage
Main Outcome: Adaptation of nurses to AI |
|
Scientific Title of Study
|
A Convergent Parallel Mixed-Methods Study to Assess the Effectiveness of a Machine Learning-Based Triage System on Technology Acceptance and Workflow Adaptation Among Emergency Department Nurses at a Tertiary Care Hospital in Coimbatore: A Randomized Controlled Trial. |
| Trial Acronym |
Nil |
|
Secondary IDs if Any
|
| Secondary ID |
Identifier |
| NIL |
NIL |
|
|
Details of Principal Investigator or overall Trial Coordinator (multi-center study)
|
| Name |
Baskaran M |
| Designation |
Professor |
| Affiliation |
PSG College of Nursing |
| Address |
PSG College of Nursing
Department: Mental health Nursing
Room No:02
Avinashi Road, Peelamedu,
Coimbatore
TAMIL NADU
641004
India |
| Phone |
09842418047 |
| Fax |
|
| Email |
baskirathi@gmail.com |
|
Details of Contact Person
Scientific Query
|
| Name |
Baskaran M |
| Designation |
Professor |
| Affiliation |
PSG College of Nursing |
| Address |
PSG College of Nursing
Department: Mental health Nursing
Room No:02
Avinashi Road, Peelamedu,
Coimbatore
TAMIL NADU
641004
India |
| Phone |
09842418047 |
| Fax |
|
| Email |
baskirathi@gmail.com |
|
Details of Contact Person
Public Query
|
| Name |
Baskaran M |
| Designation |
Professor |
| Affiliation |
PSG College of Nursing |
| Address |
PSG College of Nursing
Department: Mental health Nursing
Room No:02
Avinashi Road, Peelamedu,
Coimbatore
TAMIL NADU
641004
India |
| Phone |
09842418047 |
| Fax |
|
| Email |
baskirathi@gmail.com |
|
|
Source of Monetary or Material Support
|
| 1. Monetary: The Tamilnadu Dr M G R Medical University, Chennai. Research grant Rupees Four Lakhs only. Sanction order number to be filled. 2. Infrastructural: Psg College of Nursing, Coimbatore. Research infrastructure and oversight. 3. Material: Psg College of Technology, Coimbatore. Hardware, software, and technical support for artificial intelligence triage prototype. |
|
|
Primary Sponsor
|
| Name |
The Tamilnadu Dr MGR Medical University |
| Address |
69 Anna Salai, Guindy, Chennai 600032, Tamil Nadu, India |
| Type of Sponsor |
Government funding agency |
|
|
Details of Secondary Sponsor
|
| Name |
Address |
| PSG College of Technology |
Department of Biomedical Engineering, Psg College of Technology, Peelamedu, Coimbatore 641004, Tamil Nadu, India |
| PSG Institute of Medical Sciences and Research Hospitals |
Emergency Medicine Department, Psg Imsr Hospitals, Peelamedu, Coimbatore 641004, Tamil Nadu, India |
|
|
Countries of Recruitment
|
India |
|
Sites of Study
|
| No of Sites = 1 |
| Name of Principal
Investigator |
Name of Site |
Site Address |
Phone/Fax/Email |
| Dr Yamini Subramani |
PSG Hospitals |
Emergency Department
Avinashi Road, Peelamedu
Coimbatore
TAMIL NADU |
9842418047
baskirathi@gmail.com |
|
|
Details of Ethics Committee
|
| No of Ethics Committees= 1 |
| Name of Committee |
Approval Status |
| Institutional Human Ethics Committee PSG institute of medical sciences and Research centre |
Approved |
|
|
Regulatory Clearance Status from DCGI
|
|
|
Health Condition / Problems Studied
|
| Health Type |
Condition |
| Healthy Human Volunteers |
Not Applicable |
|
|
Intervention / Comparator Agent
|
| Type |
Name |
Details |
| Intervention |
Artificial Intelligence Based Triage System |
Week 1 – Structured training:
Didactic and hands-on sessions on the AI triage system, including operation of the hardware kiosk, understanding sensor-based contactless monitoring, and interpretation of the machine learning algorithm’s triage classifications.
Week 2 – Supervised use:
Nurses use the system for real or simulated patient triage under direct supervision of a trainer or principal investigator, with immediate feedback and error correction.
Weeks 3 and 4 – Independent use:
Nurses utilize the system autonomously in clinical triage settings. No direct supervision is provided, though system logs may be reviewed periodically for fidelity and safety. |
| Comparator Agent |
Standard Triage Practice |
Staff nurses in the control group perform patient triage using the existing manual triage process without access to the artificial intelligence based triage system. |
|
|
Inclusion Criteria
|
| Age From |
21.00 Year(s) |
| Age To |
50.00 Year(s) |
| Gender |
Both |
| Details |
Registered nurses working in emergency medical departments for more than six months. Direct involvement in patient triage activities. |
|
| ExclusionCriteria |
| Details |
Those with previous extensive experience with artificial intelligence based systems. Nurses planning to leave the emergency department during the study period. |
|
|
Method of Generating Random Sequence
|
Computer generated randomization |
|
Method of Concealment
|
Sequentially numbered, sealed, opaque envelopes |
|
Blinding/Masking
|
Open Label |
|
Primary Outcome
|
| Outcome |
TimePoints |
| Mean change in total score on the Trust in Artificial Intelligence Technology Scale from baseline to post-test at twelve weeks. The scale consists of five items measured on a seven point Likert scale with higher scores indicating greater trust in artificial intelligence technology. |
Baseline and at twelve weeks |
|
|
Secondary Outcome
|
| Outcome |
TimePoints |
| Mean change in total score on the Trust in Artificial Intelligence Technology Scale from baseline to post-test at twelve weeks. The scale consists of five items measured on a seven point Likert scale with higher scores indicating greater trust in artificial intelligence technology. |
Baseline and at twelve weeks |
| Mean change in total score on the Computer Self-Efficacy Scale from baseline to post-test at twelve weeks. The scale consists of five items measured on a seven point Likert scale with higher scores indicating greater confidence in using computer based systems. |
Baseline and at twelve weeks |
| Mean frequency of artificial intelligence based triage system utilization by nurses in the experimental group during the independent utilization phase measured by system access logs. Utilization frequency includes number of logins per shift and number of triage assessments performed using the system. |
Throughout the twelve week post-implementation period |
|
|
Target Sample Size
|
Total Sample Size="40"
Sample Size from India="40"
Final Enrollment numbers achieved (Total)= "Applicable only for Completed/Terminated trials"
Final Enrollment numbers achieved (India)="Applicable only for Completed/Terminated trials" |
|
Phase of Trial
|
N/A |
|
Date of First Enrollment (India)
|
21/07/2026 |
| Date of Study Completion (India) |
Applicable only for Completed/Terminated trials |
| Date of First Enrollment (Global) |
Date Missing |
| Date of Study Completion (Global) |
Applicable only for Completed/Terminated trials |
|
Estimated Duration of Trial
|
Years="3"
Months="0"
Days="0" |
|
Recruitment Status of Trial (Global)
|
Not Yet Recruiting |
| Recruitment Status of Trial (India) |
Not Yet Recruiting |
Publication Details
Modification(s)
|
N/A |
|
Individual Participant Data (IPD) Sharing Statement
|
Will individual participant data (IPD) be shared publicly (including data dictionaries)?
Response - NO
|
|
Brief Summary
|
This randomized controlled trial evaluates the effectiveness of an artificial intelligence based triage system on acceptance and adaptation among forty staff nurses in emergency departments at a tertiary care hospital in Coimbatore, India. Participants are randomly assigned to experimental group receiving artificial intelligence based triage system training and implementation or control group receiving standard triage practice. The primary outcome is change in Technology Acceptance Model Scale score from baseline to twelve weeks. Secondary outcomes include change in Adaptation to Technology Scale score and system utilization frequency. The study hypothesis is that the artificial intelligence based triage system with structured training will significantly improve acceptance and adaptation among staff nurses. |