| CTRI Number |
CTRI/2025/06/089576 [Registered on: 25/06/2025] Trial Registered Prospectively |
| Last Modified On: |
22/06/2025 |
| Post Graduate Thesis |
Yes |
| Type of Trial |
Observational |
|
Type of Study
|
Cohort Study |
| Study Design |
Other |
|
Public Title of Study
|
Enhancing AI tools for smarter symptom analysis in healthcare: A real-world validation study |
|
Scientific Title of Study
|
Optimisation of an AI based clinical decision support system of symptom analysis in clinical settings
A prospective validation study |
| Trial Acronym |
NIL |
|
Secondary IDs if Any
|
| Secondary ID |
Identifier |
| NIL |
NIL |
|
|
Details of Principal Investigator or overall Trial Coordinator (multi-center study)
|
| Name |
Mudita Khattri |
| Designation |
Junior Resident, Department of General Medicine, AIIMS Rishikesh |
| Affiliation |
AIIMS Rishikesh |
| Address |
Room no 16409, 6th Floor, Department of General Medicine, AIIMS Rishikesh
Dehradun
UTTARANCHAL
249203
India
Dehradun
UTTARANCHAL
249203
India |
| Phone |
9836888382 |
| Fax |
|
| Email |
khattrimudi@gmail.com |
|
Details of Contact Person
Scientific Query
|
| Name |
Dr Prasan Kumar Panda |
| Designation |
Additional Professor, Department of General Medicine, AIIMS Rishikesh |
| Affiliation |
AIIMS Rishikesh |
| Address |
Room no 16409, 6th Floor, Department of General Medicine, AIIMS Rishikesh
Dehradun
Uttaranchal
249203
India
Dehradun
UTTARANCHAL
249203
India |
| Phone |
9868999488 |
| Fax |
|
| Email |
prasan.med@aiimsrishikesh.edu.in |
|
Details of Contact Person
Public Query
|
| Name |
Dr Prasan Kumar Panda |
| Designation |
Additional Professor, Department of General Medicine, AIIMS Rishikesh |
| Affiliation |
AIIMS Rishikesh |
| Address |
Room no 16409, 6th Floor, Department of General Medicine, AIIMS Rishikesh
Dehradun
Uttaranchal
249203
India
Dehradun
UTTARANCHAL
249203
India |
| Phone |
9868999488 |
| Fax |
|
| Email |
prasan.med@aiimsrishikesh.edu.in |
|
|
Source of Monetary or Material Support
|
| Department of General Medicine, AIIMS Rishikesh
Dehradun
UTTARANCHAL
249203
India |
|
|
Primary Sponsor
|
| Name |
AIIMS RISHIKESH |
| Address |
Room no 16409, 6th Floor, Department of General Medicine, AIIMS Rishikesh
Dehradun
Uttaranchal |
| Type of Sponsor |
Other [SELF] |
|
|
Details of Secondary Sponsor
|
| Name |
Address |
| SELF |
PG Hostel, Hostel no 86, AIIMS
Virbhadra Road, Rishikesh, Uttaranchal
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 Mudita Khattri |
AIIMS RISHIKESH |
Room no16409, 6th Floor, Department of General Medicine, AIIMS Rishikesh
Dehradun
Uttaranchal
Dehradun
UTTARANCHAL |
9836888382
khattrimudi@gmail.com |
|
|
Details of Ethics Committee
|
| No of Ethics Committees= 1 |
| Name of Committee |
Approval Status |
| All India Institute of Medical Sciences, Rishikesh, Institutional Ethics Committee |
Approved |
|
|
Regulatory Clearance Status from DCGI
|
|
|
Health Condition / Problems Studied
|
| Health Type |
Condition |
| Patients |
(1) ICD-10 Condition: R00-R99||Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified, |
|
|
Intervention / Comparator Agent
|
| Type |
Name |
Details |
| Intervention |
Nil |
Nil |
| Comparator Agent |
NIL |
NIL |
|
|
Inclusion Criteria
|
| Age From |
18.00 Year(s) |
| Age To |
69.00 Year(s) |
| Gender |
Both |
| Details |
1. OPD and IPD patients under MEDICINE DEPARTMENT of AIIMS RISHIKESH.
2. Patients who give consent to participate in the study.
|
|
| ExclusionCriteria |
| Details |
1. Incomplete Data: Cases where data collection is incomplete or compromised leading to gaps in the required information for analysis
2. Patients whose visited MEDICINE department for investigation purpose example medical certificate.
3. Patients whose clinical conditions not eligible for evaluation by the Medicine Department referral cases.
|
|
|
Method of Generating Random Sequence
|
Not Applicable |
|
Method of Concealment
|
Not Applicable |
|
Blinding/Masking
|
Not Applicable |
|
Primary Outcome
|
| Outcome |
TimePoints |
| 1. To validate existing Data-based CDSS symptom repository in OPD and IPD settings by evaluating clinicians real time feedback on the symptom checklist |
Total duration of Study is 18 months divided in 12 months of Data collection phase and 3 months each for data analysis and data re implementation and analysis phase. |
|
|
Secondary Outcome
|
| Outcome |
TimePoints |
1. To predict clinical diagnosis as per expert recommendation.
2. To implement the optimized AI-solution in national portal e-Sanjeevani.
3. To predict department recommendations as per symptom analysis.
|
Total duration of Study is 18 months divided in 12 months of Data collection phase and 3 months each for data analysis and data re implementation and analysis phase. |
|
|
Target Sample Size
|
Total Sample Size="5000"
Sample Size from India="5000"
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)
|
15/07/2025 |
| 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="1"
Months="6"
Days="0" |
|
Recruitment Status of Trial (Global)
|
Not Applicable |
| Recruitment Status of Trial (India) |
Not Yet Recruiting |
|
Publication Details
|
N/A |
|
Individual Participant Data (IPD) Sharing Statement
|
Will individual participant data (IPD) be shared publicly (including data dictionaries)?
Response - NO
|
|
Brief Summary
|
This study aims to validate
the symptom repository and identify the strengths and limitations of the CDSS,
offering insights that can enhance its diagnostic accuracy, functionality and
acceptance among healthcare professionals The AI based clinical decision support system
(CDSS) in symptom analysis will demonstrate a statistically significant
improvement in clinical decision-making accuracy in real-world clinical
settings compared to conventional decision-making processes |