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Integrating Artificial Intelligence Into International Classification of Functioning, Disability, and Health Coding: Effectiveness of a Mobile Application for Patient Questionnaires

NCT07021781 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 185

Last updated 2025-06-15

No results posted yet for this study

Summary

Mobile applications and artificial intelligence are increasingly integrated into medical practice, yet their impact on workflow optimization and diagnostic accuracy remains understudied. This study evaluates the effectiveness of the MedQuest mobile application in optimizing patient questionnaire processes and assesses the accuracy of AI-driven International Classification of Functioning, Disability and Health (ICF) coding in comparison to traditional clinician-based coding.

Conditions

  • ICF
  • Rehabilitation
  • Artifical Intelligence
  • Application

Interventions

OTHER

MedQuest mobile application

Participants in this group will complete standardized questionnaires and scales using the MedQuest mobile application. Physicians will provide patients with a QR code, allowing them to access assigned digital questionnaires on their personal mobile devices or provided tablets. The application facilitates the digital input of patient responses. Following completion, the MedQuest application automatically processes the questionnaire data and utilizes an integrated artificial intelligence system (Claude 3.5 Sonnet, version from 22.10.2024) to generate recommended International Classification of Functioning, Disability and Health (ICF) codes. The application also provides an integrated calculator for questionnaire scores. This intervention aims to streamline the assessment process, reduce completion time, and enhance the efficiency and accuracy of ICF coding through AI integration.

OTHER

Traditional Paper-Based Questionnaires

Participants in this group will complete all standardized questionnaires and scales (e.g. SF-36, Barthel Index, etc.) manually on printed paper forms. Physicians will complete the forms and patients will complete their responses with a pen or pencil. Subsequent evaluation and processing of these questionnaires will be performed by physicians via the Medquest application, followed by manual identification and recording of International Classification of Functioning, Disability, and Health (ICF) codes based on clinical judgment and established guidelines. This method represents the traditional approach to patient assessment and data collection.

Sponsors & Collaborators

  • Tulip Medicine

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-11-25
Primary Completion
2025-02-26
Completion
2025-02-26

Countries

  • Kazakhstan

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07021781 on ClinicalTrials.gov