Enterprise AI Analysis: Healthcare
Streamlining Tobacco Cessation with AI: A Protocol for Enhanced Patient Outcomes
This study protocol outlines the development and efficacy testing of eDOSTHI, an AI-enabled mobile application designed to provide accessible and culturally adapted support for tobacco cessation. Targeting a significant public health challenge, the platform aims to empower patients with tailored interventions and continuous guidance, addressing critical gaps in current treatment availability, particularly in low-income settings. The robust trial design ensures a comprehensive evaluation of its impact on abstinence rates and overall patient well-being.
Key Impact for Healthcare Enterprises
The eDOSTHI platform offers a scalable solution for healthcare providers to significantly improve tobacco cessation outcomes, enhance patient engagement, and optimize resource allocation.
0%
Reduction in Relapse Rates
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Patients in Intervention Arm
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Languages Supported (Initial)
0 Weeks
Follow-up Assessment Period
Deep Analysis & Enterprise Applications
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eDOSTHI
AI-Enabled Treatment Package for Tobacco Cessation
Impact: A role-based, cross-platform application developed in English and Bengali to enhance reach and ease of treatment. It leverages AI for personalized support and guidance.
Enterprise Process Flow
Web-Browser & Mobile App Development
→
Rule-Based Decision Support System
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Interactive Chat Interface (MI & CBT Principles)
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Daily Consumption Tracking
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Weekly/Biweekly Intensive Interaction
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Fortnightly/Monthly Booster Interactions
Trial Design Comparison
| Feature | Active Arm (eDOSTHI) | Placebo Arm |
|---|---|---|
| Intervention Type |
|
|
| Sample Size | 220 patients | 220 patients |
| Assessments | Baseline, 4 weeks, 24 weeks (FTND, QSU, PHQ-4, GAD-7, Urinary Cotinine, Breath CO) | Baseline, 4 weeks, 24 weeks (FTND, QSU, PHQ-4, GAD-7, Urinary Cotinine, Breath CO) |
CTRI/2025/09/094053
Clinical Trial Registration Number
Significance: The study is officially registered, ensuring transparency and adherence to ethical guidelines for randomized controlled trials in India.
Case Study: Personalized Support in Action
A patient struggling with tobacco dependence downloads the eDOSTHI app. After initial assessment, the AI chatbot initiates weekly interactive sessions focused on managing cravings using CBT techniques and preventing relapse through motivational interviewing. The app provides personalized reminders for nicotine replacement therapy and directs the patient to local health care facilities and quitline numbers, ensuring comprehensive support throughout their cessation journey.
220
Patients Engaged in RCT Intervention
Impact: Large-scale engagement in a randomized controlled trial will provide robust evidence for the efficacy and acceptability of AI-enabled tobacco cessation interventions in diverse populations.
Calculate Your Potential ROI with AI
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Estimated Annual Savings
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Annual Hours Reclaimed
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Implementation Roadmap
A structured approach to integrating eDOSTHI within your healthcare system, from development to full efficacy testing.
Phase 1: Software Development & Prototype (8-9 Months)
Design and develop the eDOSTHI server and mobile application (Android) with expert input from psychiatrists and clinicians. Deployment at AIIMS Kalyani and initial testing with 8-10 volunteers.
Phase 2: Pilot Testing (Quantitative & Qualitative)
Test acceptability and feasibility on 220 tobacco users (18-65 years) using convenience sampling. Includes 4-week telephonic/face-to-face follow-ups, FGDs, and IDIs with stakeholders to identify facilitators/barriers for refinement.
Phase 3: Efficacy Testing & Prediction Model (36 Months Total)
Conduct a Randomized Controlled Trial (RCT) with 440 patients (220 intervention, 220 control) assessing outcomes at baseline, 4, and 24 weeks. Develop a supervised machine learning model to predict smoking cessation outcomes using collected patient data.
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