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Impact of AI-Enabled Telemedicine Service on Patient Outcomes

Students & Supervisors

Student Authors
Sudipto Kumar Chakrabarty
Bachelor of Science in Computer Science & Engineering, FST
Arnob Debnath
Bachelor of Science in Computer Science & Engineering, FST
Susmita Mitra
Bachelor of Science in Computer Science & Engineering, FST
Supervisors
Md. Mortuza Ahmmed
Associate Professor, Faculty, FST

Abstract

Background: Many people still struggle to get the right treatment at the right time, even with advancements in medical care. Telemedicine gives a solution to this problem, for example, video contact between doctors and patients, and also many alternative health apps. However, traditional Telemedicine services face some limitations. Integration of AI in telemedicine opens a new horizon that overcomes the limitations in traditional telemedicine, like report analysis, diagnosis, and tracking health records. So this study aims to examine the last 24 (2000-20024) years to find out how patient satisfaction, treatment accuracy, and follow-up rates are changed as a result of the gradual integration of AI in Telemedicine. Methods: A time series dataset spanning 2000-2024 was constructed using secondary data collected from reputable sources, including the American Psychological Association, JMIR Formative Research, American Medical Informatics Association, ICT Division(Government of Bangladesh). This dataset gives the information on the Patient Satisfaction Score, AI Integration Level, and Telemedicine Adoption Rate. Thus, from 2000 to 2024, the data set was merged to examine the pattern of how telemedicine and AI affect patient outcomes. Results: The findings indicate that during AI advanced Integration (2020-2024), patients' satisfaction score averages around 88 compared to an average of around 57 initially during the AI integration (2000-2008). This calculation indicates an improvement of around 55%. Similarly treatment accuracy improves from 64 % to 90%, an increase of around 40%. Conclusion: This study demonstrates that AI-enabled telemedicine significantly positive impact on patient outcomes. The findings reflect the potential outcomes of integrating advanced AI tools in telemedicine services to enhance healthcare, especially in remote areas.

Keywords

AI Telemedicine AI Integration in Telemedicine Time Series Analysis

Publication Details

  • Type of Publication: Conference 
  • Conference Name: 1st National BioMed Health ResearchCon (NBHRC) 2025
  • Date of Conference: 28/08/2025 - 28/08/2025
  • Venue: Dr. Milon Auditorium, Dhaka Medical College
  • Organizer: Dhaka Medical College Research and Academic Club
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