ECEESPE2025 ePoster Presentations Metabolism, Nutrition and Obesity (164 abstracts)
1Prayas Diabetes Center, Diabetes and Obesity, Indore, India; 2Kewalya Hospital, Thane, India; 3Samarpan Clinic, Omerga, India
JOINT3938
Aim: This study aims to evaluate the impact of Mitraa, an AI-based chatbot, on patient care, focusing on its effectiveness in improving medication adherence, patient engagement, and reducing unnecessary clinic visits.
Materials and Methods: A pilot study was conducted involving 100 patients with chronic conditions. Participants were provided access to Mitraa, which offers personalized, real-time health support, including medical information, medication reminders, lifestyle recommendations, and continuous monitoring. The chatbot leverages natural language processing (NLP) and machine learning algorithms to adapt to individual patient needs. Data on medication adherence, patient engagement, satisfaction, and clinic visit frequency were collected over a three-month period.
Results: Mitraa demonstrated significant improvements in patient outcomes. Medication adherence rates increased by 35%, and patient engagement rose by 40% during the study period. Additionally, 85% of users reported higher satisfaction with their healthcare experience, attributing this to Mitraas accessibility and personalized guidance. The chatbot also contributed to a 25% reduction in unnecessary clinic visits, alleviating the burden on healthcare facilities.
Conclusion: Mitraa effectively enhances patient care by providing continuous, personalized support and bridging the gap between healthcare providers and patients. The observed improvements in adherence, engagement, and patient satisfaction highlight the chatbots potential to foster proactive, patient-centered care. By reducing the strain on clinical resources and empowering patients to manage their health, Mitraa contributes to more efficient healthcare delivery and healthier communities.