• Dipeeka Kamble
• Dipak Kalaskar
• Anuradha Kathe
• Tejas Javare

This study was focused on establishing an AI-enhanced Electronic Medical Record (EMR) system intended to address some of the limitations present in traditional healthcare record management. Existing EMRs often allow health data to be captured directly in an electronic format; however, many possess very few intelligent capabilities that could reduce administrative burdens and improve patient experiences. Our system is a secure, role-specific platform used by physicians, patients, pharmacists, laboratory staff, and administrators via a web-based interface. It is built on PHP (Laravel/CodeIgniter) and MySQL with a modern front end (HTML, CSS, JavaScript), and its main distinguishing feature is the use of an OpenAI GPT-3.5-powered chatbot to assist in appointment scheduling, prescription management, inquiry about lab tests, and general medical queries. The platform allows several role-relevant functions, such as updating medical history, managing consultations, uploading lab results, and tracking health analytics assessments. Real-time processing of data and stringent role-based access control guarantee operational efficiency while adhering to data privacy regulations. The implementation has shown enhanced record management efficiency, reduction in patient waiting time, and streamlining of clinical procedures. With the AI chatbot being able to perform about 70% of routine inquiries from patients, this has drastically reduced the workload of healthcare staff. This fully integrated solution endows modern healthcare with secure data management, timely service delivery, and enhanced capabilities for patient interaction—representing a significant milestone in intelligent healthcare information systems.

EMR system, AI chatbot, healthcare automation, eClinicalWorks, medical records, patient management, Medication Management, Predictive Analytics.

"AI enabled Electronic Medical Records (EMR) System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.c367-c377, May-2025, Available :http://www.jetir.org/papers/JETIR2505245.pdf

"AI enabled Electronic Medical Records (EMR) System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppc367-c377, May-2025, Available at : http://www.jetir.org/papers/JETIR2505245.pdf