Abstract
This participatory action research addresses the growing challenges in caring for
patients with non-communicable diseases (NCDs), including increasing patient numbers,
complications, and disease complexity, alongside rising healthcare costs. The study involved
collaboration between a multidisciplinary research team comprising doctors, mathematicians,
engineers, and information scientists, and a healthcare team including physicians, nurses,
pharmacists, dietitians, computer technicians, and village health volunteers.
Previously, healthcare providers recorded diagnosis and treatment information in
patients' personal booklets, which then had to be transferred to computer systems, resulting
in redundant work. Patients often faced issues such as forgetting or losing their booklets,
incomplete records, or illegible handwriting, leading to discontinuity of information and
communication problems between hospitals.
To address these issues, the research team developed an artificial intelligence (AI)
technology in the form of an application. The study was conducted in five pilot hospitals in
Nakhon Ratchasima province: 1 ) Suranaree University of Technology Hospital, 2) Pak Chong
Nana Hospital, 3) Non Sung Hospital, 4) Sikhio Hospital, and 5) Chakkarat Hospital
After identifying challenges in NCD patient care, such as high workload, complex and
redundant processes, lack of data connectivity between service units, increasing patient
complications and clinical risks, and limited use of telemedicine, the team developed an NCD
patient care service system called "A.I. Jai Dee" (A.I. Kind Heart) application. This system
reduces unnecessary steps, enhances value-added processes in patient care, and incorporates
beneficial features for patients, including: 1. A support system to increase knowledge and
skills for proper self-care and health management 2. A self-monitoring system for patients'
health status and data 3. An automatic notification system and telemedicine consultation
with medical professionals 4. A data processing system for disease trajectory prediction and
complication risk assessment 5. A system to enhance medical personnel's knowledge and
skills in utilizing AI for medical benefits
This innovative approach aims to improve NCD patient care efficiency, reduce
complications, and optimize healthcare resource utilization. The results from using the
Application show that accumulated blood sugar improved by 45.45%, remained the same or
stable at 3.33%, and worsened by 21.21%. It was found that the accumulated blood sugar
improved when HbA1c decreased from 12.8 to 8.7 and from 10.5 to 5.7, which is a significant
reduction. This technology may help and support the healthcare providers to empower and
improve the patient’s self-care.
