Author(s):
Bunnasorn Techajumlernsuk, Lawan Sratthaphut, Samart Jamrat
Email(s):
jamrat_S@su.ac.th
DOI:
10.52711/0974-360X.2026.00560 
Address:
Bunnasorn Techajumlernsuk1,2, Lawan Sratthaphut3,4, Samart Jamrat3,4*
1Program of Health Informatics, Division of Digital Health, Faculty of Pharmacy, Silpakorn University, Nakhon Pathom, 73000, Thailand.
2Department of Social and Administrative Pharmacy Department, Faculty of Pharmacy, Srinakharinwirot University, Nakhon Nayok, 26120, Thailand.
3Artificial Intelligent and Metabolomics Research Group, Faculty of Pharmacy, Silpakorn University, Nakhon Pathom, 73000, Thailand.
4Division of Digital Health, Faculty of Pharmacy, Silpakorn University, Nakhon Pathom, 73000, Thailand.
*Corresponding Author
Published In:
Volume - 19,
Issue - 9,
Year - 2026
ABSTRACT:
Optimizing Rational Drug Use (RDU) is essential in community pharmacy practice. To improve RDU prescribing and optimize medication decision-making, this study develops a clinical decision support tool to assist community pharmacists in symptom analysis and medication recommendations following Thailand's RDU policy. The system integrates real-time symptom analysis, symptom-disease matching, and disease-drug treatment recommendations based on Thailand RDU guidelines for community pharmacies in drug store by utilizing a database design and low-code platform. The interface was designed with User Experience (UX) principles to ensure accessibility and ease of use. The system database includes 481 symptoms, 200 disease profiles, and 315 drug lists. Fifteen case studies were conducted to evaluate system performance, yielding a precision score of 1, a recall score of 0.84, and an F1-score of 0.92, demonstrating reliable drug-disease matching. The findings indicate that the system supports pharmacists in symptom assessment, disease identification, and rational drug use recommendations. This study highlights the potential for a patient-centered digital health tool that enhances community pharmacy services, reduces the risk of medication errors, and improves pharmaceutical care quality.
Cite this article:
Bunnasorn Techajumlernsuk, Lawan Sratthaphut, Samart Jamrat. The Development of Clinical decision support system for Symptom Analysis and Rational Drug Use Recommendations for Community Pharmacy. Research Journal Pharmacy and Technology. 2026;19(9):3993-9. doi: 10.52711/0974-360X.2026.00560
Cite(Electronic):
Bunnasorn Techajumlernsuk, Lawan Sratthaphut, Samart Jamrat. The Development of Clinical decision support system for Symptom Analysis and Rational Drug Use Recommendations for Community Pharmacy. Research Journal Pharmacy and Technology. 2026;19(9):3993-9. doi: 10.52711/0974-360X.2026.00560 Available on: https://rjptonline.org/AbstractView.aspx?PID=2026-19-9-6
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