Identifikasi Potensi Efek Samping Obat Pada Resep Pasien Rawat Jalan dengan Menggunakan Open AI (ChatGPT)
DOI:
https://doi.org/10.63004/hrji.v4i5.1303Kata Kunci:
chatgpt, efek samping obat, identifikasi, kecerdasan buatan, open aiAbstrak
Efek samping obat (ESO) merupakan tantangan penting dalam pelayanan farmasi klinis, terutama pada pasien rawat jalan. Identifikasi dini ESO diperlukan untuk meningkatkan keamanan terapi. Penelitian ini bertujuan mengetahui profil pasien, mengidentifikasi potensi ESO, serta mengevaluasi akurasi ChatGPT dalam mendeteksi dan menganalisis ESO. Desain penelitian deskriptif dilakukan dengan pendekatan kuantitatif retrospektif menggunakan 351 resep pasien rawat jalan di Klinik Cahaya Madani pada bulan Januari–Maret 2025. Penelitian dilaksanakan di Klinik Cahaya Madani pada bulan Juli–September 2025. Analisis dilakukan dengan menggunakan ChatGPT, yang kemudian divalidasi dengan menggunakan Drugs.com, MIMS.com, dan brosur obat, kemudian dievaluasi dengan confusion matrix. Mayoritas pasien adalah perempuan (53,8%) dengan usia dewasa (39,6%), dan resep didominasi obat jadi (85,8%). Potensi ESO terbanyak adalah gangguan gastrointestinal (63,8%), sedasi (63,0%), dan reaksi alergi (32,8%). Hasil evaluasi menunjukkan akurasi 92,85%, presisi 92,85%, recall 100%, dan F1-score 96,29%. ChatGPT terbukti efektif mendeteksi ESO, namun tetap memerlukan validasi klinis dari tenaga kesehatan profesional.
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