The Studi Transformasi Deteksi Sinyal Farmakovigilans: Dari Spontaneous Reporting System (SRS) Menuju Integrasi Artificial Intelligence (AI)
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Abstract
Adverse Drug Reactions (ADR) menjadi ancaman serius terhadap keselamatan pasien dan beban finansial sistem kesehatan global. Sistem pelaporan spontan (Spontaneous Reporting System/SRS) merupakan pendekatan tradisional utama dalam deteksi sinyal farmakovigilans, namun dibatasi oleh underreporting, keterlambatan pelaporan, dan bias pelapor. Artikel ini bertujuan untuk membandingkan pendekatan SRS dengan pendekatan berbasis Artificial Intelligence (AI) dalam mendeteksi sinyal keamanan obat. Metode yang digunakan adalah kajian naratif literatur, dengan penelusuran literatur dari database yang sesuai kriteria inklusi yaitu artikel original dan terbit pada tahun 2015-2025. Data yang diperoleh dianalisis dan disajikan secara deskriptif. Hasil studi menunjukkan bahwa pelaporan ADR masih rendah akibat hambatan sistemik, namun dapat ditingkatkan melalui pelatihan dan intervensi multifaset. Integrasi AI, seperti model LGBM, dLBM, dan aTarantula, mampu mendeteksi ADR secara otomatis dengan akurasi tinggi, bahkan dari data tidak terstruktur. Kesimpulan artikel ini bahwa pendekatan integratif antara SRS dan AI merupakan strategi optimal untuk meningkatkan efektivitas deteksi sinyal farmakovigilans di masa depan, dengan menggabungkan kekuatan data real-world dari SRS dan kemampuan analitik canggih dari AI.
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