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All Journal International Journal of Public Health Science (IJPHS) Jurnal NERS Health Notions Jurnal Kesehatan Prima Jurnal Pengabdian Masyarakat Kesehatan JURNAL PENELITIAN KESEHATAN JAIM (Jurnal Abdi Masyarakat) Jurnal Keperawatan Frontiers in Community Service and Empowerment Darussalam: Journal of Psychology and Educational Jurnal Keperawatan (e-Journal) Research Psychologie, Orientation et Conseil Journal of World Future Medicine, Health and Nursing
Setyorini, Dhiana
Poltekkes Kemenkes Surabaya
Humanities Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Medicine & Pharmacology Nursing Public Health Social Sciences Other

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AI-ASSISTED DIAGNOSTICS IN NURSING PRACTICE: IMPACT ON PATIENT ASSESSMENT AND CARE Dhiana Setyorini; Rini Ambarwati; Minarti Minarti; Nur Hasanah
Journal of World Future Medicine, Health and Nursing Vol. 4 No. 1 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v4i1.3367

Abstract

The rapid integration of artificial intelligence (AI) into healthcare has transformed clinical decision-making processes, including patient assessment and diagnostic support. In nursing practice, accurate and timely assessment is critical to patient safety and quality of care, yet increasing workload and clinical complexity often challenge nurses’ diagnostic performance. This study aims to examine the impact of AI-assisted diagnostic tools on nursing assessment accuracy, efficiency, and overall patient care outcomes. The research employs a mixed-methods design combining quantitative analysis of assessment performance indicators with qualitative exploration of nurses’ experiences in clinical settings where AI diagnostics are implemented. Data were collected from registered nurses across selected hospital units using standardized assessment records, questionnaires, and semi-structured interviews. The results indicate that AI-assisted diagnostics significantly improve assessment accuracy, reduce time to clinical decision-making, enhance early detection of patient deterioration, and increase nurses’ confidence in clinical judgment. Qualitative findings reveal that nurses perceive AI tools as supportive systems that augment, rather than replace, professional expertise when appropriately integrated into workflows. The study concludes that AI-assisted diagnostics represent a valuable advancement in nursing practice by strengthening patient assessment and promoting safer, more consistent care.  
Co-Authors Adelita Setiawan Adivtian Ragayasa Ariefa Quinta Hanum Arnes Yuli Vandika Benny Novico Zani Buka, Sisilia Prima Yanuaria Cahyono, Intim Chyono, Intim Della Afrianti Dessy Arna, Yessy Dina Rasmita Ekayani, Ni Putu Karunia Eko Winarti Elvin Elsa Maharenny Emdat Suprayitno Enung Mardiyana Heryyanoor, Heryyanoor Hidayati, Ratna Huda, Moch. Maftuchul I Made Sutarna Indrayani, Siska Indriatie Jenie Palupi Joko Suwito Khofifah Nuril Fauziyah Khrisna Agung Cendekiawan Luthfiyah, Sari MINARTI Minarti Minarti Minarti Minarti Moch. Bahrudin Nur Anugrahini, Hepta Nur Hasanah Padoli . Rasmita, Dina Restanty, Dian Aby Rini Ambarwati Sofwan Ashari Sopiatun, Rita Syiska Atik Maryanti Wahyu Sri Astutik Yudied Agung Mirasa Zani, Benny Novico