Economic Impact, Clinical Outcomes, and Implementation Challenges of Artificial Intelligence Solutions in Cardiac Care: A Systematic Literature Review

  • سال انتشار: 1404
  • محل انتشار: InfoScience Trends، دوره: 2، شماره: 5
  • کد COI اختصاصی: JR_ISJTREND-2-5_003
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 30
دانلود فایل این مقاله

نویسندگان

Amin Zaki Zadeh

Internal Medicine Department, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.

Elnaz Olama

Faculty of Medicine, Georgian National University SEU, Tbilisi ۰۱۶۶, Georgia.

Milad Vosoughi

Department of Internal Medicine, Hamadan University of Medical Sciences, Hamadan, Iran.

Amiryousef Zahedi

Internal Medicine Department at Caucasus Medical Centre (Tbilisi), Tbilisi, Georgia.

Akram Soltanzadeh

Faculty of Medicine, Kurdistan University of Medical Sciences, Kurdistan, Iran

Mohammad hossein Mirjani

Faculty of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.

Iman Fereydooni

Department of Internal Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.

چکیده

Artificial intelligence (AI) is transforming cardiac care by enhancing diagnosis, risk stratification, and patient monitoring. This systematic review synthesizes evidence from ۱۴ studies (۲۰۲۰–۲۰۲۵) on the economic impact, clinical outcomes, and implementation challenges of AI in cardiology. Findings demonstrate that AI-driven interventions—including machine learning-guided atrial fibrillation screening, AI-enhanced cardiac imaging, and remote monitoring—improve disease detection rates and reduce adverse events (e.g., strokes, hospitalizations) while proving cost-effective. For instance, targeted AI screening identified ۲۷–۴۵% more atrial fibrillation cases versus standard care, with incremental cost-effectiveness ratios favoring AI adoption. However, real-world implementation faces barriers such as electronic health record integration costs, clinician adoption resistance, and workflow disruptions. Facilitators like phased rollouts, embedded decision support tools, and real-world performance tracking mitigated these challenges. Methodological limitations include study heterogeneity, reliance on model-based economic analyses, and underreporting of long-term implementation costs. The review highlights a critical gap between AI's theoretical benefits and its practical deployment, emphasizing the need for pragmatic trials, standardized outcome reporting, and stakeholder collaboration. By addressing these challenges, AI can realize its potential to enhance cardiac care efficiency and patient outcomes.

کلیدواژه ها

Artificial intelligence, Cardiac Care, Cost-Effectiveness, clinical outcomes

اطلاعات بیشتر در مورد COI

COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.

کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.