<p>In the era of digitalization, the use of data analytics in healthcare has become a major facilitator of improved patient care, operational efficiency, and evidence-based clinical decision-making. The aim of this review article is to provide an overview of healthcare data analytics, particularly for healthcare practitioners, clinicians, and medical administrators across various specialties, who may not have a formal background in data science who plan to collaborate with digital technologies more precisely, big data analytics and data science. It provides an introduction to the theoretical and practical concepts in healthcare data analytics, outlining its benefits, associated challenges, adoption strategies, and practical applications of data analytics and artificial intelligence (AI) in medicine. The review highlights how advanced analytical techniques such as predictive modelling, machine learning, and AI are revolutionising healthcare delivery by enabling pre-emptive interventions and personalized treatment plans. Lastly, the article identifies promising areas of research in medical data analytics, and it outlines how emerging technologies can be used to enhance treatment outcomes, evidence-based decision-making, and the delivery of quality healthcare services.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Introduction to health care data analytics- an overview

  • Amanuel Worku,
  • Fetlework Gubena Arage,
  • Fentahun Bikale Kebede

摘要

In the era of digitalization, the use of data analytics in healthcare has become a major facilitator of improved patient care, operational efficiency, and evidence-based clinical decision-making. The aim of this review article is to provide an overview of healthcare data analytics, particularly for healthcare practitioners, clinicians, and medical administrators across various specialties, who may not have a formal background in data science who plan to collaborate with digital technologies more precisely, big data analytics and data science. It provides an introduction to the theoretical and practical concepts in healthcare data analytics, outlining its benefits, associated challenges, adoption strategies, and practical applications of data analytics and artificial intelligence (AI) in medicine. The review highlights how advanced analytical techniques such as predictive modelling, machine learning, and AI are revolutionising healthcare delivery by enabling pre-emptive interventions and personalized treatment plans. Lastly, the article identifies promising areas of research in medical data analytics, and it outlines how emerging technologies can be used to enhance treatment outcomes, evidence-based decision-making, and the delivery of quality healthcare services.