Optimizing Healthcare Operations with AI-Driven Decision Support Systems

EasyChair Preprint no. 12832

Abstract

The healthcare industry faces numerous challenges in delivering efficient and effective care, such as resource allocation, scheduling, patient flow management, and clinical decision-making. To address these challenges, healthcare organizations are increasingly turning to artificial intelligence (AI)-driven decision support systems. This abstract explores the application of AI in optimizing healthcare operations and its potential benefits.

AI-driven decision support systems leverage advanced algorithms and machine learning techniques to analyze large volumes of healthcare data, including electronic health records, medical imaging, and patient-generated data. By processing and interpreting this vast amount of information, AI systems can provide valuable insights and recommendations to healthcare professionals, enabling them to make well-informed decisions and improve operational efficiency.

One significant area where AI can optimize healthcare operations is resource allocation. Hospitals and healthcare facilities often struggle with managing their resources effectively, such as staff, equipment, and beds. AI algorithms can analyze historical data and real-time information to predict patient demand, optimize staff scheduling, and ensure the availability of essential resources. This proactive approach helps minimize bottlenecks, reduce waiting times, and enhance the overall patient experience.

Additionally, AI-driven decision support systems can enhance clinical decision-making by providing evidence-based recommendations. By analyzing patient data, including symptoms, medical history, and genetic information, AI algorithms can assist healthcare professionals in diagnosing diseases accurately and determining the most appropriate treatment plans. This technology has the potential to improve patient outcomes, reduce medical errors, and optimize treatment pathways.

Keyphrases: digital, Healthcare, science

@Booklet{EasyChair:12832,
  author = {Favour Olaoye and Kaledio Potter},
  title = {Optimizing Healthcare Operations with AI-Driven Decision Support Systems},
  howpublished = {EasyChair Preprint no. 12832},

  year = {EasyChair, 2024}}