An overview of Business Intelligence research in healthcare organizations using a topic modeling approach

The intersection of Business intelligence (BI) and data analytics with healthcare has witnessed remarkable growth in recent decades. With the aim of identifying the most attentive themes, topics, and research priorities, this review endeavors to perform a literature analysis on research articles add...

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Bibliographic Details
Main Authors: Mehraeen, Mohammad, Mahmoudi, Laya, Sharifi, Mohammad Hossein
Format: Conference Proceeding
Language:English
Subjects:
Big Data
Business intelligence
Costs
Decision making
Healthcare organizations
Medical services
Natural language processing
Object recognition
Text mining
Topic Modeling
Online Access:Request full text
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Summary:The intersection of Business intelligence (BI) and data analytics with healthcare has witnessed remarkable growth in recent decades. With the aim of identifying the most attentive themes, topics, and research priorities, this review endeavors to perform a literature analysis on research articles addressing business intelligence in healthcare. To conduct the study, a total of 751 articles, published between 2002 and 2023, were analyzed through topic modeling, a technique used in natural language processing (NLP) and machine learning. As a result, seven major themes were identified: Unique Device Identification, Big Data and Data Analytics, Operational Efficiency, Effective Decision-Making, Healthcare Delivery Optimization, Resource Optimization and Cost Reduction, and Nosocomial Infections are growing. The analysis revealed that there is a growing interest in leveraging business intelligence for infection control and operational improvements using health information technology and data analytics, while efforts to optimize resources/reduce costs appear to be on the decline. The research findings shed light on the increasing capabilities and use of business intelligence in healthcare, highlighting opportunities for future research.
ISSN:2643-279X
DOI:10.1109/ICCKE60553.2023.10326258