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Decision-Making based on Big Data Analytics for People Management in Healthcare Organizations
Maria José Sousa1, António Miguel Pesqueira2, Carlos Lemos3
1ISCTE-Instituto Universitário de Lisboa, Lisbon, Portugal. mjdcsousa@gmail.com.
Journal of Medical Systems
|July 24, 2019
Summary
Big data analytics improves healthcare decision-making by integrating large datasets. This enhances efficiency and supports leaders with predictive models and real-time insights for better people management.
Area of Science:
- Health Informatics
- Data Science in Healthcare
- Healthcare Management
Background:
- Healthcare organizations generate vast amounts of data.
- Effective data utilization is crucial for operational efficiency and strategic decision-making.
- Current challenges exist in integrating and analyzing large datasets for management purposes.
Purpose of the Study:
- To examine big data analytics' role in healthcare decision-making.
- To identify key big data analytics supporting healthcare leaders.
- To propose strategies for enhancing efficiency across the healthcare value chain.
Main Methods:
- Systematic literature review.
- Analysis of big data applications in healthcare.
- Development of a predictive model for people management.
Main Results:
- Big data analytics significantly enhances the efficiency of the decision-making process.
- Predictive models and real-time analytics are key tools for healthcare leaders.
- Integration of data collection, management, and analysis is vital.
Conclusions:
- Big data analytics is essential for optimizing healthcare operations.
- Implementing predictive models can lead to improved people management.
- Strategic use of big data analytics drives efficiency and cost-effectiveness in healthcare organizations.
Keywords:
AnalyticsBig dataBusiness intelligence; Prisma methodologyDecision-makingHealthcare organizationsLeadersOutcomesMore Related Videos
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