Data-driven decision making in patient management: a systematic review
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View abstract on PubMed
Summary
This summary is machine-generated.Data-Driven Decision Making (DDDM) enhances patient management through AI and decision support systems. While challenges exist, DDDM offers personalized care and streamlines healthcare decisions.
Area Of Science
- Healthcare Technology
- Medical Informatics
- Health Services Research
Background
- Data-Driven Decision Making (DDDM) is crucial for effective patient management in healthcare.
- Understanding the technologies and frameworks of DDDM in patient care is essential.
Purpose Of The Study
- To comprehensively review technologies used in DDDM for patient management.
- To establish a framework illustrating DDDM's role in patient management.
Main Methods
- Systematic review following PRISMA-P guidelines.
- Screening of studies from Web of Science, PubMed, and Embase.
- Application of specific inclusion criteria for patient management studies utilizing DDDM.
Main Results
- AI and other methods dominate data-driven approaches in patient management.
- Decision support systems, Markov decision processes, and shared decision-making are key methods.
- Applications span disease diagnosis, treatment, precision medicine, patient care, and nursing.
Conclusions
- DDDM offers significant advantages including personalization and streamlined decision-making.
- Challenges like data quality and interpretability need addressing for optimal implementation.
- DDDM is vital for patient management and broader healthcare system improvements.
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