The role of AI in enhancing electronic health records: Automation, insights and predictive analytics

The addition of Artificial Intelligence drives fundamental transformation within Electronic Health Records which leads to data-centric operating systems in healthcare facilities. AI integration with EHR systems focuses on three essential achievement goals including automation and the generation of insights and predictive analytics capabilities. The automation of data operations through artificial intelligence technology enhances both system performance speed and prevents human errors in data handling. AI uses extensive datasets to help medical practitioners make treatment decisions through analytical insights which additionally enables forecasting of patient health conditions.. The document examines multiple case studies and research presenting evidence about how artificial Intelligence affects Electronic Health Record functionality enhancements. Primary research demonstrates how healthcare delivery experienced enhanced outcomes while healthcare staff reduced workload needs and data remained more accurate. The upgraded management system encounters technical difficulties regarding security of collected data and complicated system connections. The basis of research about AI's impact in healthcare derives primarily from various case studies along with data assessments and surveys which collectively demonstrate AI's complete potential in healthcare systems.

Authors

Publication Details

Journal
Global Journal of Engineering and Technology Advances
Published
2024-09-30
DOI
https://doi.org/10.30574/gjeta.2024.20.3.0161
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

The role of AI in enhancing electronic health records: Automation, insights and predictive analytics

Znu Zartashea
Global Journal of Engineering and Technology Advances
Machine Learning in Healthcare
article

The role of AI in enhancing electronic health records: Automation, insights and predictive analytics

Znu Zartashea
article en

Abstract

The addition of Artificial Intelligence drives fundamental transformation within Electronic Health Records which leads to data-centric operating systems in healthcare facilities. AI integration with EHR systems focuses on three essential achievement goals including automation and the generation of insights and predictive analytics capabilities. The automation of data operations through artificial intelligence technology enhances both system performance speed and prevents human errors in data handling. AI uses extensive datasets to help medical practitioners make treatment decisions through analytical insights which additionally enables forecasting of patient health conditions.. The document examines multiple case studies and research presenting evidence about how artificial Intelligence affects Electronic Health Record functionality enhancements. Primary research demonstrates how healthcare delivery experienced enhanced outcomes while healthcare staff reduced workload needs and data remained more accurate. The upgraded management system encounters technical difficulties regarding security of collected data and complicated system connections. The basis of research about AI's impact in healthcare derives primarily from various case studies along with data assessments and surveys which collectively demonstrate AI's complete potential in healthcare systems.

Global Journal of Engineering and Technology AdvancesVol. 20(3)
Openalex Percentile: Top 74%
Machine Learning in Healthcare
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