Using Big Data Analytics for Patient Safety, Hospital Acquired Conditions

Big data analytics can provide valuable insight into avoiding patient safety events and reducing the incidence of hospital acquired conditions.

Prediction and prevention are the two main goals for patient safety experts seeking to avoid adverse events and reduce the prevalence of hospital acquired conditions (HACs). While workflow strategies, staff training, and human factors play a critical role in helping hospitals get ahead of infections, falls, pressure ulcers, and medication errors, big data analytics tools are becoming increasingly important in the age of digital care.

Author: Jennifer Bresnick

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