EHR Usability

Artificial Intelligence System Predicts Postoperative Complications

March 21, 2023 - Recent research published in JAMA Network Open found that an artificial intelligence (AI) system known as MySurgeryRisk used EHR data and input features to predict postoperative complications successfully. Predicting postoperative complications is extremely valuable in informing clinical decision-making during surgical procedures. These predictions...


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Using a Patient-Reported Outcome Tool to Make EHR Data Actionable

by Shania Kennedy

EHRs play a critical role in guiding care coordination and delivery, but interoperability challenges can prevent EHR data from being used effectively to improve patient care. Addressing these issues is a major focus for healthcare...

New Initiative Combines Nursing Expertise, AI to Create Prediction Model

by Shania Kennedy

Columbia University Irving Medical Center (CUIMC) is leading a multi-hospital effort known as the CONCERN (COmmunicating Narrative Concerns Entered by RNs) Initiative, which aims to utilize...

Machine Learning, Whole Genome Sequencing Detect Disease Outbreaks

by Erin McNemar, MPA

University of Pittsburg School of Medicine and Carnegie Mellon University researchers are using machine learning and whole-genome sequencing to improve the detection of infectious disease...

How Teamwork Fuels Award Winning Health Information Management

by Jessica Kent

At the core of any meaningful healthcare intervention is medical data. A patient’s health history, prescription information, and demographic data are the building blocks of quality care delivery,...

Hard Stops in EHRs, Clinical Decision Support Can Improve Care

by Jennifer Bresnick

Clinical decision support systems that use hard stops, in which a response is required before a user can move forward with a task, are associated with higher performance on both process and outcomes...

Are Universal EHRs Key to Healthcare Value, Trust, and AI Adoption?

by Jennifer Bresnick

Healthcare providers in the United States generally don’t harbor very warm feelings for their electronic health records (EHRs). Despite efforts from vendors and regulators to improve the...

Using Big Data Analytics for Patient Safety, Hospital Acquired Conditions

by Jennifer Bresnick

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...

Understanding the Basics of Clinical Decision Support Systems

by Jennifer Bresnick

Clinical decision support systems are quickly becoming essential tools for healthcare providers as the volume of available data increases alongside their responsibility to deliver value-based care. Reducing clinical variation and...