The problem with the problem list
Apr. 10, 2023—Algorithms to infer missing problems and suggest that they be added to electronic health records improved problem list completeness, with benefits for clinical care, patient comprehension of health conditions and population health.
Machine learning predicts delirium
Jan. 23, 2023—Using machine learning based on electronic health records of ICU patients predicted new-onset delirium with 82% sensitivity, Vanderbilt researchers found.
PheWAS reveals post-COVID-19 diagnoses
Sep. 8, 2022—Using a high-throughput informatics technique and electronic health records, Vanderbilt researchers found that COVID-19 survivors had an increased risk for more than 40 new diagnoses.
Impact of digital health interventions
Jan. 31, 2022—Vanderbilt researchers test and recommend statistical approaches to study the association between engagement with digital health interventions and clinical outcomes.
AI predicts 24-hour hospital discharge
Nov. 16, 2021—Vanderbilt researchers used a machine learning algorithm and data from more than 26,000 hospital stays to predict who would and would not be discharged over the next 24 hours.
Strength in numbers
May. 3, 2021—Voluntary data sharing across a region’s health systems and ambulatory care practices is important for measuring and improving health care quality and safety, Vanderbilt researchers report.
Gregor Mendel would be proud
Dec. 12, 2019—A computational method that uses hospital billing codes and electronic health records can identify genetic disease cases before clinical teams do.
How to fake a medical record
Nov. 4, 2019—Simulated electronic health records could avoid patient privacy risks and help speed discovery.