electronic health records (EHRs)

Stanford, Essentia Health join VUMC-based clinical research network

The STAR Clinical Research Network, based at Vanderbilt University Medical Center (VUMC), has added two new partners — Essentia Health, a Minnesota-based rural health care system, and Stanford University School of Medicine, one of the country’s leading academic medical centers.

Team uses COVID-19 to test automated acute disease profiling

An automated solution for creating phenotyping algorithms, PheNorm, worked well to identify symptomatic COVID-19 cases in electronic health records, suggesting that automation could speed high-throughput phenotyping of acute disease.

Study validates use of VUMC suicide risk model in Navy primary care

A Vanderbilt study found that automated suicide risk prediction models operating on electronic health records could help clinical teams efficiently identify patients for face-to-face suicide risk screening and prevention.

Bryan Shepherd’s research to validate EHR data receives MERIT Award from the NIH

Vanderbilt’s Bryan Shepherd, PhDhas received a MERIT Award, or Method to Extend Research in Time Award, from the National Institute of Allergy and Infectious Diseases.

The study team from VUMC included, from left, Xinmeng Zhang, You Chen, PhD, Bradley Malin, PhD, and Chao Yan, PhD. On the computers are Northwestern Medicine colleagues Abel Kho, MD, and Yuyang Yang. (photo by Donn Jones)

Study tracks clinical team engagement with health records by patient race/ethnicity

A review of electronic health record user access logs found that EHRs of adult inpatients from minority racial and ethnic populations on average received lower engagement from health care teams than the records of white adult inpatients.

Algorithm scours health records for lung cancer risk

Vanderbilt researchers have developed a computer algorithm that scans electronic health records, or EHRs, to identify patients who meet criteria for lung cancer screening.

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