Tech & Health Archive — Page 15 of 21
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November 4, 2020
Study tracks physician use of electronic health records
According to a new large-scale descriptive study in the journal Pediatrics, for each outpatient encounter, pediatricians on average spend 16 minutes using the electronic health record (EHR). -
October 29, 2020
Telementoring project aims to improve access for adults with autism
A team at Vanderbilt University Medical Center and Vanderbilt Kennedy Center is launching a program to improve access to primary care for adults with autism. -
October 29, 2020
New tool rapidly identifies health records for studies
Electronic health records (EHR) are increasingly a resource for biomedical discovery, and automated searches for records that reflect a phenotype of interest, typically a disease, are a common starting point. -
September 21, 2020
Throwing weight around on the internet
What users mention in online weight loss forum tracks with how much weight they lose. -
September 17, 2020
Stead to step down from Chief Strategy Officer role after decades of remarkable contributions
Visionary — someone who thinks about the future or advancements in a creative and imaginative way, a person who is ahead of her or his time and who has a powerful plan for change in the future. Such a person is William “Bill” Stead, MD, Vanderbilt University Medical Center’s Chief Strategy Officer, McKesson Foundation Professor of Biomedical Informatics and Professor of Medicine. -
September 17, 2020
Center for Genetic Privacy lands major grant renewal
The National Human Genome Research Institute (NHGRI) has awarded a four-year, $4 million grant renewal to Vanderbilt University Medical Center’s Center for Genetic Privacy and Identity in Community Settings (GetPreCiSe). -
August 27, 2020
Study uses AI to sort patient messages by complexity
Taking an interest in electronic message threads between surgical patients and their health care teams, a research group at Vanderbilt University Medical Center has tested how well certain commonly used machine learning algorithms can classify such exchanges according to their clinical decision-making complexity.