Electronic health records can help catch undiagnosed cases of Type 2 diabetes, UCLA researchers find

In 2012, a group of UCLA researchers set out to mine thousands of electronic health records for a more accurate and less expensive way to identify people who have undiagnosed Type 2 diabetes. The researchers got much more than they bargained for. Not only did they develop an algorithm with the potential to vastly increase the number of correct diagnoses of the disease by refining the pool of candidates who are put forward for screening; they also uncovered several previously unknown risk factors for diabetes, including a history of sexual and gender identity disorders, intestinal infections and a category of illnesses that includes such sexually transmitted diseases as chlamydia. The findings appear February 16 in the Journal of Biomedical Informatics. “With widespread implementation, these discoveries have the potential to dramatically decrease the number of undetected cases of Type 2 diabetes, prevent complications from the disease and save lives,” said Ariana Anderson, the study’s lead author and an assistant research professor and statistician at UCLA’s Semel Institute for Neuroscience and Human Behavior.  Anderson and Mark Cohen, a Semel Institute professor in residence, led a team that examined electronic records for 9,948 people from hospitals, clinics and doctor’s offices in all 50 states. Although the patients themselves were not identifiable, the records included their vital signs, prescription medications and reported ailments, categorized according t...
Source: UCLA Newsroom: Health Sciences - Category: Universities & Medical Training Source Type: news