A new, validated software-based method for identifying patients with newly diagnosed HIV using electronic medical records (EMRs) is described in AIDS Research and Human Retroviruses.
Providing medical care early on to people with newly diagnosed HIV infection is important for improving clinical outcomes. Study authors Matthew Bidwell Goetz and Tuyen Hoang, VA Greater Los Angeles Healthcare System and David Geffen School of Medicine, UCLA; Virginia Kan, Washington DC VA Medical Center and George Washington University School of Medicine; David Rimland, Atlanta VA Medical Center and Emory University School of Medicine; and Maria Rodriguez-Barradas, Michael E. DeBakey VA Medical Center and Baylor University School of Medicine, Houston, TX, developed an algorithm designed to search EMRs to identify patients with new diagnoses of HIV infection based on the sequence of HIV diagnostic testing, diagnostic code entries into the EMR, and measurements of HIV genetic material in blood samples. They tested and validated their software tool using EMRs from patients undergoing HIV testing from 2006-2012 at four large Veterans Health Administration facilities.
The authors report the sensitivity, specificity, and predictive value of the algorithm in the article "Development and Validation of an Algorithm to Identify Patients Newly Diagnosed with HIV Infection from Electronic Health Records."
"This paper describes new and valuable methodologies that will enhance the ability of public health officials to monitor increases in newly infected HIV populations," says Thomas Hope, PhD, Editor-in-Chief of AIDS Research and Human Retroviruses and Professor of Cell and Molecular Biology at the Feinberg School of Medicine, Northwestern University, Chicago, IL. "This will help to determine where healthcare resources for HIV-positive patients and testing for highest risk patients could be utilized more effectively. This will surely aid in facilitating the fight against HIV/AIDS."
More information: The article is available free on the AIDS Research and Human Retroviruses website at http://online.liebertpub.com/doi/full/10.1089/aid.2013.0287 until August 15, 2014