PUBLIC RELEASE DATE: <\/p>\n
15-Jul-2014 <\/p>\n
Contact: Kathryn Ruehle kruehle@liebertpub.com<\/a> 914-740-2100 Mary Ann Liebert, Inc.\/Genetic Engineering News<\/p>\n New Rochelle, NY, July 15, 2014A 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, a peer-reviewed journal published by Mary Ann Liebert, Inc., publishers. 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<\/a> until August 15, 2014. <\/p>\n 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. <\/p>\n 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.\" <\/p>\n \"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.\" <\/p>\n ### <\/p>\n About the Journal <\/p>\n AIDS Research and Human Retroviruses is published monthly in print and online. The Journal presents papers, reviews, and case studies documenting the latest developments and research advances in the molecular biology of HIV and SIV and innovative approaches to HIV vaccine and therapeutic drug research, including the development of antiretroviral agents and immune-restorative therapies. The content also explores the molecular and cellular basis of HIV pathogenesis and HIV\/HTLV epidemiology. The Journal features rapid publication of emerging sequence information and reports on clinical trials of emerging HIV therapies. Tables of content and a sample issue may be viewed on the AIDS Research and Human Retroviruses website at http:\/\/www.liebertpub.com\/aid<\/a>. <\/p>\n <\/p>\n Link: PUBLIC RELEASE DATE: 15-Jul-2014 Contact: Kathryn Ruehle kruehle@liebertpub.com<\/a> 914-740-2100 Mary Ann Liebert, Inc.\/Genetic Engineering News New Rochelle, NY, July 15, 2014A 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, a peer-reviewed journal published by Mary Ann Liebert, Inc., publishers. 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<\/a> until August 15, 2014. Providing medical care early on to people with newly diagnosed HIV infection is important for improving clinical outcomes. Continue reading
\nIdentifying newly diagnosed HIV-infected people using electronic medical records<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"