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10.1080/09540121.2014.911813 http://scihub22266oqcxt.onion/10.1080/09540121.2014.911813 C4095997!4095997!24779521     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\24779521.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       AIDS+Care 2014 ; 26 (10): 1318-25 Nephropedia Template TP {{tp|p=24779521|t=2014. Development of an electronic medical record-based algorithm to identify patients with unknown HIV status |pdf=|usr=}}{{24779521}} gab.com Text Development of an electronic medical record-based algorithm to identify patients with unknown HIV status JO: AIDS Care http://www.kidney.de/pget.php?&tw=1&pmid=24779521 #FOAvip Individuals with unknown HIV status are at risk for undiagnosed HIV, but practical and reliable methods for identifying these individuals have not been described. We developed an algorithm to identify patients with unknown HIV status using data from the electronic medical record (EMR) of a large healthcare system. We developed EMR-based criteria to classify patients as having known status (HIV-positive or HIV-negative) or unknown status and applied these criteria to all patients seen in the affiliated healthcare system from 2008?2012. Performance characteristics of the algorithm for identifying patients with unknown HIV status were calculated by comparing a random sample of the algorithm?s results to a reference standard medical record review. The algorithm classifies all patients as having either known or unknown HIV status. Its sensitivity and specificity for identifying patients with unknown status are 99.4% (95% CI: 96.5%?100%) and 95.2% (95% CI: 83.8%?99.4%), respectively; with positive and negative predictive values of 98.7% (95% CI: 95.5%?99.8%) and 97.6% (95% CI: 87.1%?99.1%), respectively. Using commonly available data from an EMR, our algorithm has high sensitivity and specificity for identifying patients with unknown HIV status. This algorithm may inform expanded HIV testing strategies aiming to test the untested. Twit Text FOAVip Development of an electronic medical record-based algorithm to identify patients with unknown HIV status ????AIDS Care http://www.kidney.de/pget.php?&tw=1&pmid=24779521 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=24779521 #FOAvip English Wikipedia <ref>{{Cite pmid|24779521}}</ref> Development of an electronic medical record-based algorithm to identify patients with unknown HIV status #MMPMID24779521 Felsen UR; Bellin EY; Cunningham CO; Zingman BS AIDS Care 2014[Oct]; 26 (10): 1318-25 PMID24779521show ga Individuals with unknown HIV status are at risk for undiagnosed HIV, but practical and reliable methods for identifying these individuals have not been described. We developed an algorithm to identify patients with unknown HIV status using data from the electronic medical record (EMR) of a large healthcare system. We developed EMR-based criteria to classify patients as having known status (HIV-positive or HIV-negative) or unknown status and applied these criteria to all patients seen in the affiliated healthcare system from 2008?2012. Performance characteristics of the algorithm for identifying patients with unknown HIV status were calculated by comparing a random sample of the algorithm?s results to a reference standard medical record review. The algorithm classifies all patients as having either known or unknown HIV status. Its sensitivity and specificity for identifying patients with unknown status are 99.4% (95% CI: 96.5%?100%) and 95.2% (95% CI: 83.8%?99.4%), respectively; with positive and negative predictive values of 98.7% (95% CI: 95.5%?99.8%) and 97.6% (95% CI: 87.1%?99.1%), respectively. Using commonly available data from an EMR, our algorithm has high sensitivity and specificity for identifying patients with unknown HIV status. This algorithm may inform expanded HIV testing strategies aiming to test the untested. äDevelopment of an electronic medical record-based algorithm to identif(epmc).pdf DeepDyve Pubget Overpricing