tetano
Editor, Senior Moderator
Am J Obstet Gynecol. 2011 Jun;204(6 Suppl 1):S46-53. Epub 2011 Mar 9.
Validation of algorithm to identify American Indian/Alaska Native pregnant women at risk from pandemic H1N1 influenza.
Penman-Aguilar A, Tucker MJ, Groom AV, Reilley BA, Klepacki S, Cullen T, Gebremariam C, Redd JT.
Source
Women's Health and Fertility Branch, Division of Reproductive Health, National Center for Chronic Disease Prevention and Health Promotion, US Centers for Disease Control and Prevention, Atlanta, GA 30341, USA. APenmanAguilar@cdc.gov
Abstract
Pregnant women and American Indian and Alaska Native people are at elevated risk of severe disease and mortality from 2009 pandemic influenza A/H1N1. We validated an electronic health record-based algorithm used by Indian Health Service to identify pregnant women in near real-time surveillance of pandemic influenza A/H1N1. We randomly selected a stratified sample of 515 patients at 3 Indian Health Service-funded hospitals with varied characteristics. With comprehensive review of patients' electronic health records as the gold standard, we calculated the positive predictive value and sensitivity of the pregnancy algorithm. The sensitivity of the algorithm at individual hospitals ranged from 94.1-96.0%. Positive predictive value ranged from 94.4-98.3%. Despite differences among hospitals on key characteristics, the pregnancy algorithm performed nearly equivalently with high positive predictive value and sensitivity at all facilities. It may prove helpful for surveillance during future epidemics and for targeting interventions for pregnant women and infants.
Published by Mosby, Inc.
PMID:
21514920
[PubMed - in process]
http://www.ncbi.nlm.nih.gov/pubmed/21514920
Validation of algorithm to identify American Indian/Alaska Native pregnant women at risk from pandemic H1N1 influenza.
Penman-Aguilar A, Tucker MJ, Groom AV, Reilley BA, Klepacki S, Cullen T, Gebremariam C, Redd JT.
Source
Women's Health and Fertility Branch, Division of Reproductive Health, National Center for Chronic Disease Prevention and Health Promotion, US Centers for Disease Control and Prevention, Atlanta, GA 30341, USA. APenmanAguilar@cdc.gov
Abstract
Pregnant women and American Indian and Alaska Native people are at elevated risk of severe disease and mortality from 2009 pandemic influenza A/H1N1. We validated an electronic health record-based algorithm used by Indian Health Service to identify pregnant women in near real-time surveillance of pandemic influenza A/H1N1. We randomly selected a stratified sample of 515 patients at 3 Indian Health Service-funded hospitals with varied characteristics. With comprehensive review of patients' electronic health records as the gold standard, we calculated the positive predictive value and sensitivity of the pregnancy algorithm. The sensitivity of the algorithm at individual hospitals ranged from 94.1-96.0%. Positive predictive value ranged from 94.4-98.3%. Despite differences among hospitals on key characteristics, the pregnancy algorithm performed nearly equivalently with high positive predictive value and sensitivity at all facilities. It may prove helpful for surveillance during future epidemics and for targeting interventions for pregnant women and infants.
Published by Mosby, Inc.
PMID:
21514920
[PubMed - in process]
http://www.ncbi.nlm.nih.gov/pubmed/21514920