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Hospital electronic medical record–based public health surveillance system deployed during the 2002 Winter Olympic Games
Background Several computer biosurveillance systems are in place to detect events of public health (PH) significance; however, most lack access to timely and detailed patient-level data and investigation of alerts places a strain on PH resources. Methods Hospital-based infection control professional...
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Published in: | American journal of infection control 2007-04, Vol.35 (3), p.163-171 |
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creator | Gundlapalli, Adi V., MD, PhD Olson, Jonathan, BS Smith, Sean P., BS Baza, Michael, BS Hausam, Robert R., MD Eutropius, Louise J., RN, BSN, CIC Pestotnik, Stanley L., MS, RPh Duncan, Karen, RN, MSN Staggers, Nancy, PhD, RN, FAAN Pincetl, Pierre, MD Samore, Matthew H., MD |
description | Background Several computer biosurveillance systems are in place to detect events of public health (PH) significance; however, most lack access to timely and detailed patient-level data and investigation of alerts places a strain on PH resources. Methods Hospital-based infection control professionals led a multi-disciplinary team to develop a computer rule–based system that relies on the patient's electronic medical record. The rules operated on HL7 messages transmitted by clinical computing systems and encompassed a variety of types of patient-level data, including laboratory test ordering and results, radiology ordering and reports, emergency room and outpatient clinic visits, and hospital admissions. Laboratory data were mapped to standard vocabularies, and radiology data were processed using natural language–processing algorithms before the rules were applied to filter for events of PH interest. For each rule, statistical process controls were applied to generate alerts when levels exceeded two standard deviations above the mean. The system was deployed at a large hospital in Salt Lake City during the 2002 Winter Olympic Games, and it was accessed 3 times a day to perform surveillance. Daily reports were provided to local PH agencies after preliminary investigation of the alerts. Results Of the 24 rules monitored, 9 generated alerts on 11 different occasions. The only significant event of PH interest that was noted during the surveillance period was an increase in influenza during the Games. The positive predictive value of the rules varied with a high value (89%) noted for identification of pneumonia from chest radiograph reports by natural language–processing algorithms. Conclusions With the assistance of a novel computer-based surveillance system linked to the electronic medical record that uses objective, quantifiable events and access to patient data, infection control practitioners could play a front-line role in biosurveillance and facilitate bidirectional communication with PH agencies. |
doi_str_mv | 10.1016/j.ajic.2006.08.003 |
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Methods Hospital-based infection control professionals led a multi-disciplinary team to develop a computer rule–based system that relies on the patient's electronic medical record. The rules operated on HL7 messages transmitted by clinical computing systems and encompassed a variety of types of patient-level data, including laboratory test ordering and results, radiology ordering and reports, emergency room and outpatient clinic visits, and hospital admissions. Laboratory data were mapped to standard vocabularies, and radiology data were processed using natural language–processing algorithms before the rules were applied to filter for events of PH interest. For each rule, statistical process controls were applied to generate alerts when levels exceeded two standard deviations above the mean. The system was deployed at a large hospital in Salt Lake City during the 2002 Winter Olympic Games, and it was accessed 3 times a day to perform surveillance. Daily reports were provided to local PH agencies after preliminary investigation of the alerts. Results Of the 24 rules monitored, 9 generated alerts on 11 different occasions. The only significant event of PH interest that was noted during the surveillance period was an increase in influenza during the Games. The positive predictive value of the rules varied with a high value (89%) noted for identification of pneumonia from chest radiograph reports by natural language–processing algorithms. Conclusions With the assistance of a novel computer-based surveillance system linked to the electronic medical record that uses objective, quantifiable events and access to patient data, infection control practitioners could play a front-line role in biosurveillance and facilitate bidirectional communication with PH agencies.</description><identifier>ISSN: 0196-6553</identifier><identifier>EISSN: 1527-3296</identifier><identifier>DOI: 10.1016/j.ajic.2006.08.003</identifier><identifier>PMID: 17433939</identifier><language>eng</language><publisher>St. Louis, MO: Mosby, Inc</publisher><subject>Biological and medical sciences ; Cluster Analysis ; Disease Notification ; Disease Outbreaks - prevention & control ; Emergency Medical Services - classification ; Emergency Medical Services - statistics & numerical data ; Epidemiology. Vaccinations ; General aspects ; Hospitals, University ; Humans ; Infection Control ; Infection Control - methods ; Infectious Disease ; Infectious diseases ; Mandatory Reporting ; Medical Informatics Applications ; Medical Records Systems, Computerized - statistics & numerical data ; Medical sciences ; Population Surveillance - methods ; Sports ; Utah - epidemiology</subject><ispartof>American journal of infection control, 2007-04, Vol.35 (3), p.163-171</ispartof><rights>Association for Professionals in Infection Control and Epidemiology, Inc.</rights><rights>2007 Association for Professionals in Infection Control and Epidemiology, Inc.</rights><rights>2007 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c505t-33932dcc997a5641d52c4440d793ab1d42edc6afa2347dac90101534841a8ae73</citedby><cites>FETCH-LOGICAL-c505t-33932dcc997a5641d52c4440d793ab1d42edc6afa2347dac90101534841a8ae73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=19133180$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/17433939$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gundlapalli, Adi V., MD, PhD</creatorcontrib><creatorcontrib>Olson, Jonathan, BS</creatorcontrib><creatorcontrib>Smith, Sean P., BS</creatorcontrib><creatorcontrib>Baza, Michael, BS</creatorcontrib><creatorcontrib>Hausam, Robert R., MD</creatorcontrib><creatorcontrib>Eutropius, Louise J., RN, BSN, CIC</creatorcontrib><creatorcontrib>Pestotnik, Stanley L., MS, RPh</creatorcontrib><creatorcontrib>Duncan, Karen, RN, MSN</creatorcontrib><creatorcontrib>Staggers, Nancy, PhD, RN, FAAN</creatorcontrib><creatorcontrib>Pincetl, Pierre, MD</creatorcontrib><creatorcontrib>Samore, Matthew H., MD</creatorcontrib><title>Hospital electronic medical record–based public health surveillance system deployed during the 2002 Winter Olympic Games</title><title>American journal of infection control</title><addtitle>Am J Infect Control</addtitle><description>Background Several computer biosurveillance systems are in place to detect events of public health (PH) significance; however, most lack access to timely and detailed patient-level data and investigation of alerts places a strain on PH resources. Methods Hospital-based infection control professionals led a multi-disciplinary team to develop a computer rule–based system that relies on the patient's electronic medical record. The rules operated on HL7 messages transmitted by clinical computing systems and encompassed a variety of types of patient-level data, including laboratory test ordering and results, radiology ordering and reports, emergency room and outpatient clinic visits, and hospital admissions. Laboratory data were mapped to standard vocabularies, and radiology data were processed using natural language–processing algorithms before the rules were applied to filter for events of PH interest. For each rule, statistical process controls were applied to generate alerts when levels exceeded two standard deviations above the mean. The system was deployed at a large hospital in Salt Lake City during the 2002 Winter Olympic Games, and it was accessed 3 times a day to perform surveillance. Daily reports were provided to local PH agencies after preliminary investigation of the alerts. Results Of the 24 rules monitored, 9 generated alerts on 11 different occasions. The only significant event of PH interest that was noted during the surveillance period was an increase in influenza during the Games. The positive predictive value of the rules varied with a high value (89%) noted for identification of pneumonia from chest radiograph reports by natural language–processing algorithms. Conclusions With the assistance of a novel computer-based surveillance system linked to the electronic medical record that uses objective, quantifiable events and access to patient data, infection control practitioners could play a front-line role in biosurveillance and facilitate bidirectional communication with PH agencies.</description><subject>Biological and medical sciences</subject><subject>Cluster Analysis</subject><subject>Disease Notification</subject><subject>Disease Outbreaks - prevention & control</subject><subject>Emergency Medical Services - classification</subject><subject>Emergency Medical Services - statistics & numerical data</subject><subject>Epidemiology. Vaccinations</subject><subject>General aspects</subject><subject>Hospitals, University</subject><subject>Humans</subject><subject>Infection Control</subject><subject>Infection Control - methods</subject><subject>Infectious Disease</subject><subject>Infectious diseases</subject><subject>Mandatory Reporting</subject><subject>Medical Informatics Applications</subject><subject>Medical Records Systems, Computerized - statistics & numerical data</subject><subject>Medical sciences</subject><subject>Population Surveillance - methods</subject><subject>Sports</subject><subject>Utah - epidemiology</subject><issn>0196-6553</issn><issn>1527-3296</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><recordid>eNp9ks1qFTEUx4Mo9rb6Ai4kG93NeJLMV0AEKbYVCl1UcRlyk3O9GTMfJjOFcdV38A19EjPcC4Uuugqc_M7hz-8cQt4wyBmw6kOb69aZnANUOTQ5gHhGNqzkdSa4rJ6TDTBZZVVZihNyGmMLAFJU5UtywupCCCnkhvy5GuLoJu0pejRTGHpnaIfWmVQKaIZg_93_3eqIlo7z1qffPWo_7Wmcwx0673VvkMYlTthRi6MfloTaObj-J532SFM8Tn-4fsJAb_zSjWnEpe4wviIvdtpHfH18z8j3iy_fzq-y65vLr-efrzNTQjlla1BujZGy1mVVMFtyUxQF2FoKvWW24GhNpXeai6K22khIckpRNAXTjcZanJH3h7ljGH7PGCfVuWhwTY7DHFUNom645AnkB9CEIcaAOzUG1-mwKAZqNa5atRpXq3EFjUrGU9Pb4_R5m7w9tBwVJ-DdEdAxSd2FJMzFB04yIVgDift44DC5uHMYVDQOk1zr0h4mZQf3dI5Pj9qNd_26xl-4YGyHOfTJsmIqcgXqdr2N9TSgAsYaUYv_9WC1ew</recordid><startdate>20070401</startdate><enddate>20070401</enddate><creator>Gundlapalli, Adi V., MD, PhD</creator><creator>Olson, Jonathan, BS</creator><creator>Smith, Sean P., BS</creator><creator>Baza, Michael, BS</creator><creator>Hausam, Robert R., MD</creator><creator>Eutropius, Louise J., RN, BSN, CIC</creator><creator>Pestotnik, Stanley L., MS, RPh</creator><creator>Duncan, Karen, RN, MSN</creator><creator>Staggers, Nancy, PhD, RN, FAAN</creator><creator>Pincetl, Pierre, MD</creator><creator>Samore, Matthew H., MD</creator><general>Mosby, Inc</general><general>Mosby</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20070401</creationdate><title>Hospital electronic medical record–based public health surveillance system deployed during the 2002 Winter Olympic Games</title><author>Gundlapalli, Adi V., MD, PhD ; Olson, Jonathan, BS ; Smith, Sean P., BS ; Baza, Michael, BS ; Hausam, Robert R., MD ; Eutropius, Louise J., RN, BSN, CIC ; Pestotnik, Stanley L., MS, RPh ; Duncan, Karen, RN, MSN ; Staggers, Nancy, PhD, RN, FAAN ; Pincetl, Pierre, MD ; Samore, Matthew H., MD</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c505t-33932dcc997a5641d52c4440d793ab1d42edc6afa2347dac90101534841a8ae73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Biological and medical sciences</topic><topic>Cluster Analysis</topic><topic>Disease Notification</topic><topic>Disease Outbreaks - prevention & control</topic><topic>Emergency Medical Services - classification</topic><topic>Emergency Medical Services - statistics & numerical data</topic><topic>Epidemiology. Vaccinations</topic><topic>General aspects</topic><topic>Hospitals, University</topic><topic>Humans</topic><topic>Infection Control</topic><topic>Infection Control - methods</topic><topic>Infectious Disease</topic><topic>Infectious diseases</topic><topic>Mandatory Reporting</topic><topic>Medical Informatics Applications</topic><topic>Medical Records Systems, Computerized - statistics & numerical data</topic><topic>Medical sciences</topic><topic>Population Surveillance - methods</topic><topic>Sports</topic><topic>Utah - epidemiology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gundlapalli, Adi V., MD, PhD</creatorcontrib><creatorcontrib>Olson, Jonathan, BS</creatorcontrib><creatorcontrib>Smith, Sean P., BS</creatorcontrib><creatorcontrib>Baza, Michael, BS</creatorcontrib><creatorcontrib>Hausam, Robert R., MD</creatorcontrib><creatorcontrib>Eutropius, Louise J., RN, BSN, CIC</creatorcontrib><creatorcontrib>Pestotnik, Stanley L., MS, RPh</creatorcontrib><creatorcontrib>Duncan, Karen, RN, MSN</creatorcontrib><creatorcontrib>Staggers, Nancy, PhD, RN, FAAN</creatorcontrib><creatorcontrib>Pincetl, Pierre, MD</creatorcontrib><creatorcontrib>Samore, Matthew H., MD</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>American journal of infection control</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gundlapalli, Adi V., MD, PhD</au><au>Olson, Jonathan, BS</au><au>Smith, Sean P., BS</au><au>Baza, Michael, BS</au><au>Hausam, Robert R., MD</au><au>Eutropius, Louise J., RN, BSN, CIC</au><au>Pestotnik, Stanley L., MS, RPh</au><au>Duncan, Karen, RN, MSN</au><au>Staggers, Nancy, PhD, RN, FAAN</au><au>Pincetl, Pierre, MD</au><au>Samore, Matthew H., MD</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Hospital electronic medical record–based public health surveillance system deployed during the 2002 Winter Olympic Games</atitle><jtitle>American journal of infection control</jtitle><addtitle>Am J Infect Control</addtitle><date>2007-04-01</date><risdate>2007</risdate><volume>35</volume><issue>3</issue><spage>163</spage><epage>171</epage><pages>163-171</pages><issn>0196-6553</issn><eissn>1527-3296</eissn><abstract>Background Several computer biosurveillance systems are in place to detect events of public health (PH) significance; however, most lack access to timely and detailed patient-level data and investigation of alerts places a strain on PH resources. Methods Hospital-based infection control professionals led a multi-disciplinary team to develop a computer rule–based system that relies on the patient's electronic medical record. The rules operated on HL7 messages transmitted by clinical computing systems and encompassed a variety of types of patient-level data, including laboratory test ordering and results, radiology ordering and reports, emergency room and outpatient clinic visits, and hospital admissions. Laboratory data were mapped to standard vocabularies, and radiology data were processed using natural language–processing algorithms before the rules were applied to filter for events of PH interest. For each rule, statistical process controls were applied to generate alerts when levels exceeded two standard deviations above the mean. The system was deployed at a large hospital in Salt Lake City during the 2002 Winter Olympic Games, and it was accessed 3 times a day to perform surveillance. Daily reports were provided to local PH agencies after preliminary investigation of the alerts. Results Of the 24 rules monitored, 9 generated alerts on 11 different occasions. The only significant event of PH interest that was noted during the surveillance period was an increase in influenza during the Games. The positive predictive value of the rules varied with a high value (89%) noted for identification of pneumonia from chest radiograph reports by natural language–processing algorithms. Conclusions With the assistance of a novel computer-based surveillance system linked to the electronic medical record that uses objective, quantifiable events and access to patient data, infection control practitioners could play a front-line role in biosurveillance and facilitate bidirectional communication with PH agencies.</abstract><cop>St. Louis, MO</cop><pub>Mosby, Inc</pub><pmid>17433939</pmid><doi>10.1016/j.ajic.2006.08.003</doi><tpages>9</tpages></addata></record> |
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subjects | Biological and medical sciences Cluster Analysis Disease Notification Disease Outbreaks - prevention & control Emergency Medical Services - classification Emergency Medical Services - statistics & numerical data Epidemiology. Vaccinations General aspects Hospitals, University Humans Infection Control Infection Control - methods Infectious Disease Infectious diseases Mandatory Reporting Medical Informatics Applications Medical Records Systems, Computerized - statistics & numerical data Medical sciences Population Surveillance - methods Sports Utah - epidemiology |
title | Hospital electronic medical record–based public health surveillance system deployed during the 2002 Winter Olympic Games |
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