Use of diagnosis codes for detection of clinically significant opioid poisoning in the emergency department: A retrospective analysis of a surveillance case definition
Although fatal opioid poisonings tripled from 1999 to 2008, data describing nonfatal poisonings are rare. Public health authorities are in need of tools to track opioid poisonings in near real time. We determined the utility of ICD-9-CM diagnosis codes for identifying clinically significant opioid p...
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| Veröffentlicht in: | BMC emergency medicine 2016-02, Vol.16 (11), p.11, Article 11 |
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| creator | Reardon, Joseph M Harmon, Katherine J Schult, Genevieve C Staton, Catherine A Waller, Anna E |
| description | Although fatal opioid poisonings tripled from 1999 to 2008, data describing nonfatal poisonings are rare. Public health authorities are in need of tools to track opioid poisonings in near real time.
We determined the utility of ICD-9-CM diagnosis codes for identifying clinically significant opioid poisonings in a state-wide emergency department (ED) surveillance system. We sampled visits from four hospitals from July 2009 to June 2012 with diagnosis codes of 965.00, 965.01, 965.02 and 965.09 (poisoning by opiates and related narcotics) and/or an external cause of injury code of E850.0-E850.2 (accidental poisoning by opiates and related narcotics), and developed a novel case definition to determine in which cases opioid poisoning prompted the ED visit. We calculated the percentage of visits coded for opioid poisoning that were clinically significant and compared it to the percentage of visits coded for poisoning by non-opioid agents in which there was actually poisoning by an opioid agent. We created a multivariate regression model to determine if other collected triage data can improve the positive predictive value of diagnosis codes alone for detecting clinically significant opioid poisoning.
70.1 % of visits (Standard Error 2.4 %) coded for opioid poisoning were primarily prompted by opioid poisoning. The remainder of visits represented opioid exposure in the setting of other primary diseases. Among non-opioid poisoning codes reviewed, up to 36 % were reclassified as an opioid poisoning. In multivariate analysis, only naloxone use improved the positive predictive value of ICD-9-CM codes for identifying clinically significant opioid poisoning, but was associated with a high false negative rate.
This surveillance mechanism identifies many clinically significant opioid overdoses with a high positive predictive value. With further validation, it may help target control measures such as prescriber education and pharmacy monitoring. |
| doi_str_mv | 10.1186/s12873-016-0075-4 |
| format | Article |
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We determined the utility of ICD-9-CM diagnosis codes for identifying clinically significant opioid poisonings in a state-wide emergency department (ED) surveillance system. We sampled visits from four hospitals from July 2009 to June 2012 with diagnosis codes of 965.00, 965.01, 965.02 and 965.09 (poisoning by opiates and related narcotics) and/or an external cause of injury code of E850.0-E850.2 (accidental poisoning by opiates and related narcotics), and developed a novel case definition to determine in which cases opioid poisoning prompted the ED visit. We calculated the percentage of visits coded for opioid poisoning that were clinically significant and compared it to the percentage of visits coded for poisoning by non-opioid agents in which there was actually poisoning by an opioid agent. We created a multivariate regression model to determine if other collected triage data can improve the positive predictive value of diagnosis codes alone for detecting clinically significant opioid poisoning.
70.1 % of visits (Standard Error 2.4 %) coded for opioid poisoning were primarily prompted by opioid poisoning. The remainder of visits represented opioid exposure in the setting of other primary diseases. Among non-opioid poisoning codes reviewed, up to 36 % were reclassified as an opioid poisoning. In multivariate analysis, only naloxone use improved the positive predictive value of ICD-9-CM codes for identifying clinically significant opioid poisoning, but was associated with a high false negative rate.
This surveillance mechanism identifies many clinically significant opioid overdoses with a high positive predictive value. With further validation, it may help target control measures such as prescriber education and pharmacy monitoring.</description><identifier>ISSN: 1471-227X</identifier><identifier>EISSN: 1471-227X</identifier><identifier>DOI: 10.1186/s12873-016-0075-4</identifier><identifier>PMID: 26856978</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Adolescent ; Adult ; Analgesics, Opioid - poisoning ; Clinical Coding ; Emergency service ; Emergency Service, Hospital ; Female ; Health aspects ; Hospitals ; Humans ; International Classification of Diseases ; Male ; Medical Overuse - trends ; Middle Aged ; Poisoning ; Population Surveillance ; Retrospective Studies ; Triage ; Young Adult</subject><ispartof>BMC emergency medicine, 2016-02, Vol.16 (11), p.11, Article 11</ispartof><rights>COPYRIGHT 2016 BioMed Central Ltd.</rights><rights>Copyright BioMed Central 2016</rights><rights>Reardon et al. 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c564t-2564bc5dc6b7f15f70381f8ead76a83a88b80e3dd712a8ec770a78fdaad5d9803</citedby><cites>FETCH-LOGICAL-c564t-2564bc5dc6b7f15f70381f8ead76a83a88b80e3dd712a8ec770a78fdaad5d9803</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4746926/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4746926/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26856978$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Reardon, Joseph M</creatorcontrib><creatorcontrib>Harmon, Katherine J</creatorcontrib><creatorcontrib>Schult, Genevieve C</creatorcontrib><creatorcontrib>Staton, Catherine A</creatorcontrib><creatorcontrib>Waller, Anna E</creatorcontrib><title>Use of diagnosis codes for detection of clinically significant opioid poisoning in the emergency department: A retrospective analysis of a surveillance case definition</title><title>BMC emergency medicine</title><addtitle>BMC Emerg Med</addtitle><description>Although fatal opioid poisonings tripled from 1999 to 2008, data describing nonfatal poisonings are rare. Public health authorities are in need of tools to track opioid poisonings in near real time.
We determined the utility of ICD-9-CM diagnosis codes for identifying clinically significant opioid poisonings in a state-wide emergency department (ED) surveillance system. We sampled visits from four hospitals from July 2009 to June 2012 with diagnosis codes of 965.00, 965.01, 965.02 and 965.09 (poisoning by opiates and related narcotics) and/or an external cause of injury code of E850.0-E850.2 (accidental poisoning by opiates and related narcotics), and developed a novel case definition to determine in which cases opioid poisoning prompted the ED visit. We calculated the percentage of visits coded for opioid poisoning that were clinically significant and compared it to the percentage of visits coded for poisoning by non-opioid agents in which there was actually poisoning by an opioid agent. We created a multivariate regression model to determine if other collected triage data can improve the positive predictive value of diagnosis codes alone for detecting clinically significant opioid poisoning.
70.1 % of visits (Standard Error 2.4 %) coded for opioid poisoning were primarily prompted by opioid poisoning. The remainder of visits represented opioid exposure in the setting of other primary diseases. Among non-opioid poisoning codes reviewed, up to 36 % were reclassified as an opioid poisoning. In multivariate analysis, only naloxone use improved the positive predictive value of ICD-9-CM codes for identifying clinically significant opioid poisoning, but was associated with a high false negative rate.
This surveillance mechanism identifies many clinically significant opioid overdoses with a high positive predictive value. With further validation, it may help target control measures such as prescriber education and pharmacy monitoring.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Analgesics, Opioid - poisoning</subject><subject>Clinical Coding</subject><subject>Emergency service</subject><subject>Emergency Service, Hospital</subject><subject>Female</subject><subject>Health aspects</subject><subject>Hospitals</subject><subject>Humans</subject><subject>International Classification of Diseases</subject><subject>Male</subject><subject>Medical Overuse - trends</subject><subject>Middle Aged</subject><subject>Poisoning</subject><subject>Population Surveillance</subject><subject>Retrospective Studies</subject><subject>Triage</subject><subject>Young Adult</subject><issn>1471-227X</issn><issn>1471-227X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNptUl1rFTEQXUSxH_oDfJGAz1uT_UiyPgiXolYo-GLBtzA3mWxTssma7L1wf1H_pllurS1IIJkkZ86cGU5VvWP0gjHJP2bWSNHWlPGaUtHX3YvqlHWC1U0jfr18Ep9UZznfUcqEZMPr6qThsueDkKfV_U1GEi0xDsYQs8tER4OZ2JiIwQX14mJYAdq74DR4fyDZjcHZcgkLibOLzpA5uhyDCyNxgSy3SHDCNGLQh8IyQ1omDMsnsiEJlxTzvPLukUAAf1iLlgJA8i7t0XkPQSPRUIQZtKXqKuFN9cqCz_j24Tyvbr5--Xl5VV__-Pb9cnNd6553S92Ufat7o_lWWNZbQVvJrEQwgoNsQcqtpNgaI1gDErUQFIS0BsD0ZpC0Pa8-H3nn3XZCo4vsBF7NyU2QDiqCU89_grtVY9yrTnR8aHgh-PBAkOLvHeZF3cVdKn1mxYRoxUB51_1DjeBRuWBjIdOTy1ptuq6RtKGiLaiL_6DKMjg5HUOZTnl_lsCOCboMOSe0j8IZVatl1NEyqlhGrZZRq5T3Tzt-zPjrkfYPoiPBIA</recordid><startdate>20160208</startdate><enddate>20160208</enddate><creator>Reardon, Joseph M</creator><creator>Harmon, Katherine J</creator><creator>Schult, Genevieve C</creator><creator>Staton, Catherine A</creator><creator>Waller, Anna E</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><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>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>5PM</scope></search><sort><creationdate>20160208</creationdate><title>Use of diagnosis codes for detection of clinically significant opioid poisoning in the emergency department: A retrospective analysis of a surveillance case definition</title><author>Reardon, Joseph M ; Harmon, Katherine J ; Schult, Genevieve C ; Staton, Catherine A ; Waller, Anna E</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c564t-2564bc5dc6b7f15f70381f8ead76a83a88b80e3dd712a8ec770a78fdaad5d9803</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Analgesics, Opioid - poisoning</topic><topic>Clinical Coding</topic><topic>Emergency service</topic><topic>Emergency Service, Hospital</topic><topic>Female</topic><topic>Health aspects</topic><topic>Hospitals</topic><topic>Humans</topic><topic>International Classification of Diseases</topic><topic>Male</topic><topic>Medical Overuse - trends</topic><topic>Middle Aged</topic><topic>Poisoning</topic><topic>Population Surveillance</topic><topic>Retrospective Studies</topic><topic>Triage</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Reardon, Joseph M</creatorcontrib><creatorcontrib>Harmon, Katherine J</creatorcontrib><creatorcontrib>Schult, Genevieve C</creatorcontrib><creatorcontrib>Staton, Catherine A</creatorcontrib><creatorcontrib>Waller, Anna E</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>BMC emergency medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Reardon, Joseph M</au><au>Harmon, Katherine J</au><au>Schult, Genevieve C</au><au>Staton, Catherine A</au><au>Waller, Anna E</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Use of diagnosis codes for detection of clinically significant opioid poisoning in the emergency department: A retrospective analysis of a surveillance case definition</atitle><jtitle>BMC emergency medicine</jtitle><addtitle>BMC Emerg Med</addtitle><date>2016-02-08</date><risdate>2016</risdate><volume>16</volume><issue>11</issue><spage>11</spage><pages>11-</pages><artnum>11</artnum><issn>1471-227X</issn><eissn>1471-227X</eissn><abstract>Although fatal opioid poisonings tripled from 1999 to 2008, data describing nonfatal poisonings are rare. Public health authorities are in need of tools to track opioid poisonings in near real time.
We determined the utility of ICD-9-CM diagnosis codes for identifying clinically significant opioid poisonings in a state-wide emergency department (ED) surveillance system. We sampled visits from four hospitals from July 2009 to June 2012 with diagnosis codes of 965.00, 965.01, 965.02 and 965.09 (poisoning by opiates and related narcotics) and/or an external cause of injury code of E850.0-E850.2 (accidental poisoning by opiates and related narcotics), and developed a novel case definition to determine in which cases opioid poisoning prompted the ED visit. We calculated the percentage of visits coded for opioid poisoning that were clinically significant and compared it to the percentage of visits coded for poisoning by non-opioid agents in which there was actually poisoning by an opioid agent. We created a multivariate regression model to determine if other collected triage data can improve the positive predictive value of diagnosis codes alone for detecting clinically significant opioid poisoning.
70.1 % of visits (Standard Error 2.4 %) coded for opioid poisoning were primarily prompted by opioid poisoning. The remainder of visits represented opioid exposure in the setting of other primary diseases. Among non-opioid poisoning codes reviewed, up to 36 % were reclassified as an opioid poisoning. In multivariate analysis, only naloxone use improved the positive predictive value of ICD-9-CM codes for identifying clinically significant opioid poisoning, but was associated with a high false negative rate.
This surveillance mechanism identifies many clinically significant opioid overdoses with a high positive predictive value. With further validation, it may help target control measures such as prescriber education and pharmacy monitoring.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>26856978</pmid><doi>10.1186/s12873-016-0075-4</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Adolescent Adult Analgesics, Opioid - poisoning Clinical Coding Emergency service Emergency Service, Hospital Female Health aspects Hospitals Humans International Classification of Diseases Male Medical Overuse - trends Middle Aged Poisoning Population Surveillance Retrospective Studies Triage Young Adult |
| title | Use of diagnosis codes for detection of clinically significant opioid poisoning in the emergency department: A retrospective analysis of a surveillance case definition |
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