Accuracy of diagnosis codes to identify febrile young infants using administrative data
BACKGROUND Administrative data can be used to determine optimal management of febrile infants and aid clinical practice guideline development. OBJECTIVE Determine the most accurate International Classification of Diseases, Ninth Revision (ICD‐9) diagnosis coding strategies for identification of febr...
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| Veröffentlicht in: | Journal of hospital medicine 2015-12, Vol.10 (12), p.787-793 |
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| creator | Aronson, Paul L. Williams, Derek J. Thurm, Cary Tieder, Joel S. Alpern, Elizabeth R. Nigrovic, Lise E. Schondelmeyer, Amanda C. Balamuth, Fran Myers, Angela L. McCulloh, Russell J. Alessandrini, Evaline A. Shah, Samir S. Browning, Whitney L. Hayes, Katie L. Feldman, Elana A. Neuman, Mark I. |
| description | BACKGROUND
Administrative data can be used to determine optimal management of febrile infants and aid clinical practice guideline development.
OBJECTIVE
Determine the most accurate International Classification of Diseases, Ninth Revision (ICD‐9) diagnosis coding strategies for identification of febrile infants.
DESIGN
Retrospective cross‐sectional study.
SETTING
Eight emergency departments in the Pediatric Health Information System.
PATIENTS
Infants aged |
| doi_str_mv | 10.1002/jhm.2441 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4715646</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3923472731</sourcerecordid><originalsourceid>FETCH-LOGICAL-c5461-4066d81b09675743e0d4d3c95b4922635049ef844c18bcf1c788aad3dfd269703</originalsourceid><addsrcrecordid>eNp1kU1PFTEUhhujEQQTf4Fp4sbNYL9nZmNCiN4rAm4wGDdNpx-XXmdaaGeA-feWcLmiiaue5jx58rYvAG8wOsAIkQ_ry-GAMIafgV3MOa24QOL548xbsgNe5bxGiNGGs5dghwjCGtHiXXBxqPWUlJ5hdNB4tQox-wx1NDbDMUJvbBi9m6GzXfK9hXOcwgr64FQYM5yyLzdlBh98HpMa_Y2FRo1qH7xwqs_29ebcA98_fzo_WlYn3xZfjg5PKs2ZwBVDQpgGd6gVNa8ZtcgwQ3XLO9YSIihHrLWuYUzjptMO67pplDLUOENEWyO6Bz4-eK-mbrBGl7RJ9fIq-UGlWUbl5d-b4C_lKt5IVmMumCiC9xtBiteTzaMcfNa271WwccoS1wI1QhBEC_ruH3QdpxTK8wrFa044btgfoU4x52TdNgxG8r4tWdqS920V9O3T8FvwsZ4CVA_Abfn6-b8iebw83Qg3fCnD3m15lX5JUdOay4uzhVycLunix_FX-ZP-Bg4frbk</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1757525184</pqid></control><display><type>article</type><title>Accuracy of diagnosis codes to identify febrile young infants using administrative data</title><source>MEDLINE</source><source>Wiley Online Library Journals Frontfile Complete</source><creator>Aronson, Paul L. ; Williams, Derek J. ; Thurm, Cary ; Tieder, Joel S. ; Alpern, Elizabeth R. ; Nigrovic, Lise E. ; Schondelmeyer, Amanda C. ; Balamuth, Fran ; Myers, Angela L. ; McCulloh, Russell J. ; Alessandrini, Evaline A. ; Shah, Samir S. ; Browning, Whitney L. ; Hayes, Katie L. ; Feldman, Elana A. ; Neuman, Mark I.</creator><creatorcontrib>Aronson, Paul L. ; Williams, Derek J. ; Thurm, Cary ; Tieder, Joel S. ; Alpern, Elizabeth R. ; Nigrovic, Lise E. ; Schondelmeyer, Amanda C. ; Balamuth, Fran ; Myers, Angela L. ; McCulloh, Russell J. ; Alessandrini, Evaline A. ; Shah, Samir S. ; Browning, Whitney L. ; Hayes, Katie L. ; Feldman, Elana A. ; Neuman, Mark I. ; Febrile Young Infant Research Collaborative ; for the Febrile Young Infant Research Collaborative</creatorcontrib><description>BACKGROUND
Administrative data can be used to determine optimal management of febrile infants and aid clinical practice guideline development.
OBJECTIVE
Determine the most accurate International Classification of Diseases, Ninth Revision (ICD‐9) diagnosis coding strategies for identification of febrile infants.
DESIGN
Retrospective cross‐sectional study.
SETTING
Eight emergency departments in the Pediatric Health Information System.
PATIENTS
Infants aged <90 days evaluated between July 1, 2012 and June 30, 2013 were randomly selected for medical record review from 1 of 4 ICD‐9 diagnosis code groups: (1) discharge diagnosis of fever, (2) admission diagnosis of fever without discharge diagnosis of fever, (3) discharge diagnosis of serious infection without diagnosis of fever, and (4) no diagnosis of fever or serious infection.
EXPOSURE
The ICD‐9 diagnosis code groups were compared in 4 case‐identification algorithms to a reference standard of fever ≥100.4°F documented in the medical record.
MEASUREMENTS
Algorithm predictive accuracy was measured using sensitivity, specificity, and negative and positive predictive values.
RESULTS
Among 1790 medical records reviewed, 766 (42.8%) infants had fever. Discharge diagnosis of fever demonstrated high specificity (98.2%, 95% confidence interval [CI]: 97.8‐98.6) but low sensitivity (53.2%, 95% CI: 50.0‐56.4). A case‐identification algorithm of admission or discharge diagnosis of fever exhibited higher sensitivity (71.1%, 95% CI: 68.2‐74.0), similar specificity (97.7%, 95% CI: 97.3‐98.1), and the highest positive predictive value (86.9%, 95% CI: 84.5‐89.3).
CONCLUSIONS
A case‐identification strategy that includes admission or discharge diagnosis of fever should be considered for febrile infant studies using administrative data, though underclassification of patients is a potential limitation. Journal of Hospital Medicine 2015;10:787–793. © 2015 Society of Hospital Medicine</description><identifier>ISSN: 1553-5592</identifier><identifier>EISSN: 1553-5606</identifier><identifier>DOI: 10.1002/jhm.2441</identifier><identifier>PMID: 26248691</identifier><language>eng</language><publisher>United States: Blackwell Publishing Ltd</publisher><subject>Codes ; Confidence intervals ; Cross-Sectional Studies ; Databases, Factual - standards ; Female ; Fever - diagnosis ; Fever - epidemiology ; Hospitals ; Humans ; Infant ; Infant, Newborn ; International Classification of Diseases - standards ; Male ; Medical records ; Patient Discharge - standards ; Retrospective Studies ; Statistics as Topic - standards</subject><ispartof>Journal of hospital medicine, 2015-12, Vol.10 (12), p.787-793</ispartof><rights>2015 Society of Hospital Medicine</rights><rights>2015 Society of Hospital Medicine.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5461-4066d81b09675743e0d4d3c95b4922635049ef844c18bcf1c788aad3dfd269703</citedby><cites>FETCH-LOGICAL-c5461-4066d81b09675743e0d4d3c95b4922635049ef844c18bcf1c788aad3dfd269703</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fjhm.2441$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fjhm.2441$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,776,780,881,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26248691$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Aronson, Paul L.</creatorcontrib><creatorcontrib>Williams, Derek J.</creatorcontrib><creatorcontrib>Thurm, Cary</creatorcontrib><creatorcontrib>Tieder, Joel S.</creatorcontrib><creatorcontrib>Alpern, Elizabeth R.</creatorcontrib><creatorcontrib>Nigrovic, Lise E.</creatorcontrib><creatorcontrib>Schondelmeyer, Amanda C.</creatorcontrib><creatorcontrib>Balamuth, Fran</creatorcontrib><creatorcontrib>Myers, Angela L.</creatorcontrib><creatorcontrib>McCulloh, Russell J.</creatorcontrib><creatorcontrib>Alessandrini, Evaline A.</creatorcontrib><creatorcontrib>Shah, Samir S.</creatorcontrib><creatorcontrib>Browning, Whitney L.</creatorcontrib><creatorcontrib>Hayes, Katie L.</creatorcontrib><creatorcontrib>Feldman, Elana A.</creatorcontrib><creatorcontrib>Neuman, Mark I.</creatorcontrib><creatorcontrib>Febrile Young Infant Research Collaborative</creatorcontrib><creatorcontrib>for the Febrile Young Infant Research Collaborative</creatorcontrib><title>Accuracy of diagnosis codes to identify febrile young infants using administrative data</title><title>Journal of hospital medicine</title><addtitle>J. Hosp. Med</addtitle><description>BACKGROUND
Administrative data can be used to determine optimal management of febrile infants and aid clinical practice guideline development.
OBJECTIVE
Determine the most accurate International Classification of Diseases, Ninth Revision (ICD‐9) diagnosis coding strategies for identification of febrile infants.
DESIGN
Retrospective cross‐sectional study.
SETTING
Eight emergency departments in the Pediatric Health Information System.
PATIENTS
Infants aged <90 days evaluated between July 1, 2012 and June 30, 2013 were randomly selected for medical record review from 1 of 4 ICD‐9 diagnosis code groups: (1) discharge diagnosis of fever, (2) admission diagnosis of fever without discharge diagnosis of fever, (3) discharge diagnosis of serious infection without diagnosis of fever, and (4) no diagnosis of fever or serious infection.
EXPOSURE
The ICD‐9 diagnosis code groups were compared in 4 case‐identification algorithms to a reference standard of fever ≥100.4°F documented in the medical record.
MEASUREMENTS
Algorithm predictive accuracy was measured using sensitivity, specificity, and negative and positive predictive values.
RESULTS
Among 1790 medical records reviewed, 766 (42.8%) infants had fever. Discharge diagnosis of fever demonstrated high specificity (98.2%, 95% confidence interval [CI]: 97.8‐98.6) but low sensitivity (53.2%, 95% CI: 50.0‐56.4). A case‐identification algorithm of admission or discharge diagnosis of fever exhibited higher sensitivity (71.1%, 95% CI: 68.2‐74.0), similar specificity (97.7%, 95% CI: 97.3‐98.1), and the highest positive predictive value (86.9%, 95% CI: 84.5‐89.3).
CONCLUSIONS
A case‐identification strategy that includes admission or discharge diagnosis of fever should be considered for febrile infant studies using administrative data, though underclassification of patients is a potential limitation. Journal of Hospital Medicine 2015;10:787–793. © 2015 Society of Hospital Medicine</description><subject>Codes</subject><subject>Confidence intervals</subject><subject>Cross-Sectional Studies</subject><subject>Databases, Factual - standards</subject><subject>Female</subject><subject>Fever - diagnosis</subject><subject>Fever - epidemiology</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Infant</subject><subject>Infant, Newborn</subject><subject>International Classification of Diseases - standards</subject><subject>Male</subject><subject>Medical records</subject><subject>Patient Discharge - standards</subject><subject>Retrospective Studies</subject><subject>Statistics as Topic - standards</subject><issn>1553-5592</issn><issn>1553-5606</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kU1PFTEUhhujEQQTf4Fp4sbNYL9nZmNCiN4rAm4wGDdNpx-XXmdaaGeA-feWcLmiiaue5jx58rYvAG8wOsAIkQ_ry-GAMIafgV3MOa24QOL548xbsgNe5bxGiNGGs5dghwjCGtHiXXBxqPWUlJ5hdNB4tQox-wx1NDbDMUJvbBi9m6GzXfK9hXOcwgr64FQYM5yyLzdlBh98HpMa_Y2FRo1qH7xwqs_29ebcA98_fzo_WlYn3xZfjg5PKs2ZwBVDQpgGd6gVNa8ZtcgwQ3XLO9YSIihHrLWuYUzjptMO67pplDLUOENEWyO6Bz4-eK-mbrBGl7RJ9fIq-UGlWUbl5d-b4C_lKt5IVmMumCiC9xtBiteTzaMcfNa271WwccoS1wI1QhBEC_ruH3QdpxTK8wrFa044btgfoU4x52TdNgxG8r4tWdqS920V9O3T8FvwsZ4CVA_Abfn6-b8iebw83Qg3fCnD3m15lX5JUdOay4uzhVycLunix_FX-ZP-Bg4frbk</recordid><startdate>201512</startdate><enddate>201512</enddate><creator>Aronson, Paul L.</creator><creator>Williams, Derek J.</creator><creator>Thurm, Cary</creator><creator>Tieder, Joel S.</creator><creator>Alpern, Elizabeth R.</creator><creator>Nigrovic, Lise E.</creator><creator>Schondelmeyer, Amanda C.</creator><creator>Balamuth, Fran</creator><creator>Myers, Angela L.</creator><creator>McCulloh, Russell J.</creator><creator>Alessandrini, Evaline A.</creator><creator>Shah, Samir S.</creator><creator>Browning, Whitney L.</creator><creator>Hayes, Katie L.</creator><creator>Feldman, Elana A.</creator><creator>Neuman, Mark I.</creator><general>Blackwell Publishing Ltd</general><general>Frontline Medical Communications</general><scope>BSCLL</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>K9.</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>201512</creationdate><title>Accuracy of diagnosis codes to identify febrile young infants using administrative data</title><author>Aronson, Paul L. ; Williams, Derek J. ; Thurm, Cary ; Tieder, Joel S. ; Alpern, Elizabeth R. ; Nigrovic, Lise E. ; Schondelmeyer, Amanda C. ; Balamuth, Fran ; Myers, Angela L. ; McCulloh, Russell J. ; Alessandrini, Evaline A. ; Shah, Samir S. ; Browning, Whitney L. ; Hayes, Katie L. ; Feldman, Elana A. ; Neuman, Mark I.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5461-4066d81b09675743e0d4d3c95b4922635049ef844c18bcf1c788aad3dfd269703</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Codes</topic><topic>Confidence intervals</topic><topic>Cross-Sectional Studies</topic><topic>Databases, Factual - standards</topic><topic>Female</topic><topic>Fever - diagnosis</topic><topic>Fever - epidemiology</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Infant</topic><topic>Infant, Newborn</topic><topic>International Classification of Diseases - standards</topic><topic>Male</topic><topic>Medical records</topic><topic>Patient Discharge - standards</topic><topic>Retrospective Studies</topic><topic>Statistics as Topic - standards</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Aronson, Paul L.</creatorcontrib><creatorcontrib>Williams, Derek J.</creatorcontrib><creatorcontrib>Thurm, Cary</creatorcontrib><creatorcontrib>Tieder, Joel S.</creatorcontrib><creatorcontrib>Alpern, Elizabeth R.</creatorcontrib><creatorcontrib>Nigrovic, Lise E.</creatorcontrib><creatorcontrib>Schondelmeyer, Amanda C.</creatorcontrib><creatorcontrib>Balamuth, Fran</creatorcontrib><creatorcontrib>Myers, Angela L.</creatorcontrib><creatorcontrib>McCulloh, Russell J.</creatorcontrib><creatorcontrib>Alessandrini, Evaline A.</creatorcontrib><creatorcontrib>Shah, Samir S.</creatorcontrib><creatorcontrib>Browning, Whitney L.</creatorcontrib><creatorcontrib>Hayes, Katie L.</creatorcontrib><creatorcontrib>Feldman, Elana A.</creatorcontrib><creatorcontrib>Neuman, Mark I.</creatorcontrib><creatorcontrib>Febrile Young Infant Research Collaborative</creatorcontrib><creatorcontrib>for the Febrile Young Infant Research Collaborative</creatorcontrib><collection>Istex</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of hospital medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Aronson, Paul L.</au><au>Williams, Derek J.</au><au>Thurm, Cary</au><au>Tieder, Joel S.</au><au>Alpern, Elizabeth R.</au><au>Nigrovic, Lise E.</au><au>Schondelmeyer, Amanda C.</au><au>Balamuth, Fran</au><au>Myers, Angela L.</au><au>McCulloh, Russell J.</au><au>Alessandrini, Evaline A.</au><au>Shah, Samir S.</au><au>Browning, Whitney L.</au><au>Hayes, Katie L.</au><au>Feldman, Elana A.</au><au>Neuman, Mark I.</au><aucorp>Febrile Young Infant Research Collaborative</aucorp><aucorp>for the Febrile Young Infant Research Collaborative</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Accuracy of diagnosis codes to identify febrile young infants using administrative data</atitle><jtitle>Journal of hospital medicine</jtitle><addtitle>J. Hosp. Med</addtitle><date>2015-12</date><risdate>2015</risdate><volume>10</volume><issue>12</issue><spage>787</spage><epage>793</epage><pages>787-793</pages><issn>1553-5592</issn><eissn>1553-5606</eissn><abstract>BACKGROUND
Administrative data can be used to determine optimal management of febrile infants and aid clinical practice guideline development.
OBJECTIVE
Determine the most accurate International Classification of Diseases, Ninth Revision (ICD‐9) diagnosis coding strategies for identification of febrile infants.
DESIGN
Retrospective cross‐sectional study.
SETTING
Eight emergency departments in the Pediatric Health Information System.
PATIENTS
Infants aged <90 days evaluated between July 1, 2012 and June 30, 2013 were randomly selected for medical record review from 1 of 4 ICD‐9 diagnosis code groups: (1) discharge diagnosis of fever, (2) admission diagnosis of fever without discharge diagnosis of fever, (3) discharge diagnosis of serious infection without diagnosis of fever, and (4) no diagnosis of fever or serious infection.
EXPOSURE
The ICD‐9 diagnosis code groups were compared in 4 case‐identification algorithms to a reference standard of fever ≥100.4°F documented in the medical record.
MEASUREMENTS
Algorithm predictive accuracy was measured using sensitivity, specificity, and negative and positive predictive values.
RESULTS
Among 1790 medical records reviewed, 766 (42.8%) infants had fever. Discharge diagnosis of fever demonstrated high specificity (98.2%, 95% confidence interval [CI]: 97.8‐98.6) but low sensitivity (53.2%, 95% CI: 50.0‐56.4). A case‐identification algorithm of admission or discharge diagnosis of fever exhibited higher sensitivity (71.1%, 95% CI: 68.2‐74.0), similar specificity (97.7%, 95% CI: 97.3‐98.1), and the highest positive predictive value (86.9%, 95% CI: 84.5‐89.3).
CONCLUSIONS
A case‐identification strategy that includes admission or discharge diagnosis of fever should be considered for febrile infant studies using administrative data, though underclassification of patients is a potential limitation. Journal of Hospital Medicine 2015;10:787–793. © 2015 Society of Hospital Medicine</abstract><cop>United States</cop><pub>Blackwell Publishing Ltd</pub><pmid>26248691</pmid><doi>10.1002/jhm.2441</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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| identifier | ISSN: 1553-5592 |
| ispartof | Journal of hospital medicine, 2015-12, Vol.10 (12), p.787-793 |
| issn | 1553-5592 1553-5606 |
| language | eng |
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| source | MEDLINE; Wiley Online Library Journals Frontfile Complete |
| subjects | Codes Confidence intervals Cross-Sectional Studies Databases, Factual - standards Female Fever - diagnosis Fever - epidemiology Hospitals Humans Infant Infant, Newborn International Classification of Diseases - standards Male Medical records Patient Discharge - standards Retrospective Studies Statistics as Topic - standards |
| title | Accuracy of diagnosis codes to identify febrile young infants using administrative data |
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