The Impact of ICD-9-CM Code Rank Order on the Estimated Prevalence of Clostridium difficile Infections
Background. US estimates of the Clostridium difficile infection (CDI) burden have utilized International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes. Whether ICD-9-CM code rank order affects CDI prevalence estimates is important because the National Ho...
Gespeichert in:
| Veröffentlicht in: | Clinical infectious diseases 2011-07, Vol.53 (1), p.20-25 |
|---|---|
| Hauptverfasser: | , , , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 25 |
|---|---|
| container_issue | 1 |
| container_start_page | 20 |
| container_title | Clinical infectious diseases |
| container_volume | 53 |
| creator | Dubberke, Erik R. Butler, Anne M. Nyazee, Humaa A. Reske, Kimberly A. Yokoe, Deborah S. Mayer, Jeanmarie Mangino, Julie E. Khan, Yosef M. Fraser, Victoria J. |
| description | Background. US estimates of the Clostridium difficile infection (CDI) burden have utilized International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes. Whether ICD-9-CM code rank order affects CDI prevalence estimates is important because the National Hospital Discharge Survey (NHDS) and the Nationwide Inpatient Sample (NIS) have varying limits on the number of ICD-9-CM codes collected. Methods. ICD-9-CM codes for CDI (008.45), C. difficile toxin assay results, and dates of admission and discharge were collected from electronic hospital databases for adult patients admitted to 4 hospitals in the United States from July 2000 through June 2006. CDI prevalence per 1000 discharges was calculated and compared for NHDS and NIS limits and toxin assay results from the same hospitals. CDI prevalence estimates were compared using the χ² test, and the test of equality was used to compare slopes. Results. CDI prevalence measured by NIS criteria was significantly higher than that measured using NHDS criteria (10.7 cases per 1000 discharges versus 9.4 cases per 1000 discharges; P < .001) in the 4 hospitals. CDI prevalence measured by toxin assay results was 9.4 cases per 1000 discharges (P = .57 versus NHDS). However, the CDI prevalence increased more rapidly over time when measured according to the NHDS criteria than when measured according to toxin assay results (β = 1.09 versus 0.84; P = .008). Conclusions. Compared with the NHDS definition, the NIS definition captured 12% more CDI cases and reported significantly higher CDI rates. Rates calculated using toxin assay results were not different from rates calculated using NHDS criteria, but CDI prevalence appeared to increase more rapidly when measured by NHDS criteria than when measured by toxin assay results. |
| doi_str_mv | 10.1093/cid/cir246 |
| format | Article |
| fullrecord | <record><control><sourceid>jstor_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_3110281</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><jstor_id>23030998</jstor_id><oup_id>10.1093/cid/cir246</oup_id><sourcerecordid>23030998</sourcerecordid><originalsourceid>FETCH-LOGICAL-c486t-c42326ee7d80141521321d67172a4bab8aafec35e6a9d73a11827a2a853628313</originalsourceid><addsrcrecordid>eNp9kc9vFCEcxYnR2B968a4hTbyYTOULA8NcTJqx6iY1NaaeCQuMZZ2FFZgm_vdls2tXLz0A34QP7z3yEHoF5BxIz94bb-tKtBVP0DFw1jWC9_C0zoTLppVMHqGTnFeEAEjCn6MjCoIz2stjNN7cOrxYb7QpOI54MXxs-mb4iodoHf6uwy98naxLOAZcKnmZi1_r4iz-ltydnlwwbvtumGIuyVs_r7H14-iNn6puGJ0pPob8Aj0b9ZTdy_15in58urwZvjRX158Xw8VVY1opSt0po8K5zkoCLXAKjIIVHXRUt0u9lFpXRcad0L3tmK7_oZ2mWnImqGTATtGHne5mXq6dNS6UpCe1STV1-qOi9ur_m-Bv1c94pxgAoXIrcLYXSPH37HJRqzinUDMr2QHtWhCyQu92kEkx5-TGBwMgaluJqpWoXSUVfvNvpAf0bwcVeLsHdDZ6GpMOxucD1zJOaN8euDhvHjd8veNWucR00GGEkb763QPIrano</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>871274168</pqid></control><display><type>article</type><title>The Impact of ICD-9-CM Code Rank Order on the Estimated Prevalence of Clostridium difficile Infections</title><source>Jstor Complete Legacy</source><source>Oxford University Press Journals All Titles (1996-Current)</source><source>MEDLINE</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Alma/SFX Local Collection</source><creator>Dubberke, Erik R. ; Butler, Anne M. ; Nyazee, Humaa A. ; Reske, Kimberly A. ; Yokoe, Deborah S. ; Mayer, Jeanmarie ; Mangino, Julie E. ; Khan, Yosef M. ; Fraser, Victoria J.</creator><creatorcontrib>Dubberke, Erik R. ; Butler, Anne M. ; Nyazee, Humaa A. ; Reske, Kimberly A. ; Yokoe, Deborah S. ; Mayer, Jeanmarie ; Mangino, Julie E. ; Khan, Yosef M. ; Fraser, Victoria J. ; Centers for Disease Control and Prevention Epicenters Program ; Centers for Disease Control and Prevention Epicenters Program</creatorcontrib><description>Background. US estimates of the Clostridium difficile infection (CDI) burden have utilized International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes. Whether ICD-9-CM code rank order affects CDI prevalence estimates is important because the National Hospital Discharge Survey (NHDS) and the Nationwide Inpatient Sample (NIS) have varying limits on the number of ICD-9-CM codes collected. Methods. ICD-9-CM codes for CDI (008.45), C. difficile toxin assay results, and dates of admission and discharge were collected from electronic hospital databases for adult patients admitted to 4 hospitals in the United States from July 2000 through June 2006. CDI prevalence per 1000 discharges was calculated and compared for NHDS and NIS limits and toxin assay results from the same hospitals. CDI prevalence estimates were compared using the χ² test, and the test of equality was used to compare slopes. Results. CDI prevalence measured by NIS criteria was significantly higher than that measured using NHDS criteria (10.7 cases per 1000 discharges versus 9.4 cases per 1000 discharges; P < .001) in the 4 hospitals. CDI prevalence measured by toxin assay results was 9.4 cases per 1000 discharges (P = .57 versus NHDS). However, the CDI prevalence increased more rapidly over time when measured according to the NHDS criteria than when measured according to toxin assay results (β = 1.09 versus 0.84; P = .008). Conclusions. Compared with the NHDS definition, the NIS definition captured 12% more CDI cases and reported significantly higher CDI rates. Rates calculated using toxin assay results were not different from rates calculated using NHDS criteria, but CDI prevalence appeared to increase more rapidly when measured by NHDS criteria than when measured by toxin assay results.</description><identifier>ISSN: 1058-4838</identifier><identifier>EISSN: 1537-6591</identifier><identifier>DOI: 10.1093/cid/cir246</identifier><identifier>PMID: 21653298</identifier><identifier>CODEN: CIDIEL</identifier><language>eng</language><publisher>Oxford: Oxford University Press</publisher><subject>and Commentaries ; ARTICLES AND COMMENTARIES ; Bacterial diseases ; Bacterial diseases of the digestive system and abdomen ; Bacterial infections ; Bacterial Toxins ; Biological and medical sciences ; Chi-Square Distribution ; Clostridium ; Clostridium difficile ; Clostridium difficile - isolation & purification ; Clostridium Infections - classification ; Clostridium Infections - diagnosis ; Clostridium Infections - epidemiology ; Cross-Sectional Studies ; Cytotoxicity Tests, Immunologic ; Discharge ; Disease outbreaks ; Enzyme-Linked Immunosorbent Assay ; Epidemiology ; Gastroenterology. Liver. Pancreas. Abdomen ; Health Care Surveys ; Hospital admissions ; Hospitals ; Human bacterial diseases ; Humans ; Infections ; Infectious diseases ; International Classification of Diseases ; Medical diagnosis ; Medical sciences ; Other diseases. Semiology ; Patient admissions ; Prevalence ; Preventive medicine ; Stomach. Duodenum. Small intestine. Colon. Rectum. Anus ; Surveillance ; Toxins ; United States - epidemiology</subject><ispartof>Clinical infectious diseases, 2011-07, Vol.53 (1), p.20-25</ispartof><rights>Copyright © 2011 Oxford University Press on behalf of the Infectious Diseases Society of America</rights><rights>The Author 2011. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com. 2011</rights><rights>2015 INIST-CNRS</rights><rights>The Author 2011. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved.</rights><rights>Copyright University of Chicago, acting through its Press Jul 1, 2011</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c486t-c42326ee7d80141521321d67172a4bab8aafec35e6a9d73a11827a2a853628313</citedby><cites>FETCH-LOGICAL-c486t-c42326ee7d80141521321d67172a4bab8aafec35e6a9d73a11827a2a853628313</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/23030998$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/23030998$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,314,776,780,799,881,1578,27901,27902,57992,58225</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=24350294$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21653298$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Dubberke, Erik R.</creatorcontrib><creatorcontrib>Butler, Anne M.</creatorcontrib><creatorcontrib>Nyazee, Humaa A.</creatorcontrib><creatorcontrib>Reske, Kimberly A.</creatorcontrib><creatorcontrib>Yokoe, Deborah S.</creatorcontrib><creatorcontrib>Mayer, Jeanmarie</creatorcontrib><creatorcontrib>Mangino, Julie E.</creatorcontrib><creatorcontrib>Khan, Yosef M.</creatorcontrib><creatorcontrib>Fraser, Victoria J.</creatorcontrib><creatorcontrib>Centers for Disease Control and Prevention Epicenters Program</creatorcontrib><creatorcontrib>Centers for Disease Control and Prevention Epicenters Program</creatorcontrib><title>The Impact of ICD-9-CM Code Rank Order on the Estimated Prevalence of Clostridium difficile Infections</title><title>Clinical infectious diseases</title><addtitle>Clin Infect Dis</addtitle><description>Background. US estimates of the Clostridium difficile infection (CDI) burden have utilized International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes. Whether ICD-9-CM code rank order affects CDI prevalence estimates is important because the National Hospital Discharge Survey (NHDS) and the Nationwide Inpatient Sample (NIS) have varying limits on the number of ICD-9-CM codes collected. Methods. ICD-9-CM codes for CDI (008.45), C. difficile toxin assay results, and dates of admission and discharge were collected from electronic hospital databases for adult patients admitted to 4 hospitals in the United States from July 2000 through June 2006. CDI prevalence per 1000 discharges was calculated and compared for NHDS and NIS limits and toxin assay results from the same hospitals. CDI prevalence estimates were compared using the χ² test, and the test of equality was used to compare slopes. Results. CDI prevalence measured by NIS criteria was significantly higher than that measured using NHDS criteria (10.7 cases per 1000 discharges versus 9.4 cases per 1000 discharges; P < .001) in the 4 hospitals. CDI prevalence measured by toxin assay results was 9.4 cases per 1000 discharges (P = .57 versus NHDS). However, the CDI prevalence increased more rapidly over time when measured according to the NHDS criteria than when measured according to toxin assay results (β = 1.09 versus 0.84; P = .008). Conclusions. Compared with the NHDS definition, the NIS definition captured 12% more CDI cases and reported significantly higher CDI rates. Rates calculated using toxin assay results were not different from rates calculated using NHDS criteria, but CDI prevalence appeared to increase more rapidly when measured by NHDS criteria than when measured by toxin assay results.</description><subject>and Commentaries</subject><subject>ARTICLES AND COMMENTARIES</subject><subject>Bacterial diseases</subject><subject>Bacterial diseases of the digestive system and abdomen</subject><subject>Bacterial infections</subject><subject>Bacterial Toxins</subject><subject>Biological and medical sciences</subject><subject>Chi-Square Distribution</subject><subject>Clostridium</subject><subject>Clostridium difficile</subject><subject>Clostridium difficile - isolation & purification</subject><subject>Clostridium Infections - classification</subject><subject>Clostridium Infections - diagnosis</subject><subject>Clostridium Infections - epidemiology</subject><subject>Cross-Sectional Studies</subject><subject>Cytotoxicity Tests, Immunologic</subject><subject>Discharge</subject><subject>Disease outbreaks</subject><subject>Enzyme-Linked Immunosorbent Assay</subject><subject>Epidemiology</subject><subject>Gastroenterology. Liver. Pancreas. Abdomen</subject><subject>Health Care Surveys</subject><subject>Hospital admissions</subject><subject>Hospitals</subject><subject>Human bacterial diseases</subject><subject>Humans</subject><subject>Infections</subject><subject>Infectious diseases</subject><subject>International Classification of Diseases</subject><subject>Medical diagnosis</subject><subject>Medical sciences</subject><subject>Other diseases. Semiology</subject><subject>Patient admissions</subject><subject>Prevalence</subject><subject>Preventive medicine</subject><subject>Stomach. Duodenum. Small intestine. Colon. Rectum. Anus</subject><subject>Surveillance</subject><subject>Toxins</subject><subject>United States - epidemiology</subject><issn>1058-4838</issn><issn>1537-6591</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kc9vFCEcxYnR2B968a4hTbyYTOULA8NcTJqx6iY1NaaeCQuMZZ2FFZgm_vdls2tXLz0A34QP7z3yEHoF5BxIz94bb-tKtBVP0DFw1jWC9_C0zoTLppVMHqGTnFeEAEjCn6MjCoIz2stjNN7cOrxYb7QpOI54MXxs-mb4iodoHf6uwy98naxLOAZcKnmZi1_r4iz-ltydnlwwbvtumGIuyVs_r7H14-iNn6puGJ0pPob8Aj0b9ZTdy_15in58urwZvjRX158Xw8VVY1opSt0po8K5zkoCLXAKjIIVHXRUt0u9lFpXRcad0L3tmK7_oZ2mWnImqGTATtGHne5mXq6dNS6UpCe1STV1-qOi9ur_m-Bv1c94pxgAoXIrcLYXSPH37HJRqzinUDMr2QHtWhCyQu92kEkx5-TGBwMgaluJqpWoXSUVfvNvpAf0bwcVeLsHdDZ6GpMOxucD1zJOaN8euDhvHjd8veNWucR00GGEkb763QPIrano</recordid><startdate>20110701</startdate><enddate>20110701</enddate><creator>Dubberke, Erik R.</creator><creator>Butler, Anne M.</creator><creator>Nyazee, Humaa A.</creator><creator>Reske, Kimberly A.</creator><creator>Yokoe, Deborah S.</creator><creator>Mayer, Jeanmarie</creator><creator>Mangino, Julie E.</creator><creator>Khan, Yosef M.</creator><creator>Fraser, Victoria J.</creator><general>Oxford University Press</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>7QL</scope><scope>7T2</scope><scope>7T7</scope><scope>7U7</scope><scope>7U9</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>H94</scope><scope>K9.</scope><scope>M7N</scope><scope>P64</scope><scope>5PM</scope></search><sort><creationdate>20110701</creationdate><title>The Impact of ICD-9-CM Code Rank Order on the Estimated Prevalence of Clostridium difficile Infections</title><author>Dubberke, Erik R. ; Butler, Anne M. ; Nyazee, Humaa A. ; Reske, Kimberly A. ; Yokoe, Deborah S. ; Mayer, Jeanmarie ; Mangino, Julie E. ; Khan, Yosef M. ; Fraser, Victoria J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c486t-c42326ee7d80141521321d67172a4bab8aafec35e6a9d73a11827a2a853628313</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>and Commentaries</topic><topic>ARTICLES AND COMMENTARIES</topic><topic>Bacterial diseases</topic><topic>Bacterial diseases of the digestive system and abdomen</topic><topic>Bacterial infections</topic><topic>Bacterial Toxins</topic><topic>Biological and medical sciences</topic><topic>Chi-Square Distribution</topic><topic>Clostridium</topic><topic>Clostridium difficile</topic><topic>Clostridium difficile - isolation & purification</topic><topic>Clostridium Infections - classification</topic><topic>Clostridium Infections - diagnosis</topic><topic>Clostridium Infections - epidemiology</topic><topic>Cross-Sectional Studies</topic><topic>Cytotoxicity Tests, Immunologic</topic><topic>Discharge</topic><topic>Disease outbreaks</topic><topic>Enzyme-Linked Immunosorbent Assay</topic><topic>Epidemiology</topic><topic>Gastroenterology. Liver. Pancreas. Abdomen</topic><topic>Health Care Surveys</topic><topic>Hospital admissions</topic><topic>Hospitals</topic><topic>Human bacterial diseases</topic><topic>Humans</topic><topic>Infections</topic><topic>Infectious diseases</topic><topic>International Classification of Diseases</topic><topic>Medical diagnosis</topic><topic>Medical sciences</topic><topic>Other diseases. Semiology</topic><topic>Patient admissions</topic><topic>Prevalence</topic><topic>Preventive medicine</topic><topic>Stomach. Duodenum. Small intestine. Colon. Rectum. Anus</topic><topic>Surveillance</topic><topic>Toxins</topic><topic>United States - epidemiology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dubberke, Erik R.</creatorcontrib><creatorcontrib>Butler, Anne M.</creatorcontrib><creatorcontrib>Nyazee, Humaa A.</creatorcontrib><creatorcontrib>Reske, Kimberly A.</creatorcontrib><creatorcontrib>Yokoe, Deborah S.</creatorcontrib><creatorcontrib>Mayer, Jeanmarie</creatorcontrib><creatorcontrib>Mangino, Julie E.</creatorcontrib><creatorcontrib>Khan, Yosef M.</creatorcontrib><creatorcontrib>Fraser, Victoria J.</creatorcontrib><creatorcontrib>Centers for Disease Control and Prevention Epicenters Program</creatorcontrib><creatorcontrib>Centers for Disease Control and Prevention Epicenters Program</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>Bacteriology Abstracts (Microbiology B)</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Toxicology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Clinical infectious diseases</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dubberke, Erik R.</au><au>Butler, Anne M.</au><au>Nyazee, Humaa A.</au><au>Reske, Kimberly A.</au><au>Yokoe, Deborah S.</au><au>Mayer, Jeanmarie</au><au>Mangino, Julie E.</au><au>Khan, Yosef M.</au><au>Fraser, Victoria J.</au><aucorp>Centers for Disease Control and Prevention Epicenters Program</aucorp><aucorp>Centers for Disease Control and Prevention Epicenters Program</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Impact of ICD-9-CM Code Rank Order on the Estimated Prevalence of Clostridium difficile Infections</atitle><jtitle>Clinical infectious diseases</jtitle><addtitle>Clin Infect Dis</addtitle><date>2011-07-01</date><risdate>2011</risdate><volume>53</volume><issue>1</issue><spage>20</spage><epage>25</epage><pages>20-25</pages><issn>1058-4838</issn><eissn>1537-6591</eissn><coden>CIDIEL</coden><abstract>Background. US estimates of the Clostridium difficile infection (CDI) burden have utilized International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes. Whether ICD-9-CM code rank order affects CDI prevalence estimates is important because the National Hospital Discharge Survey (NHDS) and the Nationwide Inpatient Sample (NIS) have varying limits on the number of ICD-9-CM codes collected. Methods. ICD-9-CM codes for CDI (008.45), C. difficile toxin assay results, and dates of admission and discharge were collected from electronic hospital databases for adult patients admitted to 4 hospitals in the United States from July 2000 through June 2006. CDI prevalence per 1000 discharges was calculated and compared for NHDS and NIS limits and toxin assay results from the same hospitals. CDI prevalence estimates were compared using the χ² test, and the test of equality was used to compare slopes. Results. CDI prevalence measured by NIS criteria was significantly higher than that measured using NHDS criteria (10.7 cases per 1000 discharges versus 9.4 cases per 1000 discharges; P < .001) in the 4 hospitals. CDI prevalence measured by toxin assay results was 9.4 cases per 1000 discharges (P = .57 versus NHDS). However, the CDI prevalence increased more rapidly over time when measured according to the NHDS criteria than when measured according to toxin assay results (β = 1.09 versus 0.84; P = .008). Conclusions. Compared with the NHDS definition, the NIS definition captured 12% more CDI cases and reported significantly higher CDI rates. Rates calculated using toxin assay results were not different from rates calculated using NHDS criteria, but CDI prevalence appeared to increase more rapidly when measured by NHDS criteria than when measured by toxin assay results.</abstract><cop>Oxford</cop><pub>Oxford University Press</pub><pmid>21653298</pmid><doi>10.1093/cid/cir246</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1058-4838 |
| ispartof | Clinical infectious diseases, 2011-07, Vol.53 (1), p.20-25 |
| issn | 1058-4838 1537-6591 |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_3110281 |
| source | Jstor Complete Legacy; Oxford University Press Journals All Titles (1996-Current); MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Alma/SFX Local Collection |
| subjects | and Commentaries ARTICLES AND COMMENTARIES Bacterial diseases Bacterial diseases of the digestive system and abdomen Bacterial infections Bacterial Toxins Biological and medical sciences Chi-Square Distribution Clostridium Clostridium difficile Clostridium difficile - isolation & purification Clostridium Infections - classification Clostridium Infections - diagnosis Clostridium Infections - epidemiology Cross-Sectional Studies Cytotoxicity Tests, Immunologic Discharge Disease outbreaks Enzyme-Linked Immunosorbent Assay Epidemiology Gastroenterology. Liver. Pancreas. Abdomen Health Care Surveys Hospital admissions Hospitals Human bacterial diseases Humans Infections Infectious diseases International Classification of Diseases Medical diagnosis Medical sciences Other diseases. Semiology Patient admissions Prevalence Preventive medicine Stomach. Duodenum. Small intestine. Colon. Rectum. Anus Surveillance Toxins United States - epidemiology |
| title | The Impact of ICD-9-CM Code Rank Order on the Estimated Prevalence of Clostridium difficile Infections |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-16T08%3A53%3A11IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-jstor_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=The%20Impact%20of%20ICD-9-CM%20Code%20Rank%20Order%20on%20the%20Estimated%20Prevalence%20of%20Clostridium%20difficile%20Infections&rft.jtitle=Clinical%20infectious%20diseases&rft.au=Dubberke,%20Erik%20R.&rft.aucorp=Centers%20for%20Disease%20Control%20and%20Prevention%20Epicenters%20Program&rft.date=2011-07-01&rft.volume=53&rft.issue=1&rft.spage=20&rft.epage=25&rft.pages=20-25&rft.issn=1058-4838&rft.eissn=1537-6591&rft.coden=CIDIEL&rft_id=info:doi/10.1093/cid/cir246&rft_dat=%3Cjstor_pubme%3E23030998%3C/jstor_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=871274168&rft_id=info:pmid/21653298&rft_jstor_id=23030998&rft_oup_id=10.1093/cid/cir246&rfr_iscdi=true |