Use of International Classification of Diseases, Ninth Revision Clinical Modification Codes and Medication Use Data to Identify Nosocomial Clostridium difficile Infection

2009 ◽  
Vol 30 (11) ◽  
pp. 1070-1076 ◽  
Author(s):  
Mia Schmiedeskamp ◽  
Spencer Harpe ◽  
Ronald Polk ◽  
Michael Oinonen ◽  
Amy Pakyz
Keyword(s):  
Drug Therapy ◽  
Clostridium Difficile ◽  
Positive Predictive Value ◽  
Predictive Value ◽  
International Classification Of Diseases ◽  
International Classification ◽  
Adult Patients ◽  
Classification Of Diseases ◽  
Sensitivity Specificity

Objective.The International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code for Clostridium difficile infection (CDI) is used for surveillance of CDI. However, the ICD-9-CM code alone cannot separate nosocomial cases from cases acquired outside the institution. The purpose of this study was to determine whether combining the ICD-9-CM code with medication treatment data for CDI in hospitalized patients could enable us to distinguish between patients with nosocomial CDI and patients who were admitted with CDI. The primary objective was to compare the sensitivity, specificity, and predictive value of using the combination of ICD-9-CM code for CDI and CDI treatment records to identify cases of nosocomial CDI with the sensitivity, specificity, and predictive value of using the ICD-9-CM code alone.Design.Validation sample cross-sectional study.Setting.Academic health center.Methods.Administrative claims data from July 1, 2004, to June 30, 2005, were queried to identify adults discharged with an ICD-9-CM code for CDI and to find documentation of CDI therapy with oral vancomycin or metronidazole. Laboratory and medical records were queried to identify symptomatic CDI toxin-positive adult patients with nosocomial CDI and were compared with records of patients whose cases were predicted to be nosocomial by means of ICD-9-CM code and CDI therapy data.Results.Of 23,920 adult patients discharged from the hospital, 62 had nosocomial CDI according to symptoms and toxin assay. The sensitivity of the ICD-9-CM code alone for identifying nosocomial CDI was 96.8%, the specificity was 99.6%, the positive predictive value was 40.8%, and the negative predictive value was 100%. When CDI drug therapy was included with the ICD-9-CM code, the sensitivity ranged from 58.1% to 85.5%, specificity was virtually unchanged, and the range in positive predictive value was 37.9%–80.0%.Conclusion.Combining the ICD-9-CM code for CDI with drug therapy information increased the positive predictive value for nosocomial CDI but decreased the sensitivity.

Predictive Ability of Positive Clinical Culture Results and International Classification of Diseases, Ninth Revision, to Identify and Classify Noninvasive Staphylococcus aureus Infections: A Validation Study

2010 ◽  
Vol 31 (07) ◽  
pp. 694-700 ◽  
Author(s):  
LaRee A. Tracy ◽  
Jon P. Furuno ◽  
Anthony D. Harris ◽  
Mary Singer ◽  
Patricia Langenberg ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Confidence Interval ◽  
Predictive Value ◽  
Positive Culture ◽  
International Classification Of Diseases ◽  
International Classification ◽  
Clinical Culture ◽  
Classification Of Diseases ◽  
Definition Of

Objective.To develop and validate an algorithm to identify and classify noninvasive infections due toStaphylococcus aureusby using positive clinical culture results and administrative data.Design.Retrospective cohort study.Setting.Veterans Affairs Maryland Health Care System.Methods.Data were collected retrospectively on allS. aureusclinical culture results from samples obtained from nonsterile body sites during October 1998 through September 2008 and associated administrative claims records. An algorithm was developed to identify noninvasive infections on the basis of a uniqueS. aureus-positive culture result from a nonsterile site sample with a matchingInternational Classification of Diseases, Ninth Revision (ICD-9-CM), code for infection at time of sampling. Medical records of a subset of cases were reviewed to find the proportion of true noninvasive infections (cases that met the Centers for Disease Control and Prevention National Healthcare Safety Network [NHSN] definition of infection). Positive predictive value (PPV) and negative predictive value (NPV) were calculated for all infections and according to body site of infection.Results.We identified 4,621 uniqueS. aureus-positive culture results, of which 2,816 (60.9%) results met our algorithm definition of noninvasiveS. aureusinfection and 1,805 (39.1%) results lacked a matchingICD-9-CMcode. Among 96 cases that met our algorithm criteria for noninvasiveS. aureusinfection, 76 also met the NHSN criteria (PPV, 79.2% [95% confidence interval, 70.0%–86.1%]). Among 98 cases that failed to meet the algorithm criteria, 80 did not meet the NHSN criteria (NPV, 81.6% [95% confidence interval, 72.8%–88.0%]). The PPV of all culture results was 55.4%. The algorithm was most predictive for skin and soft-tissue infections and bone and joint infections.Conclusion.When culture-based surveillance methods are used, the addition of administrativeICD-9-CMcodes for infection can increase the PPV of true noninvasiveS. aureusinfection over the use of positive culture results alone.

scholarly journals Predictive Ability of Positive Clinical Culture Results and International Classification of Diseases, Ninth Revision, to Identify and Classify Noninvasive Staphylococcus aureus Infections: A Validation Study

2010 ◽  
Vol 31 (7) ◽  
pp. 694-700 ◽  
Author(s):  
LaRee A. Tracy ◽  
Jon P. Furuno ◽  
Anthony D. Harris ◽  
Mary Singer ◽  
Patricia Langenberg ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Confidence Interval ◽  
Predictive Value ◽  
Positive Culture ◽  
International Classification Of Diseases ◽  
International Classification ◽  
Clinical Culture ◽  
Classification Of Diseases ◽  
Definition Of

Objective.To develop and validate an algorithm to identify and classify noninvasive infections due to Staphylococcus aureus by using positive clinical culture results and administrative data.Design.Retrospective cohort study.Setting.Veterans Affairs Maryland Health Care System.Methods.Data were collected retrospectively on all S. aureus clinical culture results from samples obtained from nonsterile body sites during October 1998 through September 2008 and associated administrative claims records. An algorithm was developed to identify noninvasive infections on the basis of a unique S. aureus-positive culture result from a nonsterile site sample with a matching International Classification of Diseases, Ninth Revision (ICD-9-CM), code for infection at time of sampling. Medical records of a subset of cases were reviewed to find the proportion of true noninvasive infections (cases that met the Centers for Disease Control and Prevention National Healthcare Safety Network [NHSN] definition of infection). Positive predictive value (PPV) and negative predictive value (NPV) were calculated for all infections and according to body site of infection.Results.We identified 4,621 unique S. aureus-positive culture results, of which 2,816 (60.9%) results met our algorithm definition of noninvasive S. aureus infection and 1,805 (39.1%) results lacked a matching ICD-9-CM code. Among 96 cases that met our algorithm criteria for noninvasive S. aureus infection, 76 also met the NHSN criteria (PPV, 79.2% [95% confidence interval, 70.0%–86.1%]). Among 98 cases that failed to meet the algorithm criteria, 80 did not meet the NHSN criteria (NPV, 81.6% [95% confidence interval, 72.8%–88.0%]). The PPV of all culture results was 55.4%. The algorithm was most predictive for skin and soft-tissue infections and bone and joint infections.Conclusion.When culture-based surveillance methods are used, the addition of administrative ICD-9-CM codes for infection can increase the PPV of true noninvasive S. aureus infection over the use of positive culture results alone.

Angststörungen – von der ICD-10 zur ICD-11

2020 ◽  
pp. 1-5
Author(s):  
Timo D. Vloet ◽  
Marcel Romanos
Keyword(s):  
Mental Disorders ◽  
International Classification Of Diseases ◽  
International Classification ◽  
Statistical Manual ◽  
Diagnostic And Statistical Manual ◽  
Dsm 5 ◽  
Classification Of Diseases ◽  
Icd 10

Zusammenfassung. Hintergrund: Nach 12 Jahren Entwicklung wird die 11. Version der International Classification of Diseases (ICD-11) von der Weltgesundheitsorganisation (WHO) im Januar 2022 in Kraft treten. Methodik: Im Rahmen eines selektiven Übersichtsartikels werden die Veränderungen im Hinblick auf die Klassifikation von Angststörungen von der ICD-10 zur ICD-11 zusammenfassend dargestellt. Ergebnis: Die diagnostischen Kriterien der generalisierten Angststörung, Agoraphobie und spezifischen Phobien werden angepasst. Die ICD-11 wird auf Basis einer Lebenszeitachse neu organisiert, sodass die kindesaltersspezifischen Kategorien der ICD-10 aufgelöst werden. Die Trennungsangststörung und der selektive Mutismus werden damit den „regulären“ Angststörungen zugeordnet und können zukünftig auch im Erwachsenenalter diagnostiziert werden. Neu ist ebenso, dass verschiedene Symptomdimensionen der Angst ohne kategoriale Diagnose verschlüsselt werden können. Diskussion: Die Veränderungen im Bereich der Angsterkrankungen umfassen verschiedene Aspekte und sind in der Gesamtschau nicht unerheblich. Positiv zu bewerten ist die Einführung einer Lebenszeitachse und Parallelisierung mit dem Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Schlussfolgerungen: Die entwicklungsbezogene Neuorganisation in der ICD-11 wird auch eine verstärkte längsschnittliche Betrachtung von Angststörungen in der Klinik sowie Forschung zur Folge haben. Damit rückt insbesondere die Präventionsforschung weiter in den Fokus.

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