Literature DB >> 18171183

Comparison of the use of administrative data and an active system for surveillance of invasive aspergillosis .

Douglas C Chang1, Lauren A Burwell, G Marshall Lyon, Peter G Pappas, Tom M Chiller, Kathleen A Wannemuehler, Scott K Fridkin, Benjamin J Park.   

Abstract

BACKGROUND: Administrative data, such as International Classification of Diseases, Ninth Revision (ICD-9) codes, are readily available and are an attractive option for surveillance and quality assessment within a single institution or for interinstitutional comparisons. To understand the usefulness of administrative data for the surveillance of invasive aspergillosis, we compared information obtained from a system based on ICD-9 codes with information obtained from an active, prospective surveillance system, which used more extensive case-finding methods (Transplant Associated Infection Surveillance Network).
METHODS: Patients with suspected invasive aspergillosis were identified by aspergillosis-related ICD-9 codes assigned to hematopoietic stem cell transplant recipients and solid organ transplant recipients at a single hospital from April 1, 2001, through January 31, 2005. Suspected cases were classified as proven or probable invasive aspergillosis by medical record review using standard definitions. We calculated the sensitivity and positive predictive value (PPV) of identifying invasive aspergillosis by individual ICD-9 codes and by combinations of codes.
RESULTS: The sensitivity of code 117.3 was modest (63% [95% confidence interval {CI}, 38%-84%]), as was the PPV (71% [95% CI, 44%-90%]); the sensitivity of code 117.9 was poor (32% [95% CI, 13%-57%]), as was the PPV (15% [95% CI, 6%-31%]). The sensitivity of codes 117.3 and 117.9 combined was 84% (95% CI, 60%-97%); the PPV of the combined codes was 30% (95% CI, 18%-44%). Overall, ICD-9 codes triggered a review of medical records for 64 medical patients, only 16 (25%) of whom had proven or probable invasive aspergillosis.
CONCLUSIONS: A surveillance system that involved multiple ICD-9 codes was sufficiently sensitive to identify most cases of invasive aspergillosis; however, the poor PPV of ICD-9 codes means that this approach is not adequate as the sole tool used to classify cases. Screening ICD-9 codes to trigger a medical record review might be a useful method of surveillance for invasive aspergillosis and quality assessment, although more investigation is needed.

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Year:  2008        PMID: 18171183     DOI: 10.1086/524324

Source DB:  PubMed          Journal:  Infect Control Hosp Epidemiol        ISSN: 0899-823X            Impact factor:   3.254


  16 in total

1.  Validity and Reliability of Administrative Coded Data for the Identification of Hospital-Acquired Infections: An Updated Systematic Review with Meta-Analysis and Meta-Regression Analysis.

Authors:  Olga Redondo-González; José María Tenías; Ángel Arias; Alfredo J Lucendo
Journal:  Health Serv Res       Date:  2017-04-11       Impact factor: 3.402

2.  Future directions in mucormycosis research.

Authors:  Dimitrios P Kontoyiannis; Russell E Lewis; Oliver Lortholary; Oliver Lotholary; Brad Spellberg; Georgios Petrikkos; Emmanuel Roilides; Emmanuel Roillides; Ashraf Ibrahim; Thomas J Walsh
Journal:  Clin Infect Dis       Date:  2012-02       Impact factor: 9.079

3.  Attributable hospital cost and antifungal treatment of invasive fungal diseases in high-risk hematology patients: an economic modeling approach.

Authors:  Michelle R Ananda-Rajah; Allen Cheng; C Orla Morrissey; Tim Spelman; Michael Dooley; A Munro Neville; Monica Slavin
Journal:  Antimicrob Agents Chemother       Date:  2011-02-28       Impact factor: 5.191

4.  Increased Risk of Infectious Complications in Older Patients With Indolent Non-Hodgkin Lymphoma Exposed to Bendamustine.

Authors:  Monica Fung; Eric Jacobsen; Arnold Freedman; Daniel Prestes; Dimitrios Farmakiotis; Xiangmei Gu; Paul L Nguyen; Sophia Koo
Journal:  Clin Infect Dis       Date:  2019-01-07       Impact factor: 9.079

5.  Toward Electronic Surveillance of Invasive Mold Diseases in Hematology-Oncology Patients: An Expert System Combining Natural Language Processing of Chest Computed Tomography Reports, Microbiology, and Antifungal Drug Data.

Authors:  Michelle R Ananda-Rajah; Christoph Bergmeir; François Petitjean; Monica A Slavin; Karin A Thursky; Geoffrey I Webb
Journal:  JCO Clin Cancer Inform       Date:  2017-11

6.  Estimation of Direct Healthcare Costs of Fungal Diseases in the United States.

Authors:  Kaitlin Benedict; Brendan R Jackson; Tom Chiller; Karlyn D Beer
Journal:  Clin Infect Dis       Date:  2019-05-17       Impact factor: 9.079

7.  Epidemiology and Outcomes of Hospitalizations With Invasive Aspergillosis in the United States, 2009-2013.

Authors:  Marya D Zilberberg; Brian H Nathanson; Rachel Harrington; James R Spalding; Andrew F Shorr
Journal:  Clin Infect Dis       Date:  2018-08-16       Impact factor: 9.079

8.  Evolving health information technology and the timely availability of visit diagnoses from ambulatory visits: a natural experiment in an integrated delivery system.

Authors:  Naomi S Bardach; Jie Huang; Richard Brand; John Hsu
Journal:  BMC Med Inform Decis Mak       Date:  2009-07-17       Impact factor: 2.796

9.  Increasing incidence of zygomycosis (mucormycosis), France, 1997-2006.

Authors:  Dounia Bitar; Dieter Van Cauteren; Fanny Lanternier; Eric Dannaoui; Didier Che; Francoise Dromer; Jean Claude Desenclos; Olivier Lortholary
Journal:  Emerg Infect Dis       Date:  2009-09       Impact factor: 6.883

10.  Epidemiology of cryptococcal meningitis in the US: 1997-2009.

Authors:  Vasilios Pyrgos; Amy E Seitz; Claudia A Steiner; D Rebecca Prevots; Peter R Williamson
Journal:  PLoS One       Date:  2013-02-15       Impact factor: 3.240

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