In:
Public Health Reports, SAGE Publications, Vol. 131, No. 3 ( 2016-05), p. 483-490
Abstract:
Transcripts from admission chest radiographs could aid in identification of pneumonia cases for public health surveillance. We assessed the reliability of radiographic data abstraction and performance of radiographic key terms to identify pneumonia in patients hospitalized with laboratory-confirmed influenza virus infection. Methods. We used data on patients hospitalized with laboratory-confirmed influenza virus infection from October 2008 through December 2009 from 10 geographically diverse U.S. study sites participating in the Influenza Hospitalization Surveillance Network (FluSurv-NET). Radiographic key terms (i.e., bronchopneumonia, consolidation, infiltrate, airspace density, and pleural effusion) were abstracted from final impressions of chest radiograph reports. We assessed the reliability of radiographic data abstraction by examining the percent agreement and Cohen's κ statistic between clinicians and surveillance staff members. Using a composite reference standard for presence or absence of pneumonia based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes and discharge summary data, we calculated sensitivity, specificity, positive predictive value (PPV), and percent agreement for individual and combined radiographic key terms. Results. For each radiographic key term, the percent agreement between clinicians and surveillance staff members ranged from 89.4% to 98.6% and Cohen's κ ranged from 0.46 (moderate) to 0.84 (almost perfect). The combination of bronchopneumonia or consolidation or infiltrate or airspace density terms had sensitivity of 66.5%, specificity of 89.2%, PPV of 80.4%, and percent agreement of 80.1%. Adding pleural effusion did not result in significant changes in sensitivity, specificity, PPV, or percent agreement. Conclusion. Radiographic key terms abstracted by surveillance staff members from final impressions of chest radiograph reports had moderate to almost perfect reliability and could be used to identify pneumonia among patients hospitalized with laboratory-confirmed influenza virus infection. This method can inform pneumonia surveillance and aid in public health response.
Type of Medium:
Online Resource
ISSN:
0033-3549
,
1468-2877
DOI:
10.1177/003335491613100314
Language:
English
Publisher:
SAGE Publications
Publication Date:
2016
detail.hit.zdb_id:
2017700-8
SSG:
20,1
SSG:
27
Permalink
