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How well do ICD-9 physician claim diagnostic codes identify confirmed pertussis cases in Alberta, Canada? A Canadian Immunization Research Network (CIRN) Study

Authors :
Sumana Fathima
Kimberley A. Simmonds
Steven J. Drews
Lawrence W. Svenson
Jeffrey C. Kwong
Salaheddin M. Mahmud
Susan Quach
Caitlin Johnson
Kevin L. Schwartz
Natasha S. Crowcroft
Margaret L. Russell
For the Canadian Immunization Research Network (CIRN) Provincial Collaborative Network Vaccine Effectiveness Working Group
Source :
BMC Health Services Research, Vol 17, Iss 1, Pp 1-7 (2017)
Publication Year :
2017
Publisher :
BMC, 2017.

Abstract

Abstract Background Rates of Bordetella pertussis have been increasing in Alberta, Canada despite vaccination programs. Waning immunity from existing acellular component vaccines may be contributing to this. Vaccine effectiveness can be estimated using a variety of data sources including diagnostic codes from physician billing claims, public health records, reportable disease and laboratory databases. We sought to determine if diagnostic codes from billing claims (administrative data) are adequately sensitive and specific to identify pertussis cases among patients who had undergone disease-specific laboratory testing. Methods Data were extracted for 2004–2014 from a public health communicable disease database that contained data on patients under investigation for B. pertussis (both those who had laboratory tests and those who were epidemiologically linked to laboratory-confirmed cases) in Alberta, Canada. These were deterministically linked using a unique lifetime person identifier to the provincial billing claims database, which contains International Classification of Disease version 9 (ICD-9) diagnostic codes for physician visits. We examined visits within 90 days of laboratory testing. ICD-9 codes 033 (whooping cough), 033.0 (Bordetella pertussis), 033.1 (B. parapertussis), 033.8 (whooping cough, other specified organism), and 033.9 (whooping cough, other unspecified organism) in any of the three diagnostic fields for a claim were classified as being pertussis-specific codes. We calculated sensitivity, specificity, positive (PPV) and negative (NPV) predictive values. Results We identified 22,883 unique patients under investigation for B. pertussis. Of these, 22,095 underwent laboratory testing. Among those who had a laboratory test, 2360 tested positive for pertussis. The sensitivity of a pertussis-specific ICD-9 code for identifying a laboratory-confirmed case was 38.6%, specificity was 76.9%, PPV was 16.0%, and NPV was 91.6%. Conclusion ICD-9 codes from physician billing claims data have low sensitivity and moderate specificity to identify laboratory-confirmed pertussis among persons tested for pertussis.

Details

Language :
English
ISSN :
14726963
Volume :
17
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Health Services Research
Publication Type :
Academic Journal
Accession number :
edsdoj.91d0d8a4407b4fb3b0bbe108c5ba3fd3
Document Type :
article
Full Text :
https://doi.org/10.1186/s12913-017-2321-1