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Diagnostic Prevalence of Ankylosing Spondylitis Using Computerized Health Care Data, 1996 to 2009: Underrecognition
Jeffrey R Curtis1, Leslie R Harrold2, Maryam M Asgari3
1Professor of Medicine in the Department of Clinical Immunology and Rheumatology at the University of Alabama at Birmingham. jcurtis@uab.edu.
Introduction:
Few studies have assessed the prevalence and features of axial spondyloarthritis (axSpA) and ankylosing spondylitis in diverse, population-based, community settings.
Objectives:
We used computerized diagnoses to estimate the prevalence of axSpA and ankylosing spondylitis in Kaiser Permanente Northern California (KPNC).
Methods:
We identified persons aged 18 years or older with 1 or more International Classification of Diseases, Ninth Revision (ICD-9) diagnosis Code 720.X (ankylosing spondylitis and other inflammatory spondylopathies) in clinical encounter data from 1996 through 2009 to estimate the prevalence of axSpA and ankylosing spondylitis. We reviewed medical records to confirm the diagnosis in a random sample and estimated the positive predictive value of computerized data to identify confirmed cases using various case definitions.
Results:
In the computerized data, 5568 adults had diagnostic codes indicating axSpA. On the basis of our case-finding approach using a single physician diagnosis code for ICD-9 720.X, the point prevalence of these conditions, standardized to the 2000 US Census, was 2.26 per 1000 persons for axSpA and 1.07 per 1000 for ankylosing spondylitis. Less than half of suspected cases saw a rheumatologist. The most specific algorithm for confirmed ankylosing spondylitis required 2 or more computerized diagnoses assigned by a rheumatologist, with 67% sensitivity (95% confidence interval, 64%-69%) and 81% positive predictive value (95% confidence interval, 79%-83%).
Conclusions:
Observed prevalence in the KPNC population, compared with national estimates for axSpA and ankylosing spondylitis, suggests there is substantial underrecognition of these conditions in routine clinical practice. However, use of computerized data is able to identify true cases of ankylosing spondylitis, facilitating population-based research.
