Cohort identification of axial spondyloarthritis in a large healthcare dataset: current and future methods

Abstract

BackgroundBig data research is important for studying uncommon diseases in real-world settings. Most big data studies in axial spondyloarthritis (axSpA) have been limited to populations identified with billing codes for ankylosing spondylitis (AS). axSpA is a more inclusive concept, and reliance on AS codes does not produce a comprehensive axSpA study population. The first objective was to describe our process for establishing an appropriate sample of patients with and without axSpA for developing accurate axSpA identification methods. The second objective was to determine the classification performance of AS billing codes against the chart-reviewed axSpA reference standard.MethodsVeteran Health Affairs clinical and administrative data, between January 2005 and June 2015, were used to randomly select patients with clinical phenotypes that represented high, moderate, and low likelihoods of an axSpA diagnosis. With chart review, the sampled patients were classified as Yes axSpA, No axSpA or Uncertain axSpA, and these classification assignments were used as the reference standard for determining the positive predictive value (PPV) and sensitivity of AS ICD-9 codes for axSpA.ResultsSix hundred patients were classified as Yes axSpA (26.8%), No axSpA (68.3%), or Uncertain axSpA (4.8%). The PPV and sensitivity of an AS ICD-9 code for axSpA were 83.3% and 57.3%, respectively.ConclusionsStandard methods of identifying axSpA patients in a large dataset lacked sensitivity. An appropriate sample of patients with and without axSpA was established and characterized for developing novel axSpA identification methods that are anticipated to enable previously impractical big data research.

Clinical features in primary care electronic records before diagnosis of ankylosing spondylitis: a nested case-control study

“…2 Plots of odds ratio for individual features over three years, by gap between the end of the three year window and the date of diagnosis / matching. Dotted lines indicate 95% confidence intervals for odds ratios secondary care records so we could not assess the reliability of GPs' diagnosis of AS, however in our experience GP practices tend not to code such diagnoses without specialist opinion and in a recent US study a over 80% of a sample of coded diagnoses of AS were confirmed on chart review [18]. It should be noted that the annual incidence (approximately 4 per 100,000 per year in adults aged 18-60 years) is compatible with the lifetime prevalence of approximately 15 per 10,000 observed in other studies [19,20].…”

Clinical features in primary care electronic records before diagnosis of Ankylosing Spondylitis: a nested case-control study.

“…This meant that confidence intervals were wide and it is possible that we lacked statistical power to detect some potentially meaningful associations. The data was from stand-alone primary care records with no linkage to secondary care records so we could not assess the reliability of GPs' diagnosis of ankylosing spondylitis, however in our experience GP practices tend not to code such diagnoses without specialist opinion and in a recent US study a over 80% of a sample of coded diagnoses of AS were confirmed on chart review (18). It should be noted that the annual incidence (approximately 5 per 100,000 per year in adults aged 18-60 years) is compatible with the lifetime prevalence of approximately 15 per 10,000 observed in other studies (19,20).…”

Clinical features in primary care electronic records before diagnosis of Ankylosing Spondylitis: a nested case-control study.

“…This meant that confidence intervals were wide and it is possible that we lacked statistical power to detect some potentially meaningful associations. The data was from stand-alone primary care records with no linkage to secondary care records so we could not assess the reliability of GPs' diagnosis of AS, however in our experience GP practices tend not to code such diagnoses without specialist opinion and in a recent US study a over 80% of a sample of coded diagnoses of AS were confirmed on chart review (18). It should be noted that the annual incidence (approximately 4 per 100,000 per year in adults aged 18-60 years) is compatible with the lifetime prevalence of approximately 15 per 10,000 observed in other studies (19,20).…”