Introduction In response to increased syphilis rates in the U.S., the Department of Defense conducted a surveillance study of incident syphilis cases to determine the burden of syphilis in active duty service members. Syphilis diagnosis was derived from administrative medical encounter data (ICD-9) and reportable medical events (RME) during 2010–2015. The results demonstrated a considerable increase in primary and secondary syphilis, with only a minor elevation in latent disease. These results suggested either insufficient screening practices in the MHS or errors in diagnosis or coding of medical encounters. We performed a validation study to evaluate the sensitivity of administrative and RME data to identify incident syphilis cases and to estimate the burden of syphilis in the U.S. Army.
Methods An Army-specific 10% sample of 2976 incident syphilis cases identified in the parent military surveillance analysis was provided for validation. The electronic medical record was reviewed and data was systematically collected on clinical presentation, medical history, prior syphilis testing, and clinical assessment at each encounter, diagnosis, and treatment.
Results Of the 300 cases reviewed, 96 (32%) were identified as errors in medical coding or diagnosis and were not incident cases. Only 22% of cases were correctly staged as primary or secondary syphilis. Significant differences were found during validation in all areas of staging between the parent analysis and the validation study. Variability was seen in the HIV positive subpopulation and in those with previous diagnosis of syphilis.
Conclusion Although administrative health system data is readily available, it may lack specificity for syphilis diagnosis. Pitfalls in medical encounter coding, diagnostic uncertainty by providers, interpretation of labs, and overly sensitive inclusion criteria may misrepresent the magnitude of disease and classification of latent versus active clinical disease in the population. Caution should be used in tracking syphilis using administrative medical encounter data.
Disclosure of Interest Statement: The content of this publication is the sole responsibility of the authors and does not necessarily reflect the views, assertions, opinions or policies of the Uniformed Services University of the Health Sciences (USUHS ), the Department of Defense (DoD), or the Departments of the Army, Navy, or Air Force. Mention of trade names, commercial products, or organisations does not imply endorsement by the U.S. Government
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