Abstract
BackgroundIdentifying acute ischemic stroke (AIS) among potential stroke cases is crucial for stroke research based on claims data. However, the accuracy of using the diagnostic codes of the International Classification of Diseases 10th revision was less than expected.MethodsFrom the National Health Insurance Service (NHIS) claims data, stroke cases admitted to the hospitals participating in the multicenter stroke registry (Clinical Research Collaboration for Stroke in Korea, CRCS-K) during the study period with principal or additional diagnosis codes of I60-I64 on the 10th revision of International Classification of Diseases were extracted. The datasets were randomly divided into development and validation sets with a ratio of 7:3. A stroke identification algorithm using the claims data was developed and validated through the linkage between the extracted datasets and the registry database.ResultsAltogether, 40,443 potential cases were extracted from the NHIS claims data, of which 31.7% were certified as AIS through linkage with the CRCS-K database. We selected 17 key identifiers from the claims data and developed 37 conditions through combinations of those key identifiers. The key identifiers comprised brain CT, MRI, use of tissue plasminogen activator, endovascular treatment, carotid endarterectomy or stenting, antithrombotics, anticoagulants, etc. The sensitivity, specificity, and diagnostic accuracy of the algorithm were 81.2%, 82.9%, and 82.4% in the development set, and 80.2%, 82.0%, and 81.4% in the validation set, respectively.ConclusionsOur stroke identification algorithm may be useful to grasp stroke burden in Korea. However, further efforts to refine the algorithm are necessary.
Highlights
From the National Health Insurance Service (NHIS) claims data, stroke cases admitted to the hospitals participating in the multicenter stroke registry (Clinical Research Collaboration for Stroke in Korea, CRCS-K) during the study period with principal or additional diagnosis codes of I60-I64 on the 10th revision of International Classification of Diseases were extracted
40,443 potential cases were extracted from the National Health Insurance System (NHIS) claims data, of which 31.7% were certified as acute ischemic stroke (AIS) through linkage with the CRCS-K database
Most cases missed validation.[6,7,8, 14,15,16, 18]. This problem is mostly caused by difficulty to validate the process of identifying stroke cases using claims data through the classic epidemiologic methods, such as review of medical records or direct interview of patients or their families due to a large amount of case numbers and accessibility to the patients or their medical records
Summary
There are crucial limitations in previous claims data-based studies with respect to identification of stroke cases.[6,7,8, 14,15,16,17,18,19,20] Most cases missed validation.[6,7,8, 14,15,16, 18] This problem is mostly caused by difficulty to validate the process of identifying stroke cases using claims data through the classic epidemiologic methods, such as review of medical records or direct interview of patients or their families due to a large amount of case numbers and accessibility to the patients or their medical records If these obstacles could be overcome by linkage with the already validated registry database, the use of claims data in stroke research will be escalated. The accuracy of using the diagnostic codes of the International Classification of Diseases 10th revision was less than expected
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have