Validation of ICD-10 codes shows intracranial venous thrombosis incidence to be higher than previously reported

Abstract

Background: Intracranial venous thrombosis (ICVT) accounts for around 0.5% of all stroke cases. There have been no previously published studies of the International Classification of Diseases, Tenth Edition (ICD-10) validation for the identification of ICVT admissions in adults. Objective: The aims of this study were to validate and quantify the performance of the ICD-10 coding system for identifying cases of ICVT in adults and to derive an estimate of incidence. Method: Administrative data were collected for all patients admitted to a regional neurosciences centre over a 5-year period. We searched for the following ICD-10 codes at any position: G08.X (intracranial and intraspinal phlebitis and thrombophlebitis), I67.6 (non-pyogenic thrombosis of intracranial venous system), I63.6 (cerebral infarction due to cerebral venous thrombosis, non-pyogenic), O22.5 (cerebral venous thrombosis in pregnancy) and O87.3 (cerebral venous thrombosis in the puerperium). Results: Sixty-five admissions were identified by at least one of the relevant ICD-10 codes. The overall positive predictive value (PPV) for confirmed ICVT from all of the admissions combined was 92.3% (60 out of 65) with the results for each code as follows: G08.X 91.5% (54 of 59), O22.5 100% (4 of 4), I67.6 100% (1 of 1), I63.6 100% (1 of 1) and O87.3 100% (1 of 1). There were 40 unique cases of ICVT over a 5-year period giving an annual incidence of ICVT of 5 per million. Conclusions: All codes gave a high PPV. Implications for practice: As demonstrated in previous studies, the incidence of ICVT may be higher than previously thought.

Cerebral venous thrombosis and portal vein thrombosis: A retrospective cohort study of 537,913 COVID-19 cases

“…The analyses were repeated in four different ways to test the robustness of the findings to the choice of outcome, cohort, covariates, and statistical model. First, analyses were repeated after broadening the diagnostic criteria for CVT to include I63.6 (cerebral infarction due to central thrombosis, non-pyogenic), G08 (intracranial and intraspinal phlebitis and thrombophlebitis), O22.5 (CVT in pregnancy) and O87.3 (CVT in the puerperium), in line with recent epidemiological studies that have used this definition of CVT [ 13 , 14 ].…”

Background rates of hospitalizations and emergency department visits for selected thromboembolic and coagulation disorders in Ontario, Canada, 2015 to 2020, to inform COVID-19 vaccine safety surveillance

“…Additionally, we used recorded diagnostic codes in administrative data without information on clinical and/or diagnostic confirmation, and the validity of these data are imperfect, which may result in under or overestimation. However, we used previously validated codes [15][16][17][18] or equivalent codes 14 to improve the accuracy of case ascertainment in administrative data and there is no reason to believe that there would be substantial changes in the direction or magnitude of misdiagnosis between study years. The quality of DAD hospitalization data has been previously evaluated.…”

“…Where available, we used codes that have been previously validated. [14][15][16][17][18] We used the Canadian Institute for Health Information (CIHI)…”

The role of health classifications in health information management

“…Researchers rely on the coded data for much of their work and are therefore interested in the integrity of the data and the relevance of the classifications to their sphere of interest. Several articles in this Virtual Special Issue report on studies to reconcile the information in the medical record or in other databases with the coded data held in admitted patient datasets (Handley and Emsley, 2020; Murray et al, 2017; Nguyen et al, 2019; Sveticic et al, 2020; Trinh et al, 2017, 2018). They identify a range of issues associated with the coded data, including that in some cases conditions are not being coded and in others that clinical codes do not provide the specificity needed for good research.…”