Validation of Stroke and Trombolytic Terapy in Korean National Health Insurance Claim Data
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Background and Purpose Te claims data of the Korean National Health Insurance (NHI) system can be useful in stroke research. Te aim of this study was to validate the accuracy of hospital discharge data used for NHI claims in identifying acute stroke and use of thrombolytic therapy. Methods Te hospital discharge data of 1,811 patients with stroke-related diagnosis codes were obtained from Jeju National University Hospital (JNUH) and Seoul Medical Center (SMC). Tree algorithms were tested to identify discharges with acute stroke [ischemic stroke (IS), intracranial hemorrhage (ICH), or subarachnoid hemorrhage (SAH)]: 1) all diagnosis codes up to nine positions, 2) one primary diagnosis and one secondary diagnosis, and 3) only one primary diagnosis code. Reviews of medical records were considered the gold standards. Results Overall, the degree of agreement (κ) was higher for algorithms 1 and 2 than for algorithm 3, and the sensitivity and specifcity of the frst two algorithms for IS and SAH were both >90%, with almost perfect agreement (κ=0.83–0.84) in the JNUH data set. Regarding ICH, only algorithm 1 yielded an almost perfect agreement (κ=0.82). In the SMC data set, almost perfect agreement was found for both ICH and SAH in all three algorithms. In contrast, the three algorithms yielded a range of agreement levels, though all substantial, for IS. Almost perfect agreement was obtained for use of thrombolytic therapy in both data sets (κ=0.91– 0.99). Conclusions Discharge with hemorrhagic stroke and use of thrombolytic therapy were identifed with high reliability in administrative discharge data. A substantial level of agreement was also obtained for IS, despite variation between the algorithms and data sets.
Abstract
Background and Purpose Te claims data of the Korean National Health Insurance (NHI) system can be useful in stroke research. Te aim of this study was to validate the accuracy of hospital discharge data used for NHI claims in identifying acute stroke and use of thrombolytic therapy. Methods Te hospital discharge data of 1,811 patients with stroke-related diagnosis codes were obtained from Jeju National University Hospital (JNUH) and Seoul Medical Center (SMC). Tree algorithms were tested to identify discharges with acute stroke [ischemic stroke (IS), intracranial hemorrhage (ICH), or subarachnoid hemorrhage (SAH)]: 1) all diagnosis codes up to nine positions, 2) one primary diagnosis and one secondary diagnosis, and 3) only one primary diagnosis code. Reviews of medical records were considered the gold standards. Results Overall, the degree of agreement (κ) was higher for algorithms 1 and 2 than for algorithm 3, and the sensitivity and specifcity of the frst two algorithms for IS and SAH were both >90%, with almost perfect agreement (κ=0.83–0.84) in the JNUH data set. Regarding ICH, only algorithm 1 yielded an almost perfect agreement (κ=0.82). In the SMC data set, almost perfect agreement was found for both ICH and SAH in all three algorithms. In contrast, the three algorithms yielded a range of agreement levels, though all substantial, for IS. Almost perfect agreement was obtained for use of thrombolytic therapy in both data sets (κ=0.91– 0.99). Conclusions Discharge with hemorrhagic stroke and use of thrombolytic therapy were identifed with high reliability in administrative discharge data. A substantial level of agreement was also obtained for IS, despite variation between the algorithms and data sets.
참고문헌 (25)
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