Cheng-Yang Hsieh1, Chih-Hung Chen2, Chung-Yi Li3, Ming-Liang Lai4. 1. Stroke Center and Department of Neurology, Tainan Sin Lau Hospital, Tainan, Taiwan; Institute of Clinical Pharmacy and Pharmaceutical Science, National Cheng Kung University, Tainan, Taiwan. 2. Stroke Center, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Department of Neurology, College of Medicine, National Cheng Kung University, Tainan, Taiwan. Electronic address: lchih@mail.ncku.edu.tw. 3. Institute of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Department of Public Health, College of Public Health, China Medical University, Taichung, Taiwan. 4. Institute of Clinical Pharmacy and Pharmaceutical Science, National Cheng Kung University, Tainan, Taiwan; Stroke Center, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Department of Neurology, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Abstract
BACKGROUND/ PURPOSE: The National Health Insurance Research Database, which uses claims data from hospitals contracted with the National Health Insurance (NHI) program in Taiwan, has been widely used for stroke research. The diagnostic accuracy of the NHI claims data with regard to acute ischemic stroke (AIS) has rarely been validated. The aim of this study was to validate the diagnosis of AIS in NHI claims data using the Taiwan Stroke Registry (TSR) as a reference. METHODS: We retrieved patients' data with a discharge diagnosis of AIS [five-digit International Classification of Diseases Code, 9(th) version (ICD-9 code): 433xx or 434xx] in a single medical center from August 2006 to December 2008. We then linked these patients to the TSR to validate their AIS diagnosis in the claims data. The positive predictive value (PPV) and sensitivity were determined. RESULTS: We reviewed the claims data of 1736 consecutive AIS patients, of whom 1299 (74.8%) were linked successfully to the stroke registry database. After reviewing the medical records and imaging results of other patients not linked to the registry database (n = 437), 235 patients were found to have had an AIS. The PPV was 88.4% [95% confidence interval (CI): 86.8-89.8%] and sensitivity was 97.3% (95% CI: 96.4-98.1%). Forty-four (21.8%) of the false-positive cases (n = 202) were coded as 433x0 or 434x0. CONCLUSION: The PPV of a diagnosis of AIS in the NHI claims data was high. Using five-digit ICD-9 codes to identify AIS cases will markedly decrease the false-positive rate compared with using the commonly used three-digit method.
BACKGROUND/ PURPOSE: The National Health Insurance Research Database, which uses claims data from hospitals contracted with the National Health Insurance (NHI) program in Taiwan, has been widely used for stroke research. The diagnostic accuracy of the NHI claims data with regard to acute ischemic stroke (AIS) has rarely been validated. The aim of this study was to validate the diagnosis of AIS in NHI claims data using the Taiwan Stroke Registry (TSR) as a reference. METHODS: We retrieved patients' data with a discharge diagnosis of AIS [five-digit International Classification of Diseases Code, 9(th) version (ICD-9 code): 433xx or 434xx] in a single medical center from August 2006 to December 2008. We then linked these patients to the TSR to validate their AIS diagnosis in the claims data. The positive predictive value (PPV) and sensitivity were determined. RESULTS: We reviewed the claims data of 1736 consecutive AIS patients, of whom 1299 (74.8%) were linked successfully to the stroke registry database. After reviewing the medical records and imaging results of other patients not linked to the registry database (n = 437), 235 patients were found to have had an AIS. The PPV was 88.4% [95% confidence interval (CI): 86.8-89.8%] and sensitivity was 97.3% (95% CI: 96.4-98.1%). Forty-four (21.8%) of the false-positive cases (n = 202) were coded as 433x0 or 434x0. CONCLUSION: The PPV of a diagnosis of AIS in the NHI claims data was high. Using five-digit ICD-9 codes to identify AIS cases will markedly decrease the false-positive rate compared with using the commonly used three-digit method.