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Ming-Jen Tsai,1,* Cheng-Han Tsai,2,3,* Ru-Chiou Pan,4 Chi-Feng Hsu,1 Sheng-Feng Sung5,6 1Department of Emergency Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, Taiwan; 2Department of Emergency Medicine, Chiayi Branch, Taichung Veteran’s General Hospital, Chiayi City, Taiwan; 3Department of Information Management, Institute of Healthcare Information Management, National Chung Cheng University, Chiayi County, Taiwan; 4Clinical Data Center, Department of Medical Research, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, Taiwan; 5Division of Neurology, Department of Internal Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, Taiwan; 6Department of Nursing, Min-Hwei Junior College of Health Care Management, Tainan, Taiwan*These authors contributed equally to this workCorrespondence: Sheng-Feng Sung, Division of Neurology, Department of Internal Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, Taiwan, Tel +886 5 276 5041 Ext 7283, Fax +886 5 278 4257, Email sfusng@cych.org.tw; richard.sfsung@gmail.comPurpose: Taiwan’s national health insurance (NHI) database is a valuable resource for large-scale epidemiological and long-term survival research for out-of-hospital cardiac arrest (OHCA). We developed and validated case definition algorithms for OHCA based on the International Classification of Diseases (ICD) diagnostic codes and billing codes for NHI reimbursement.Patients and Methods: Claims data and medical records of all emergency department visits from 2010 to 2020 were retrieved from the hospital’s research-based database. Death-related diagnostic codes and keywords were used to identify potential OHCA cases, which were ascertained by chart reviews. We tested the performance of the developed OHCA algorithms and validated them on an external dataset.Results: The algorithm defining OHCA as any cardiac arrest (CA)-related ICD code in the first three diagnosis fields performed the best with a sensitivity of 89.5% (95% confidence interval [CI], 88.2– 90.7%), a positive predictive value (PPV) of 90.6% (95% CI, 89.4– 91.8%), and a kappa value of 0.900 (95% CI, 0.891– 0.909). The second-best algorithm consists of any CA-related ICD code in any diagnosis field with a billing code for triage acuity level 1, achieving a sensitivity of 85.6% (95% CI, 84.1– 87.0%), a PPV of 93.6% (95% CI, 92.5– 94.5), and a kappa value of 0.894 (95% CI, 0.884– 0.903). Both algorithms performed well in external validation. In subgroup analyses, the former algorithm performed the best in adult patients, outpatient claims, and during the ICD-9 era. The latter algorithm performed the best in the inpatient claims and during the ICD-10 era. The best algorithm for identifying pediatric OHCAs was any CA-related ICD code in the first three diagnosis fields with a billing code for triage acuity level 1.Conclusion: Our results may serve as a reference for future OHCA studies using the Taiwan NHI database.Keywords: administrative claims data, diagnosis, ICD-9-CM, ICD-10-CM, out-of-hospital cardiac arrest, validation |
