A “Patch” to the NYU Emergency Department Visit Algorithm
研究发现纽约大学急诊科就诊算法因ICD编码更新导致无法分类的病例比例从2006年的11.2%升至2012年的15.5%，通过补充新编码使2012年分类率提升43%。
OBJECTIVE: To document erosion in the New York University Emergency Department (ED) visit algorithm's capability to classify ED visits and to provide a "patch" to the algorithm. DATA SOURCES: The Nationwide Emergency Department Sample. STUDY DESIGN: We used bivariate models to assess whether the percentage of visits unclassifiable by the algorithm increased due to annual changes to ICD-9 diagnosis codes. We updated the algorithm with ICD-9 and ICD-10 codes added since 2001. PRINCIPAL FINDINGS: The percentage of unclassifiable visits increased from 11.2 percent in 2006 to 15.5 percent in 2012 (p < .01), because of new diagnosis codes. Our update improves the classification rate by 43 percent in 2012 (p < .01). CONCLUSIONS: Our patch significantly improves the precision and usefulness of the most commonly used ED visit classification system in health services research.