Rapid identification of chronic kidney disease in electronic health record database using computable phenotype combining a common data model.

Author: Huai-Yu WANG ¹ ; Jian DU ¹ ; Yu YANG ¹ ; Hongbo LIN ² ; Beiyan BAO ^{3
,

4} ; Guohui DING ¹ ; Chao YANG ⁵ ; Guilan KONG ¹ ; Luxia ZHANG ¹
Author Information

1. National Institute of Health Data Science at Peking University, Beijing 100191, China.
2. Yinzhou District Center for Disease Control and Prevention, Ningbo, Zhejiang 315199, China.
3. Renal Division, Ningbo Yinzhou No. 2 Hospital
4. Ningbo Urology and Nephrology Hospital, Ningbo, Zhejiang 315192, China.
5. Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China.
Publication Type:Letter
MeSH: Humans; Electronic Health Records; Phenotype; Renal Insufficiency, Chronic/epidemiology*; Databases, Factual; Algorithms
From: Chinese Medical Journal 2023;136(7):874-876
CountryChina
Language:English