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

Chin Med J (Engl). 2023 Apr 5;136(7):874-876. doi: 10.1097/CM9.0000000000002168.

Huai-Yu Wang^{1

2}, Jian Du¹, Yu Yang¹, Hongbo Lin³, Beiyan Bao⁴, Guohui Ding^{1

5}, Chao Yang^{6

7}, Guilan Kong^{1

7}, Luxia Zhang^{1

6

7}

¹ National Institute of Health Data Science at Peking University, Beijing 100191, China.
² School of Public Health, Peking University, Beijing 100191, China.
³ Yinzhou District Center for Disease Control and Prevention, Ningbo, Zhejiang 315199, China.
⁴ Renal Division, Ningbo Yinzhou No. 2 Hospital; Ningbo Urology and Nephrology Hospital, Ningbo, Zhejiang 315192, China.
⁵ School of Computer Science, Shenyang Aerospace University, Shenyang, Liaoning 110136, China.
⁶ Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China.
⁷ Advanced Institute of Information Technology, Peking University, Hangzhou, Zhejiang 311215, China.

No abstract available

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