Frontiers in Pediatrics (Oct 2021)
Data Quality Improvement and Internal Data Audit of the Chinese Neonatal Network Data Collection System
- Jianhua Sun,
- Yun Cao,
- Mingyan Hei,
- Huiqing Sun,
- Laishuan Wang,
- Wei Zhou,
- Xiafang Chen,
- Siyuan Jiang,
- Huayan Zhang,
- Huayan Zhang,
- Xiaolu Ma,
- Hui Wu,
- Xiaoying Li,
- Yuan Shi,
- Xinyue Gu,
- Yanchen Wang,
- Tongling Yang,
- Yulan Lu,
- Wenhao Zhou,
- Chao Chen,
- Shoo K. Lee,
- Shoo K. Lee,
- Shoo K. Lee,
- Shoo K. Lee,
- Shoo K. Lee,
- Lizhong Du,
- The Chinese Neonatal Network,
- Shoo K. Lee,
- Chao Chen,
- Lizhong Du,
- Wenhao Zhou,
- Yun Cao,
- Falin Xu,
- Xiuying Tian,
- Huayan Zhang,
- Yong Ji,
- Zhankui Li,
- Jingyun Shi,
- Xindong Xue,
- Chuanzhong Yang,
- Dongmei Chen,
- Sannan Wang,
- Ling Liu,
- Xirong Gao,
- Hui Wu,
- Changyi Yang,
- Shuping Han,
- Ruobing Shan,
- Hong Jiang,
- Gang Qiu,
- Qiufen Wei,
- Rui Cheng,
- Wenqing Kang,
- Mingxia Li,
- Yiheng Dai,
- Lili Wang,
- Jiangqin Liu,
- Zhenlang Lin,
- Yuan Shi,
- Xiuyong Cheng,
- Jiahua Pan,
- Qin Zhang,
- Xing Feng,
- Qin Zhou,
- Long Li,
- Pingyang Chen,
- Xiaoying Li,
- Ling Yang,
- Deyi Zhuang,
- Yongjun Zhang,
- Jianhua Sun,
- Jinxing Feng,
- Li Li,
- Xinzhu Lin,
- Yinping Qiu,
- Kun Liang,
- Li Ma,
- Liping Chen,
- Liyan Zhang,
- Hongxia Song,
- Zhaoqing Yin,
- Mingyan Hei,
- Huiwen Huang,
- Jie Yang,
- Dong Li,
- Guofang Ding,
- Jimei Wang,
- Qianshen Zhang,
- Xiaolu Ma
Affiliations
- Jianhua Sun
- Department of Neonatology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Yun Cao
- Division of Neonatology, Children's Hospital of Fudan University, Shanghai, China
- Mingyan Hei
- Neonatal Center, Beijing Children's Hospital, Capital Medical University, Beijing, China
- Huiqing Sun
- Division of Neonatology, Henan Children's Hospital, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China
- Laishuan Wang
- Division of Neonatology, Children's Hospital of Fudan University, Shanghai, China
- Wei Zhou
- Division of Neonatology and Center for Newborn Care, Guangzhou Women and Children's Medical Center, Guangzhou, China
- Xiafang Chen
- Department of Neonatology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Siyuan Jiang
- Division of Neonatology, Children's Hospital of Fudan University, Shanghai, China
- Huayan Zhang
- Division of Neonatology and Center for Newborn Care, Guangzhou Women and Children's Medical Center, Guangzhou, China
- Huayan Zhang
- Department of Pediatrics, Children's Hospital of Philadelphia and University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
- Xiaolu Ma
- Division of Neonatology, The Children's Hospital of Zhejiang University School of Medicine, Hangzhou, China
- Hui Wu
- Division of Neonatology, The First Bethune Hospital of Jilin University, Changchun, China
- Xiaoying Li
- Division of Neonatology, Qilu Children's Hospital of Shandong University, Ji'nan, China
- Yuan Shi
- 0Division of Neonatology, Children's Hospital of Chongqing Medical University, Chongqing, China
- Xinyue Gu
- 1NHC Key Laboratory of Neonatal Diseases (Fudan University), Children's Hospital of Fudan University, Shanghai, China
- Yanchen Wang
- 1NHC Key Laboratory of Neonatal Diseases (Fudan University), Children's Hospital of Fudan University, Shanghai, China
- Tongling Yang
- Division of Neonatology, Children's Hospital of Fudan University, Shanghai, China
- Yulan Lu
- 2Center for Molecular Medicine, Pediatrics Research Institute, Children's Hospital of Fudan University, Shanghai, China
- Wenhao Zhou
- Division of Neonatology, Children's Hospital of Fudan University, Shanghai, China
- Chao Chen
- Division of Neonatology, Children's Hospital of Fudan University, Shanghai, China
- Shoo K. Lee
- 3Maternal-Infant Care Research Centre, Mount Sinai Hospital, Toronto, ON, Canada
- Shoo K. Lee
- 4Department of Pediatrics, Mount Sinai Hospital, Toronto, ON, Canada
- Shoo K. Lee
- 5Department of Pediatrics, University of Toronto, Toronto, ON, Canada
- Shoo K. Lee
- 6Department of Obstetrics and Gynecology, University of Toronto, Toronto, ON, Canada
- Shoo K. Lee
- 7Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Lizhong Du
- Division of Neonatology, The Children's Hospital of Zhejiang University School of Medicine, Hangzhou, China
- The Chinese Neonatal Network
- Shoo K. Lee
- Chao Chen
- Lizhong Du
- Wenhao Zhou
- Yun Cao
- Falin Xu
- Xiuying Tian
- Huayan Zhang
- Yong Ji
- Zhankui Li
- Jingyun Shi
- Xindong Xue
- Chuanzhong Yang
- Dongmei Chen
- Sannan Wang
- Ling Liu
- Xirong Gao
- Hui Wu
- Changyi Yang
- Shuping Han
- Ruobing Shan
- Hong Jiang
- Gang Qiu
- Qiufen Wei
- Rui Cheng
- Wenqing Kang
- Mingxia Li
- Yiheng Dai
- Lili Wang
- Jiangqin Liu
- Zhenlang Lin
- Yuan Shi
- Xiuyong Cheng
- Jiahua Pan
- Qin Zhang
- Xing Feng
- Qin Zhou
- Long Li
- Pingyang Chen
- Xiaoying Li
- Ling Yang
- Deyi Zhuang
- Yongjun Zhang
- Jianhua Sun
- Jinxing Feng
- Li Li
- Xinzhu Lin
- Yinping Qiu
- Kun Liang
- Li Ma
- Liping Chen
- Liyan Zhang
- Hongxia Song
- Zhaoqing Yin
- Mingyan Hei
- Huiwen Huang
- Jie Yang
- Dong Li
- Guofang Ding
- Jimei Wang
- Qianshen Zhang
- Xiaolu Ma
- DOI
- https://doi.org/10.3389/fped.2021.711200
- Journal volume & issue
-
Vol. 9
Abstract
Background: The Chinese Neonatal Network (CHNN) is a nationwide neonatal network that aims to improve clinical neonatal care quality and short- and long-term health outcomes of infants. This study aims to assess the quality of the Chinese Neonatal Network database by conducting an internal audit of data extraction.Methods: A data audit was performed by independently replicating the data collection and entry process in all 58 tertiary neonatal intensive care units (NICU) participating in the CHNN. Eighty-eight data elements selected for re-abstraction were classified into three categories (critical, important, less important), and agreement rates for original and re-abstracted data were predefined. Three to five records were randomly selected at each site for re-abstraction, including one short- (0–7 days), two medium- (8–28 days), and two long-stay (more than 28 days) cases. Agreement rates for each data item were calculated for individual NICUs and across the network, respectively.Results: A total of 283 cases and 24,904 data fields were re-abstracted. The agreement rates for original and re-abstracted data elements were 96.1% overall, and 97.2, 94.3, and 96.6% for critical, important, and less important data elements, respectively. Individual site variation for discrepancies ranged between 0.0 and 18.4% for all collected data elements.Conclusion: The completeness, precision, and quality of data in the CHNN database are high, providing assurance for multipurpose use, including health service evaluation, quality improvement, clinical trials, and other research.
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