Data Quality Improvement and Internal Data Audit of the Chinese Neonatal Network Data Collection System
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...
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2021-10-01
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| Series: | Frontiers in Pediatrics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fped.2021.711200/full |
| _version_ | 1818984641275625472 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Jianhua Sun |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-20T18:22:14Z |
| format | Article |
| id | doaj.art-36ce2d41ea814c97b437a3ccd8056399 |
| institution | Directory Open Access Journal |
| issn | 2296-2360 |
| language | English |
| last_indexed | 2024-12-20T18:22:14Z |
| publishDate | 2021-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Pediatrics |
| spelling | doaj.art-36ce2d41ea814c97b437a3ccd80563992022-12-21T19:30:13ZengFrontiers Media S.A.Frontiers in Pediatrics2296-23602021-10-01910.3389/fped.2021.711200711200Data Quality Improvement and Internal Data Audit of the Chinese Neonatal Network Data Collection SystemJianhua Sun0Yun Cao1Mingyan Hei2Huiqing Sun3Laishuan Wang4Wei Zhou5Xiafang Chen6Siyuan Jiang7Huayan Zhang8Huayan Zhang9Xiaolu Ma10Hui Wu11Xiaoying Li12Yuan Shi13Xinyue Gu14Yanchen Wang15Tongling Yang16Yulan Lu17Wenhao Zhou18Chao Chen19Shoo K. Lee20Shoo K. Lee21Shoo K. Lee22Shoo K. Lee23Shoo K. Lee24Lizhong Du25The Chinese Neonatal NetworkShoo K. LeeChao ChenLizhong DuWenhao ZhouYun CaoFalin XuXiuying TianHuayan ZhangYong JiZhankui LiJingyun ShiXindong XueChuanzhong YangDongmei ChenSannan WangLing LiuXirong GaoHui WuChangyi YangShuping HanRuobing ShanHong JiangGang QiuQiufen WeiRui ChengWenqing KangMingxia LiYiheng DaiLili WangJiangqin LiuZhenlang LinYuan ShiXiuyong ChengJiahua PanQin ZhangXing FengQin ZhouLong LiPingyang ChenXiaoying LiLing YangDeyi ZhuangYongjun ZhangJianhua SunJinxing FengLi LiXinzhu LinYinping QiuKun LiangLi MaLiping ChenLiyan ZhangHongxia SongZhaoqing YinMingyan HeiHuiwen HuangJie YangDong LiGuofang DingJimei WangQianshen ZhangXiaolu MaDepartment of Neonatology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, ChinaDivision of Neonatology, Children's Hospital of Fudan University, Shanghai, ChinaNeonatal Center, Beijing Children's Hospital, Capital Medical University, Beijing, ChinaDivision of Neonatology, Henan Children's Hospital, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, ChinaDivision of Neonatology, Children's Hospital of Fudan University, Shanghai, ChinaDivision of Neonatology and Center for Newborn Care, Guangzhou Women and Children's Medical Center, Guangzhou, ChinaDepartment of Neonatology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, ChinaDivision of Neonatology, Children's Hospital of Fudan University, Shanghai, ChinaDivision of Neonatology and Center for Newborn Care, Guangzhou Women and Children's Medical Center, Guangzhou, ChinaDepartment of Pediatrics, Children's Hospital of Philadelphia and University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United StatesDivision of Neonatology, The Children's Hospital of Zhejiang University School of Medicine, Hangzhou, ChinaDivision of Neonatology, The First Bethune Hospital of Jilin University, Changchun, ChinaDivision of Neonatology, Qilu Children's Hospital of Shandong University, Ji'nan, China0Division of Neonatology, Children's Hospital of Chongqing Medical University, Chongqing, China1NHC Key Laboratory of Neonatal Diseases (Fudan University), Children's Hospital of Fudan University, Shanghai, China1NHC Key Laboratory of Neonatal Diseases (Fudan University), Children's Hospital of Fudan University, Shanghai, ChinaDivision of Neonatology, Children's Hospital of Fudan University, Shanghai, China2Center for Molecular Medicine, Pediatrics Research Institute, Children's Hospital of Fudan University, Shanghai, ChinaDivision of Neonatology, Children's Hospital of Fudan University, Shanghai, ChinaDivision of Neonatology, Children's Hospital of Fudan University, Shanghai, China3Maternal-Infant Care Research Centre, Mount Sinai Hospital, Toronto, ON, Canada4Department of Pediatrics, Mount Sinai Hospital, Toronto, ON, Canada5Department of Pediatrics, University of Toronto, Toronto, ON, Canada6Department of Obstetrics and Gynecology, University of Toronto, Toronto, ON, Canada7Dalla Lana School of Public Health, University of Toronto, Toronto, ON, CanadaDivision of Neonatology, The Children's Hospital of Zhejiang University School of Medicine, Hangzhou, ChinaBackground: 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.https://www.frontiersin.org/articles/10.3389/fped.2021.711200/fullinternal data auditneonatal databasedata quality improvementneonatal networkpreterm infant |
| spellingShingle | 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 Data Quality Improvement and Internal Data Audit of the Chinese Neonatal Network Data Collection System Frontiers in Pediatrics internal data audit neonatal database data quality improvement neonatal network preterm infant |
| title | Data Quality Improvement and Internal Data Audit of the Chinese Neonatal Network Data Collection System |
| title_full | Data Quality Improvement and Internal Data Audit of the Chinese Neonatal Network Data Collection System |
| title_fullStr | Data Quality Improvement and Internal Data Audit of the Chinese Neonatal Network Data Collection System |
| title_full_unstemmed | Data Quality Improvement and Internal Data Audit of the Chinese Neonatal Network Data Collection System |
| title_short | Data Quality Improvement and Internal Data Audit of the Chinese Neonatal Network Data Collection System |
| title_sort | data quality improvement and internal data audit of the chinese neonatal network data collection system |
| topic | internal data audit neonatal database data quality improvement neonatal network preterm infant |
| url | https://www.frontiersin.org/articles/10.3389/fped.2021.711200/full |
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