TY - JOUR
T1 - Development of data dictionary for neonatal intensive care unit
T2 - advancement towards a better critical care unit
AU - Singh, Harpreet
AU - Kaur, Ravneet
AU - Saluja, Satish
AU - Cho, Su Jin
AU - Kaur, Avneet
AU - Pandey, Ashish Kumar
AU - Gupta, Shubham
AU - Das, Ritu
AU - Kumar, Praveen
AU - Palma, Jonathan
AU - Yadav, Gautam
AU - Sun, Yao
N1 - Funding Information:
This research project is funded privately by support from Child Health Imprints (CHIL) Pte. Ltd., Singapore. HS and RK are co-founders and board members of Child Health Imprints India Private Limited. AKP received a grant from Child Health Imprints India Private Limited for research. The remaining authors have no financial relationships relevant to this article to disclose.
Publisher Copyright:
VC The Author(s) 2019
PY - 2020
Y1 - 2020
N2 - Background: Critical care units (CCUs) with extensive use of various monitoring devices generate massive data. To utilize the valuable information of these devices; data are collected and stored using systems like clinical information system and laboratory information management system. These systems are proprietary, allow limited access to their database and, have the vendor-specific clinical implementation. In this study, we focus on developing an open-source web-based meta-data repository for CCU representing stay of the patient with relevant details. Methods: After developing the web-based open-source repository named data dictionary (DD), we analyzed prospective data from 2 sites for 4 months for data quality dimensions (completeness, timeliness, validity, accuracy, and consistency), morbidity, and clinical outcomes. We used a regression model to highlight the significance of practice variations linked with various quality indicators. Results: DD with 1555 fields (89.6% categorical and 11.4% text fields) is presented to cover the clinical workflow of a CCU. The overall quality of 1795 patient days data with respect to standard quality dimensions is 87%. The data exhibit 88% completeness, 97% accuracy, 91% timeliness, and 94% validity in terms of representing CCU processes. The data scores only 67% in terms of consistency. Furthermore, quality indicators and practice variations are strongly correlated (P < 0.05). Conclusion: This study documents DD for standardized data collection in CCU. DD provides robust data and insights for audit purposes and pathways for CCU to target practice improvements leading to specific quality improvements.
AB - Background: Critical care units (CCUs) with extensive use of various monitoring devices generate massive data. To utilize the valuable information of these devices; data are collected and stored using systems like clinical information system and laboratory information management system. These systems are proprietary, allow limited access to their database and, have the vendor-specific clinical implementation. In this study, we focus on developing an open-source web-based meta-data repository for CCU representing stay of the patient with relevant details. Methods: After developing the web-based open-source repository named data dictionary (DD), we analyzed prospective data from 2 sites for 4 months for data quality dimensions (completeness, timeliness, validity, accuracy, and consistency), morbidity, and clinical outcomes. We used a regression model to highlight the significance of practice variations linked with various quality indicators. Results: DD with 1555 fields (89.6% categorical and 11.4% text fields) is presented to cover the clinical workflow of a CCU. The overall quality of 1795 patient days data with respect to standard quality dimensions is 87%. The data exhibit 88% completeness, 97% accuracy, 91% timeliness, and 94% validity in terms of representing CCU processes. The data scores only 67% in terms of consistency. Furthermore, quality indicators and practice variations are strongly correlated (P < 0.05). Conclusion: This study documents DD for standardized data collection in CCU. DD provides robust data and insights for audit purposes and pathways for CCU to target practice improvements leading to specific quality improvements.
KW - Data analytics
KW - Data dictionary
KW - Electronic health record
KW - Neonatal intensive care unit
KW - Neonate health
KW - Quality indicators
UR - http://www.scopus.com/inward/record.url?scp=85102480255&partnerID=8YFLogxK
U2 - 10.1093/JAMIAOPEN/OOZ064
DO - 10.1093/JAMIAOPEN/OOZ064
M3 - Article
AN - SCOPUS:85102480255
SN - 2574-2531
VL - 3
SP - 21
EP - 30
JO - JAMIA Open
JF - JAMIA Open
IS - 1
ER -