TY - JOUR
T1 - Acute vital signs changes are underrepresented by a conventional electronic health record when compared with automatically acquired data in a single-center tertiary pediatric cardiac intensive care unit
AU - Lowry, Adam W.
AU - Futterman, Craig A.
AU - Gazit, Avihu Z.
N1 - Publisher Copyright:
© 2022 The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved.
PY - 2022/7/1
Y1 - 2022/7/1
N2 - Objective: We sought to evaluate the fidelity with which the patient's clinical state is represented by the electronic health record (EHR) flow sheet vital signs data compared to a commercially available automated data aggregation platform in a pediatric cardiac intensive care unit (CICU) Methods: This is a retrospective observational study of heart rate (HR), systolic blood pressure (SBP), respiratory rate (RR), and pulse oximetry (SpO2) data archived in a conventional EHR and an automated data platform for 857 pediatric patients admitted postoperatively to a tertiary pediatric CICU. Automated data captured for 72 h after admission were analyzed for significant HR, SBP, RR, and SpO2 deviations from baseline (events). Missed events were identified when the EHR failed to reflect the events reflected in the automated platform Results: Analysis of 132 054 622 data entries, including 264 966 (0.2%) EHR entries and 131 789 656 (99.8%) automated entries, identified 15 839 HR events, 5851 SBP events, 9648 RR events, and 2768 SpO2 events lasting 3-60 min; these events were missing in the EHR 48%, 58%, 50%, and 54% of the time, respectively. Subanalysis identified 329 physiologically implausible events (eg, likely operator or device error), of which 104 (32%) were nonetheless documented in the EHR Conclusion: In this single-center retrospective study of CICU patients, EHR vital sign documentation was incomplete compared to an automated data aggregation platform. Significant events were underrepresented by the conventional EHR, regardless of event duration. Enrichment of the EHR with automated data aggregation capabilities may improve representation of patient condition.
AB - Objective: We sought to evaluate the fidelity with which the patient's clinical state is represented by the electronic health record (EHR) flow sheet vital signs data compared to a commercially available automated data aggregation platform in a pediatric cardiac intensive care unit (CICU) Methods: This is a retrospective observational study of heart rate (HR), systolic blood pressure (SBP), respiratory rate (RR), and pulse oximetry (SpO2) data archived in a conventional EHR and an automated data platform for 857 pediatric patients admitted postoperatively to a tertiary pediatric CICU. Automated data captured for 72 h after admission were analyzed for significant HR, SBP, RR, and SpO2 deviations from baseline (events). Missed events were identified when the EHR failed to reflect the events reflected in the automated platform Results: Analysis of 132 054 622 data entries, including 264 966 (0.2%) EHR entries and 131 789 656 (99.8%) automated entries, identified 15 839 HR events, 5851 SBP events, 9648 RR events, and 2768 SpO2 events lasting 3-60 min; these events were missing in the EHR 48%, 58%, 50%, and 54% of the time, respectively. Subanalysis identified 329 physiologically implausible events (eg, likely operator or device error), of which 104 (32%) were nonetheless documented in the EHR Conclusion: In this single-center retrospective study of CICU patients, EHR vital sign documentation was incomplete compared to an automated data aggregation platform. Significant events were underrepresented by the conventional EHR, regardless of event duration. Enrichment of the EHR with automated data aggregation capabilities may improve representation of patient condition.
KW - critical care
KW - electronic health records
KW - medical informatics
KW - patient safety
KW - quality improvement
UR - http://www.scopus.com/inward/record.url?scp=85132049982&partnerID=8YFLogxK
U2 - 10.1093/jamia/ocac033
DO - 10.1093/jamia/ocac033
M3 - Article
C2 - 35301538
AN - SCOPUS:85132049982
SN - 1067-5027
VL - 29
SP - 1183
EP - 1190
JO - Journal of the American Medical Informatics Association
JF - Journal of the American Medical Informatics Association
IS - 7
ER -