Evidence map›Paper›PMID 35689135›Full record

ArticleNeurocritical care2022

Neurocritical Care Performance Measures Derived from Electronic Health Record Data are Feasible and Reveal Site-Specific Variation: A CHoRUS Pilot Project.

Sophie E Ack, Shamelia Y Loiseau, Guneeti Sharma, Joshua N Goldstein, India A Lissak, Sarah M Duffy, Edilberto Amorim, Paul Vespa, Joseph Randall Moorman, Xiao Hu and 5 more

Abstract read
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Article in Neurocritical care, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

15 authors.

Sophie E AckDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Shamelia Y LoiseauDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Guneeti SharmaDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Joshua N GoldsteinDepartment of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA.
India A LissakDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Sarah M DuffyDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA.
Edilberto AmorimDepartment of Neurology, University of California, San Francisco, San Francisco, CA, USA.
Paul VespaDepartment of Neurology, University of California, Los Angeles, Los Angeles, CA, USA.
Joseph Randall MoormanDepartment of Medicine, Cardiovascular Division, University of Virginia, Charlottesville, VA, USA.
Xiao HuSchool of Nursing and Center for Data Science, Emory University, Atlanta, GA, USA.
Gilles ClermontDepartment of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Soojin ParkDepartments of Neurology and Biomedical Informatics, Columbia University, New York, NY, USA.
Rishikesan KamaleswaranDepartment of Biomedical Informatics, Emory University, Atlanta, GA, USA.
Brandon P ForemanDepartment of Neurology, University of Cincinnati, Cincinnati, OH, USA.
Eric S RosenthalDepartment of Neurology, Massachusetts General Hospital, Boston, MA, USA. erosenthal@mgh.harvard.edu.ORCID http://orcid.org/0000-0003-3900-356X

Funding

The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) Public Engagement CoreU54NS100064 · NINDS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ENGEL, JEROME NONE, GALANOPOULOU, ARISTEA S · 2017 to 2021
$21.7M
Predictive Informatics Monitoring in the Neonatal Intensive Care UnitR01HD072071 · NICHD · UNIVERSITY OF VIRGINIA · PI KAREN D FAIRCHILD, Brynne Archer Sullivan · 2014 to 2026
$7.6M
Predicting Patient Instability Noninvasively for Nursing Care-Two (PPINNC-2)R01NR013912 · NINR · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI AL-ZAITI, SALAH S, CLERMONT, GILLES · 2012 to 2025
$7.0M
ELECTRO-BOOST: Electroencephalography for cerebral trauma recovery and oxygenationR01NS117904 · NINDS · YALE UNIVERSITY · PI DING, KAN, GILMORE, EMILY · 2020 to 2025
$3.2M
Learning to Predict Delayed Cerebral Ischemia with Novel Continuous Cerebral Arterial State IndexR01NS113541 · NINDS · EMORY UNIVERSITY · PI HU, XIAO, VESPA, PAUL M · 2020 to 2025
$3.0M
Sepsis Physiomarkers for Appropriate Risk Knowledge of monitored patients in the ICU (SPARK-ICU)R01GM139967 · NIGMS · EMORY UNIVERSITY · PI KAMALESWARAN, RISHIKESAN · 2021 to 2025
$2.8M
Integrate Dynamic System Model and Machine Learning for Calibration-Free Noninvasive ICPR01NS106905 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HU, XIAO · 2018 to 2022
$2.8M
AI driven acute renal replacement therapy - (AID-ART)R01DK131586 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CLERMONT, GILLES, KASHANI, KIANOUSH B · 2021 to 2024
$2.5M
Physiology-driven seizure management post-cardiac arrestK23NS119794 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI AMORIM, EDILBERTO · 2021 to 2025
$1.1M
Real-Time Prediction of Delayed Cerebral Ischemia after Subarachnoid HemorrhageK23NS105950 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI ROSENTHAL, ERIC S. · 2018 to 2022
$1.0M
The Impact of Intracranial Pressure on Cortical Functioning and Cognitive Outcome after Traumatic Brain InjuryK23NS101123 · NINDS · UNIVERSITY OF CINCINNATI · PI FOREMAN, BRANDON · 2017 to 2020
$797k
Machine Learning to Optimize Management of Acute Hydrocephalus PatientsR21NS113055 · NINDS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI PARK, SOOJIN · 2020 to 2020
$446k
NICHD NIH HHS R01 HD072071NIDDK NIH HHS R01 DK131586NIGMS NIH HHS R01 GM139967NINDS NIH HHS K23 NS101123NINDS NIH HHS K23 NS105950NINDS NIH HHS K23 NS119794NINDS NIH HHS R01 NS106905NINDS NIH HHS R01 NS113541NINDS NIH HHS R01 NS117904NINDS NIH HHS R21 NS113055NINDS NIH HHS R21 NS115174NINDS NIH HHS U54 NS100064NINR NIH HHS R01 NR013912
6 · The paper itself

Abstract

backgroundWe evaluated the feasibility and discriminability of recently proposed Clinical Performance Measures for Neurocritical Care (Neurocritical Care Society) and Quality Indicators for Traumatic Brain Injury (Collaborative European NeuroTrauma Effectiveness Research in TBI; CENTER-TBI) extracted from electronic health record (EHR) flowsheet data.

methodsAt three centers within the Collaborative Hospital Repository Uniting Standards (CHoRUS) for Equitable AI consortium, we examined consecutive neurocritical care admissions exceeding 24 h (03/2015-02/2020) and evaluated the feasibility, discriminability, and site-specific variation of five clinical performance measures and quality indicators: (1) intracranial pressure (ICP) monitoring (ICPM) within 24 h when indicated, (2) ICPM latency when initiated within 24 h, (3) frequency of nurse-documented neurologic assessments, (4) intermittent pneumatic compression device (IPCd) initiation within 24 h, and (5) latency to IPCd application. We additionally explored associations between delayed IPCd initiation and codes for venous thromboembolism documented using the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) system. Median (interquartile range) statistics are reported. Kruskal-Wallis tests were measured for differences across centers, and Dunn statistics were reported for between-center differences.

resultsA total of 14,985 admissions met inclusion criteria. ICPM was documented in 1514 (10.1%), neurologic assessments in 14,635 (91.1%), and IPCd application in 14,175 (88.5%). ICPM began within 24 h for 1267 (83.7%), with site-specific latency differences among sites 1-3, respectively, (0.54 h [2.82], 0.58 h [1.68], and 2.36 h [4.60]; p < 0.001). The frequency of nurse-documented neurologic assessments also varied by site (17.4 per day [5.97], 8.4 per day [3.12], and 15.3 per day [8.34]; p < 0.001) and diurnally (6.90 per day during daytime hours vs. 5.67 per day at night, p < 0.001). IPCds were applied within 24 h for 12,863 (90.7%) patients meeting clinical eligibility (excluding those with EHR documentation of limiting injuries, actively documented as ambulating, or refusing prophylaxis). In-hospital venous thromboembolism varied by site (1.23%, 1.55%, and 5.18%; p < 0.001) and was associated with increased IPCd latency (overall, 1.02 h [10.4] vs. 0.97 h [5.98], p = 0.479; site 1, 2.25 h [10.27] vs. 1.82 h [7.39], p = 0.713; site 2, 1.38 h [5.90] vs. 0.80 h [0.53], p = 0.216; site 3, 0.40 h [16.3] vs. 0.35 h [11.5], p = 0.036).

conclusionsElectronic health record-derived reporting of neurocritical care performance measures is feasible and demonstrates site-specific variation. Future efforts should examine whether performance or documentation drives these measures, what outcomes are associated with performance, and whether EHR-derived measures of performance measures and quality indicators are modifiable.

Indexed as

Brain Injuries, TraumaticVenous ThromboembolismElectronic Health RecordsHospitalsHumansIntermittent Pneumatic Compression DevicesPilot ProjectsBig dataCritical careData scienceElectronic health recordsGlasgow Coma ScaleIntracranial pressureQuality improvementQuality indicators (health care)Venous thrombosis

Identifiers

PMID35689135
PMCPMC10327405

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.