Evidence map›Paper›PMID 34983402›Full record

ArticleBMC anesthesiology2022

Investigating the cognitive capacity constraints of an ICU care team using a systems engineering approach.

Jaeyoung Park, Xiang Zhong, Yue Dong, Amelia Barwise, Brian W Pickering

Abstract read
In one paragraph

Article in BMC anesthesiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Jaeyoung ParkDepartment of Industrial and Systems Engineering, University of Florida, 482 Weil Hall, P.O. Box 116595, Gainesville, FL, 32611-6595, USA.
Xiang ZhongDepartment of Industrial and Systems Engineering, University of Florida, 482 Weil Hall, P.O. Box 116595, Gainesville, FL, 32611-6595, USA. xiang.zhong@ise.ufl.edu.
Yue DongDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, USA.
Amelia BarwiseDivision of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USA.
Brian W PickeringDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, USA.

Funding

Acute Care Learning Laboratory - Reducing Threats to Diagnostic Fidelity in Critical IllnessR18HS026609 · AHRQ · MAYO CLINIC ROCHESTER · PI PICKERING, BRIAN W · 2018 to 2021
$2.4M
AHRQ HHS R18HS026609
6 · The paper itself

Abstract

backgroundICU operational conditions may contribute to cognitive overload and negatively impact on clinical decision making. We aimed to develop a quantitative model to investigate the association between the operational conditions and the quantity of medication orders as a measurable indicator of the multidisciplinary care team's cognitive capacity.

methodsThe temporal data of patients at one medical ICU (MICU) of Mayo Clinic in Rochester, MN between February 2016 to March 2018 was used. This dataset includes a total of 4822 unique patients admitted to the MICU and a total of 6240 MICU admissions. Guided by the Systems Engineering Initiative for Patient Safety model, quantifiable measures attainable from electronic medical records were identified and a conceptual framework of distributed cognition in ICU was developed. Univariate piecewise Poisson regression models were built to investigate the relationship between system-level workload indicators, including patient census and patient characteristics (severity of illness, new admission, and mortality risk) and the quantity of medication orders, as the output of the care team's decision making.

resultsComparing the coefficients of different line segments obtained from the regression models using a generalized F-test, we identified that, when the ICU was more than 50% occupied (patient census > 18), the number of medication orders per patient per hour was significantly reduced (average = 0.74; standard deviation (SD) = 0.56 vs. average = 0.65; SD = 0.48; p < 0.001). The reduction was more pronounced (average = 0.81; SD = 0.59 vs. average = 0.63; SD = 0.47; p < 0.001), and the breakpoint shifted to a lower patient census (16 patients) when at a higher presence of severely-ill patients requiring invasive mechanical ventilation during their stay, which might be encountered in an ICU treating patients with COVID-19.

conclusionsOur model suggests that ICU operational factors, such as admission rates and patient severity of illness may impact the critical care team's cognitive function and result in changes in the production of medication orders. The results of this analysis heighten the importance of increasing situational awareness of the care team to detect and react to changing circumstances in the ICU that may contribute to cognitive overload.

Indexed as

CognitionIntensive Care UnitsPatient Care TeamAgedCOVID-19Decision Making, OrganizationalFemaleHumansMaleMiddle AgedPatient SafetySARS-CoV-2WorkloadCognitive functionElectronic medical recordsOrganizational decision makingSituational awarenessSystems approachWorkload

Identifiers

PMID34983402
PMCPMC8724599

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LicenceCC BY
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Registered trials

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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.