ArticleCritical care explorations2020
Quantifying Mobility in the ICU: Comparison of Electronic Health Record Documentation and Accelerometer-Based Sensors to Clinician-Annotated Video.
Article in Critical care explorations, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Physical Therapist-Led Therapeutic Exercise and Mobility in Adult Intensive Care Units: A Scoping Review of Operational Definitions, Dose Progression, Safety, and Documentation.Journal of clinical medicine · 2025Review
- Accelerometer-derived movement features as predictive biomarkers for muscle atrophy in neurocritical care: a prospective cohort study.Critical care (London, England) · 2024Observational
- Establishing a paediatric critical care core quality measure set using a multistakeholder, consensus-driven process.Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine · 2024Article
- Identification and Quantification of Activities Common to Intensive Care Patients; Development and Validation of a Dual-Accelerometer-Based Algorithm.Sensors (Basel, Switzerland) · 2023Article
- Effects of social influence and implementation climate and leadership on nurse-led early mobility behaviours in critical care.BMJ open quality · 2022Article
- Potentials and Challenges of Pervasive Sensing in the Intensive Care Unit.Frontiers in digital health · 2022Review
- Decoding accelerometry for classification and prediction of critically ill patients with severe brain injury.Scientific reports · 2021Article
- Standardisation, multi-measure, data quality and trending: A qualitative study on multidisciplinary perspectives to improve intensive care early mobility monitoring.Intensive & critical care nursing · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
To compare the accuracy of electronic health record clinician documentation and accelerometer-based sensors with a gold standard dataset derived from clinician-annotated video to quantify early mobility activities in adult ICU patients.
designProspective, observational study.
settingMedical ICU at an academic hospital. PATIENTS: Adult ICU patients (n = 30) were each continuously monitored over a median of 24.4 hours, yielding 711.5 hours of video, electronic health record, and sensor data.
interventionsNone. MEASUREMENTS AND MAIN
resultsElectronic health record documentation estimated ambulation (intraclass correlation coefficient, 0.89; 95% CI, 0.78-0.95), sitting out-of-bed (intraclass correlation coefficient, 0.85; 95% CI, 0.72-0.93), and turning events (intraclass correlation coefficient, 0.87; 95% CI, 0.75-0.94) with excellent agreement but underestimated the number of standing, transferring, and pregait activities performed per patient. The accelerometer-based sensor had excellent agreement with video annotation for estimating duration of time spent supine (intraclass correlation coefficient, 0.99; CI, 0.97-0.99) and sitting/standing upright (intraclass correlation coefficient, 0.92; CI, 0.82-0.96) but overestimated ambulation time.
conclusionsOur results show that electronic health record documentation and sensor-based technologies accurately capture distinct but complimentary metrics for ICU mobility measurement. Innovations in artifact detection, standardization of clinically relevant mobility definitions, and electronic health record documentation enhancements may enable further use of these technologies to drive critical care research and technology leveraged data-driven ICU models of care.
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Registered trials
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