Journal: Journal of Clinical Monitoring and Computing

Abbreviation

J Clin Monit Comput

Publisher

Springer

Journal Volumes

ISSN

1573-2614
1387-1307

Description

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2012 - 201932020 - 20222
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Publications 1 - 5 of 5
  • Use of eye tracking in analyzing distribution of visual attention among critical care nurses in daily professional life: an observational study
    Item type: Journal Article
    Hofmaenner, Daniel A.; Herling, Anique; Klinzing, Stephanie; et al. (2021)
    Journal of Clinical Monitoring and Computing
    Patient safety is a priority in healthcare, yet it is unclear how sources of errors should best be analyzed. Eye tracking is a tool used to monitor gaze patterns in medicine. The aim of this study was to analyze the distribution of visual attention among critical care nurses performing non-simulated, routine patient care on invasively ventilated patients in an ICU. ICU nurses were tracked bedside in daily practice. Eight specific areas of interest were pre-defined (respirator, drug preparation, medication, patient data management system, patient, monitor, communication and equipment/perfusors). Main independent variable and primary outcome was dwell time, secondary outcomes were hit ratio, revisits, fixation count and average fixation time on areas of interest in a targeted tracking-time of 60 min. 28 ICU nurses were analyzed and the average tracking time was 65.5 min. Dwell time was significantly higher for the respirator (12.7% of total dwell time), patient data management system (23.7% of total dwell time) and patient (33.4% of total dwell time) compared to the other areas of interest. A similar distribution was observed for fixation count (respirator 13.3%, patient data management system 25.8% and patient 31.3%). Average fixation time and revisits of the respirator were markedly elevated. Apart from the respirator, average fixation time was highest for the patient data management system, communication and equipment/perfusors. Eye tracking is helpful to analyze the distribution of visual attention of critical care nurses. It demonstrates that the respirator, the patient data management system and the patient form cornerstones in the treatment of critically ill patients. This offers insights into complex work patterns in critical care and the possibility of improving work flows, avoiding human error and maximizing patient safety.
  • Assessment of neonatal respiratory rate variability
    Item type: Journal Article
    Coleman, Jesse; Ginsburg, Amy Sarah; Macharia, William M.; et al. (2022)
    Journal of Clinical Monitoring and Computing
    Accurate measurement of respiratory rate (RR) in neonates is challenging due to high neonatal RR variability (RRV). There is growing evidence that RRV measurement could inform and guide neonatal care. We sought to quantify neonatal RRV during a clinical study in which we compared multiparameter continuous physiological monitoring (MCPM) devices. Measurements of capnography-recorded exhaled carbon dioxide across 60-s epochs were collected from neonates admitted to the neonatal unit at Aga Khan University-Nairobi hospital. Breaths were manually counted from capnograms and using an automated signal detection algorithm which also calculated mean and median RR for each epoch. Outcome measures were between- and within-neonate RRV, between- and within-epoch RRV, and 95% limits of agreement, bias, and root-mean-square deviation. Twenty-seven neonates were included, with 130 epochs analysed. Mean manual breath count (MBC) was 48 breaths per minute. Median RRV ranged from 11.5% (interquartile range (IQR) 6.8-18.9%) to 28.1% (IQR 23.5-36.7%). Bias and limits of agreement for MBC vs algorithm-derived breath count, MBC vs algorithm-derived median breath rate, MBC vs algorithm-derived mean breath rate were - 0.5 (- 2.7, 1.66), - 3.16 (- 12.12, 5.8), and - 3.99 (- 11.3, 3.32), respectively. The marked RRV highlights the challenge of performing accurate RR measurements in neonates. More research is required to optimize the use of RRV to improve care. When evaluating MCPM devices, accuracy thresholds should be less stringent in newborns due to increased RRV. Lastly, median RR, which discounts the impact of extreme outliers, may be more reflective of the underlying physiological control of breathing.
  • Where do pulse oximeter probes break?
    Item type: Journal Article
    Crede, S; Merwe, G. van der; Hutchinson, J.; et al. (2014)
    Journal of Clinical Monitoring and Computing
  • Pulse oximeter plethysmograph variation and its relationship to the arterial waveform in mechanically ventilated children.
    Item type: Journal Article
    Chandler, J.R.; Cooke, E.; Petersen, C.; et al. (2012)
    Journal of Clinical Monitoring and Computing
  • Monitoring nociception during general anesthesia with cardiorespiratory coherence
    Item type: Journal Article
    Brouse, Chris J.; Karlen, Walter Christian; Dumont, Guy A.; et al. (2013)
    Journal of Clinical Monitoring and Computing
Publications 1 - 5 of 5