Clinical Activity Monitoring System (CATS): An automatic system to quantify bedside clinical activities in the intensive care unit

Guo, Peng; Chiew, Yeong Shiong; Shao, Lei; Green, Richard; Clark, Adrian; Chase, J. Geoffrey

doi:10.1016/j.iccn.2016.05.003

Cited by 10 publications

(3 citation statements)

References 29 publications

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“…In addition, clinical severity scores do not necessarily encompass the complexity of nursing activities, which means that aspects of nursing work not directly related to the care for an individual patient are not taken into account. 18 A study that aimed to identify the nursing workload through the NAS and to verify its relationship with clinical and demographic variables of the patients revealed a weak correlation between workload (NAS) and severity index / risk of mortality through SAPS II (R=0.26), similar to the correlation shown here.…”

Section: Discussionsupporting

confidence: 78%

Carga De Trabalho De Enfermagem E a Mortalidade Dos Pacientes Em Unidade De Terapia Intensiva

Nassiff

Araújo

Menegueti

et al. 2018

Texto contexto - enferm.

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Objective: to verify if the nursing workload is a predictor of mortality at an Intensive Care Unit.Method: cross-sectional and retrospective documentary study, developed at the Intensive Care Unit of a tertiary university hospital. The Receiver Operator Characteristic Curve was used, consisting of the Nursing Activities Score and the APACHE severity score, using logistic regression to analyze the prediction of mortality.Results: the sample included 324 patients, 214 (66%) of whom survived. The mean Nursing Activities Score during the first 24 hours of hospitalization was 79.3 points, ranging from 34.8 to 134.2 points, and the median APACHE II was 24.5 (2-42). In the analysis of the Receiver Operator Characteristic Curve, the Nursing Activities Score evidenced an area under the curve corresponding to 0.626; CI between 0.570 and 0.678 and an APACHE II score of 0.721, with a 95% confidence interval from 0.669 to 0.769.Conclusion: the nursing workload did not serve as a mortality predictor at the Intensive Care Unit, as the patients who demand the main nursing workload are not necessarily the patients who evolve to death. RESUMOObjetivo: verificar se a carga de trabalho de enfermagem é um preditor de mortalidade em Unidade de Terapia Intensiva.Método: estudo documental, retrospectivo, corte transversal, desenvolvido na Unidade de Terapia Intensiva de um hospital universitário terciário. Utilizou-se a curva Receiver Operator Characteristic Curve composta pelo Nursing Activities Score e índice de gravidade APACHE e regressão logística para análise da predição de mortalidade.Resultados: compuseram a amostra 324 pacientes, sendo 214 (66%) sobreviventes. A média Nursing Activities Score das primeiras 24 horas de internação foi de 79,3 pontos, variando de 34,8 a 134,2 pontos e o APACHE II mediano foi 24,5 (2-42). Na análise da curva Receiver Operator Characteristic Curve o Nursing Activities Score evidenciou uma área sobre a curva de 0,626; IC 0,570 a 0,678 e o APACHE II de 0,721 com intervalo de confiança IC 95% de 0,669 a 0,769.Conclusão: a carga de trabalho de enfermagem não foi um preditor de mortalidade em Unidade de Terapia Intensiva, pois os pacientes que demandam a maior carga de trabalho de enfermagem não necessariamente são aqueles que evoluem para o óbito. DESCRITORES: Carga de trabalho. Recursos humanos de enfermagem. Unidades de Terapia Intensiva. Mortalidade. Índice de gravidade de doença. RESUMENObjetivo: verificar si la carga de trabajo de enfermería es um como predictor de mortalidad en Unidad de Terapia Intensiva.Método: estudio documental, retrospectivo, corte transversal, desarrollado en la Unidad de Terapia Intensiva de un hospital universitario terciario. Se utilizó la curva Receiver Operator Characteristic Curve compuesta por el Nursing Activity Score y índice de gravedad APACHE y regresión logística para análisis de la predicción de mortalidad.Resultados: compusieron la muestra 324 pacientes, siendo 214 (66%) sobrevivientes. El promedio Nursing Activities Score de las primeras 24 horas de internació...

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Section: Discussionsupporting

confidence: 78%

Carga De Trabalho De Enfermagem E a Mortalidade Dos Pacientes Em Unidade De Terapia Intensiva

Nassiff

Araújo

Menegueti

et al. 2018

Texto contexto - enferm.

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“…Another study developed and validated a Clinical Activity Tracking System (CATS), testing its use in both a simulated and actual ICU room. Like the previous study, more caregiving activity was reported between 7:00 a.m. to 11:00 p.m. compared to 11:00 p.m. to 7:00 a.m. [221]. This system was validated against manual observation with a correlation of r = 0.882 [222].…”

Section: Quantification Of Workload In the Icumentioning

confidence: 74%

Applied Artificial Intelligence in Healthcare: A Review of Computer Vision Technology Application in Hospital Settings

Lindroth,

Nalaie,

Raghu

et al. 2024

J. Imaging

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Computer vision (CV), a type of artificial intelligence (AI) that uses digital videos or a sequence of images to recognize content, has been used extensively across industries in recent years. However, in the healthcare industry, its applications are limited by factors like privacy, safety, and ethical concerns. Despite this, CV has the potential to improve patient monitoring, and system efficiencies, while reducing workload. In contrast to previous reviews, we focus on the end-user applications of CV. First, we briefly review and categorize CV applications in other industries (job enhancement, surveillance and monitoring, automation, and augmented reality). We then review the developments of CV in the hospital setting, outpatient, and community settings. The recent advances in monitoring delirium, pain and sedation, patient deterioration, mechanical ventilation, mobility, patient safety, surgical applications, quantification of workload in the hospital, and monitoring for patient events outside the hospital are highlighted. To identify opportunities for future applications, we also completed journey mapping at different system levels. Lastly, we discuss the privacy, safety, and ethical considerations associated with CV and outline processes in algorithm development and testing that limit CV expansion in healthcare. This comprehensive review highlights CV applications and ideas for its expanded use in healthcare.

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“…In a recent meta-analysis, the majority of recently developed and currently utilized workload scores were assessed either through comparison with other scores or by utilizing time-on-task measurements. 5 Attempts to use clinicians' tracking devices were undertaken to improve the workload calculation [29][30][31] ; however, perceived workload measurement relies on selfreporting and cannot be captured directly from the EHR or recorded by an external device.…”

Section: Discussionmentioning

confidence: 99%

Weak Correlation Between Perceived and Measured Intensive Care Unit Nursing Workload

Wallet,

Bonnet,

Thiriaud

et al. 2024

Journal of Nursing Care Quality

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Background: Efficient management of nursing workload in the intensive care unit (ICU) is essential for patient safety, care quality, and nurse well-being. Current ICU-specific workload assessment scores lack comprehensive coverage of nursing activities and perceived workload. Purpose: The purpose of this study was to assess the correlation between ICU nurses’ perceived workload and the Nine Equivalents of Nursing Manpower Use Score (NEMS). Methods: In a 45-bed adult ICU at a tertiary academic hospital, nurses’ perceived shift workload (measured with an 11-point Likert scale) was correlated with the NEMS, calculated manually and electronically. Results: The study included 1734 observations. The perceived workload was recorded for 77.6% of observations. A weak positive correlation was found between perceived and objectively measured workload. Conclusion: Findings indicate a need to consider the multifaceted nature of nursing activities and individual workload perceptions in the ICU.

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Clinical Activity Monitoring System (CATS): An automatic system to quantify bedside clinical activities in the intensive care unit

Cited by 10 publications

References 29 publications

Carga De Trabalho De Enfermagem E a Mortalidade Dos Pacientes Em Unidade De Terapia Intensiva

Carga De Trabalho De Enfermagem E a Mortalidade Dos Pacientes Em Unidade De Terapia Intensiva

Applied Artificial Intelligence in Healthcare: A Review of Computer Vision Technology Application in Hospital Settings

Weak Correlation Between Perceived and Measured Intensive Care Unit Nursing Workload

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