scholarly journals Increasing patient safety with neonates via handoff communication during delivery: a call for interprofessional health care team training across GME and CME

2017 ◽  
Vol Volume 8 ◽  
pp. 365-367 ◽  
Author(s):  
Allison A Vanderbilt ◽  
Scott M Pappada ◽  
Howard Stein ◽  
David Harper ◽  
Thomas J Papadimos
Keyword(s):  
Health Care ◽  
Patient Safety ◽  
Team Training ◽  
Health Care Team ◽  
Care Team

scholarly journals The Anatomy of Health Care Team Training and the State of Practice: A Critical Review

2010 ◽  
Vol 85 (11) ◽  
pp. 1746-1760 ◽  
Author(s):  
Sallie J. Weaver ◽  
Rebecca Lyons ◽  
Deborah DiazGranados ◽  
Michael A. Rosen ◽  
Eduardo Salas ◽  
...  
Keyword(s):  
Health Care ◽  
Critical Review ◽  
Team Training ◽  
Health Care Team ◽  
The State ◽  
Care Team ◽  
State Of Practice

scholarly journals Artificial Intelligence Technologies for Coping with Alarm Fatigue in Hospital Environments Because of Sensory Overload: Algorithm Development and Validation

10.2196/15406 ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. e15406 ◽  
Author(s):  
Chrystinne Oliveira Fernandes ◽  
Simon Miles ◽  
Carlos José Pereira De Lucena ◽  
Donald Cowan
Keyword(s):  
Health Care ◽  
Patient Safety ◽  
Patient Monitoring ◽  
Health Care Team ◽  
Care Team ◽  
Royal Adelaide Hospital ◽  
Alarm Fatigue ◽  
Number Of Patients ◽  
Short Period ◽  
Reasoning Algorithm

Background Informed estimates claim that 80% to 99% of alarms set off in hospital units are false or clinically insignificant, representing a cacophony of sounds that do not present a real danger to patients. These false alarms can lead to an alert overload that causes a health care provider to miss important events that could be harmful or even life-threatening. As health care units become more dependent on monitoring devices for patient care purposes, the alarm fatigue issue has to be addressed as a major concern for the health care team as well as to enhance patient safety. Objective The main goal of this paper was to propose a feasible solution for the alarm fatigue problem by using an automatic reasoning mechanism to decide how to notify members of the health care team. The aim was to reduce the number of notifications sent by determining whether or not to group a set of alarms that occur over a short period of time to deliver them together, without compromising patient safety. Methods This paper describes: (1) a model for supporting reasoning algorithms that decide how to notify caregivers to avoid alarm fatigue; (2) an architecture for health systems that support patient monitoring and notification capabilities; and (3) a reasoning algorithm that specifies how to notify caregivers by deciding whether to aggregate a group of alarms to avoid alarm fatigue. Results Experiments were used to demonstrate that providing a reasoning system can reduce the notifications received by the caregivers by up to 99.3% (582/586) of the total alarms generated. Our experiments were evaluated through the use of a dataset comprising patient monitoring data and vital signs recorded during 32 surgical cases where patients underwent anesthesia at the Royal Adelaide Hospital. We present the results of our algorithm by using graphs we generated using the R language, where we show whether the algorithm decided to deliver an alarm immediately or after a delay. Conclusions The experimental results strongly suggest that this reasoning algorithm is a useful strategy for avoiding alarm fatigue. Although we evaluated our algorithm in an experimental environment, we tried to reproduce the context of a clinical environment by using real-world patient data. Our future work is to reproduce the evaluation study based on more realistic clinical conditions by increasing the number of patients, monitoring parameters, and types of alarm.

scholarly journals Patient Safety in Primary Care: Conceptual Meanings to the Health Care Team and Patients

2020 ◽  
Vol 33 (5) ◽  
pp. 754-764
Author(s):  
Alden Yuanhong Lai ◽  
Christina T. Yuan ◽  
Jill A. Marsteller ◽  
Susan M. Hannum ◽  
Elyse C. Lasser ◽  
...  
Keyword(s):  
Primary Care ◽  
Health Care ◽  
Patient Safety ◽  
Health Care Team ◽  
Care Team

Transforming Health Care One Team at a Time: Ten Observations and the Trail Ahead

2018 ◽  
Vol 43 (3) ◽  
pp. 357-381 ◽  
Author(s):  
Eduardo Salas ◽  
Stephanie Zajac ◽  
Shannon L. Marlow
Keyword(s):  
Health Care ◽  
Team Training ◽  
Health Care Team ◽  
Care Team ◽  
Organizational Level ◽  
Future Research ◽  
Health Care Teams ◽  
Current State ◽  
State Of The Science ◽  
Insight Into

The present review synthesizes existing evidence and theory on the science of health care teams and health care team training. Ten observations are presented that capture the current state of the science, with applications to both researchers and practitioners. The observations are drawn from a variety of salient sources, including meta-analytic evidence, reviews of health care team training, primary investigations, and the authors’ collective expertise in developing and implementing medical team training. These observations provide insight into the team (e.g., psychological safety) and organizational-level (e.g., culture for teamwork) factors that drive effective health care teamwork, as well as advancements and best practices for designing and implementing team training initiatives (e.g., multilevel measurement). We highlight areas where new knowledge has emerged, and offer directions for future research that will continue to improve our understanding of health care teams in the future.

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