Formal metrics for monitoring the quality and safety of healthcare have a valuable role, but may not, by themselves, yield full insight into the range of fallibilities in organizations. ‘Soft intelligence’ is usefully understood as the processes and behaviours associated with seeking and interpreting soft data—of the kind that evade easy capture, straightforward classification and simple quantification—to produce forms of knowledge that can provide the basis for intervention. With the aim of examining current and potential practice in relation to soft intelligence, we conducted and analysed 107 in-depth qualitative interviews with senior leaders, including managers and clinicians, involved in healthcare quality and safety in the English Nat...
Technological advances in artificial intelligence (AI) are promising continuous improvements in prob...
AI has the ability to completely transform the healthcare industry by enhancing patient outcomes, bo...
Background: We focus on the importance of interpreting the quality of the labeling used as the input...
AbstractFormal metrics for monitoring the quality and safety of healthcare have a valuable role, but...
Formal metrics for monitoring the quality and safety of healthcare have a valuable role, but may not...
Copyright © 2015 The Authors. Published by Elsevier Ltd. All rights reserved. Acknowledgments We ack...
Background Healthcare organisations often fail to harvest and make use of the ‘soft intelligence’ ab...
BACKGROUND: Healthcare organisations often fail to harvest and make use of the 'soft intelligence' a...
Patients, clinicians and managers all want to be reassured that their healthcare organisation is saf...
Purpose: Incident reporting systems are commonly deployed in healthcare but resulting datasets are l...
Through a series of case studies, we review how the unthinking pursuit of metric optimization can le...
Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and oth...
We are developing an Artificial Intelligence (AI) risk governance framework based on human factors a...
Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and oth...
Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and oth...
Technological advances in artificial intelligence (AI) are promising continuous improvements in prob...
AI has the ability to completely transform the healthcare industry by enhancing patient outcomes, bo...
Background: We focus on the importance of interpreting the quality of the labeling used as the input...
AbstractFormal metrics for monitoring the quality and safety of healthcare have a valuable role, but...
Formal metrics for monitoring the quality and safety of healthcare have a valuable role, but may not...
Copyright © 2015 The Authors. Published by Elsevier Ltd. All rights reserved. Acknowledgments We ack...
Background Healthcare organisations often fail to harvest and make use of the ‘soft intelligence’ ab...
BACKGROUND: Healthcare organisations often fail to harvest and make use of the 'soft intelligence' a...
Patients, clinicians and managers all want to be reassured that their healthcare organisation is saf...
Purpose: Incident reporting systems are commonly deployed in healthcare but resulting datasets are l...
Through a series of case studies, we review how the unthinking pursuit of metric optimization can le...
Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and oth...
We are developing an Artificial Intelligence (AI) risk governance framework based on human factors a...
Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and oth...
Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and oth...
Technological advances in artificial intelligence (AI) are promising continuous improvements in prob...
AI has the ability to completely transform the healthcare industry by enhancing patient outcomes, bo...
Background: We focus on the importance of interpreting the quality of the labeling used as the input...