Systems for early detection of clinical deterioration in older people in non-hospital settings – a systematic scoping review

More and more studies are examining systems for early detection of clinical deterioration in non-hospital settings, but few have focused on older people and primary care.

Frontiers Artificial intelligence in critical illness and its impact on patient care: a comprehensive review

Healthcare, Free Full-Text

A scoping review of the impacts of COVID-19 physical distancing measures on vulnerable population groups

Machine learning-based model for prediction of clinical deterioration in hospitalized patients by COVID 19

Barriers and enablers of recognition and response to deteriorating patients in the acute hospital setting: A theory‐driven interview study using the Theoretical Domains Framework - Smith - 2021 - Journal of Advanced

British Journal of Nursing - The global elements of vital signs' assessment: a guide for clinical practice

A protocol for a systematic review of electronic early warning/track-and-trigger systems (EW/TTS) to predict clinical deterioration: Focus on automated features, technologies, and algorithms

Predicting acute clinical deterioration with interpretable machine learning to support emergency care decision making

Factors influencing nursing students' ability to recognise and respond to simulated patient deterioration: A scoping review - ScienceDirect

A national study of 23 major trauma centres to investigate the effect of frailty on clinical outcomes in older people admitted with serious injury in England (FiTR 1): a multicentre observational study

Complex interventions to improve physical function and maintain independent living in elderly people: a systematic review and meta-analysis - The Lancet

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Multisystem physiological perspective of human frailty and its modulation by physical activity

Illness severity assessment of older adults in critical illness using machine learning (ELDER-ICU): an international multicentre study with subgroup bias evaluation - The Lancet Digital Health