Performance of digital early warning score (NEWS2) in a cardiac specialist setting: retrospective cohort study.

Introduction: Patients with cardiovascular diseases (CVD) are at significant risk of developing critical events. Early warning scores (EWS) are recommended for early recognition of deteriorating patients, yet their performance has been poorly studied in cardiac care settings. Standardisation and integrated National Early Warning Score 2 (NEWS2) in electronic health records (EHRs) are recommended yet have not been evaluated in specialist settings.

Clinical deployment environments: Five pillars of translational machine learning for health.

Machine Learning for Health (ML4H) has demonstrated efficacy in computer imaging and other self-contained digital workflows, but has failed to substantially impact routine clinical care. This is no longer because of poor adoption of Electronic Health Records Systems (EHRS), but because ML4H needs an infrastructure for development, deployment and evaluation within the healthcare institution. In this paper, we propose a design pattern called a Clinical Deployment Environment (CDE).

Wearables alone will not eliminate failure to rescue.

Surveys suggest that anaesthesiologists believe that continuous monitoring with wearables will lead to improved patient outcomes. However, evidence suggests that several critical factors, including timely recognition of physiological problems, the presence of a trained team to respond to the alerts, and that the alerts occur far in advance of the deterioration, are required before overall improvement can occur. Wearables alone will not change patients' outcomes, they must be implemented as part of a system change that takes advantage of the higher frequency observations that continuous monitoring provides.

An impedance pneumography signal quality index: Design, assessment and application to respiratory rate monitoring.

Impedance pneumography (ImP) is widely used for respiratory rate (RR) monitoring. However, ImP-derived RRs can be imprecise. The aim of this study was to develop a signal quality index (SQI) for the ImP signal, and couple it with a RR algorithm, to improve RR monitoring.