continuous wireless physiological data using Lifetouch (ECG-derived heart and respiratory rate) and WristOx2 (pulse-oximetry and derived pulse rate) sensors.3

The study authors compared their bedside paediatric early warning (PEW) score and a machine learning automated approach: a Real-time Adaptive Predictive Indicator of Deterioration (RAPID), to identify children experiencing significant clinical deterioration. 982 patients contributed 7,073,486 minutes during 1,263 monitoring sessions. Twenty- nine patients experienced 36 clinically significant deteriorations. The study found that the RAPID Index detected significant deterioration more frequently (77% to 97%) and earlier than the PEW score ≥ 9/26. High sensitivity and negative predictive value for the RAPID Index was associated with low specificity and low positive predictive value. Duncan et al concluded that it is feasible to collect clinically valid physiological data wirelessly for 50% of intended monitoring time. The RAPID Index identified more deterioration, before the PEW score, but had a low specificity. By using the RAPID Index with a PEW system some life- threatening events may be averted.

Improving outcomes

The PSE technology has also been adopted by clinicians in Denmark to help improve outcomes following surgery. The technology was initially introduced at Bispebjerg Hospital and Rigshospitalet in Copenhagen, Denmark, to identify patients at risk of complications. Millions of patients undergo major surgical procedures annually. Post-operative complication rates are between 15-45% depending on the procedure, with prolonged

in-hospital stay and a high risk of intensive care unit admissions.

Among the most frequent complications are

pulmonary and circulatory complications and it is estimated that 10 million patients experience myocardial injury after noncardiac surgery every year. Prevention or early intervention of these complications with continuous monitoring using the Patient Status Engine has the potential to make a major difference in morbidity and mortality after surgery and create significant economic savings.

Monitoring patients outside the hospital setting

Errey points out that the technology is not limited to monitoring patients in hospital. Healthcare providers globally are beginning to shift patients towards homecare programmes in order to reduce costs and

Manchester Trusts use AI for remote

monitoring of COVID patients Manchester University NHS Foundation Trust (MFT) and The Christie NHS Foundation Trust in Manchester are currently trialling the Isansys platform to monitor COVID-19 patients from afar and identify and predict deterioration fast, enabling them to potentially save thousands of lives. Dr. Anthony Wilson, intensive care consultant at Manchester Royal Infirmary, part of MFT, where approximately 10-20% of hospital inpatients with COVID-19 will need to be admitted to intensive care, said: “The intensive care team at MFT has cared for many people with COVID-19 infection in the last few months. The new technology in Manchester may allow us to intervene earlier and give patients a greater chance of getting better. This


technology is a glimpse of how we will monitor hospital patients in the future, and it is fantastic that MFT and The Christie are frontrunners in such innovation.” Professor Fiona Thistlethwaite, medical oncologist at The Christie Trust, said: “Unfortunately some patients who are suffering from COVID-19 on our hospital wards can become seriously unwell. By using this system, we hope to be able to identify these patients early and this means we can optimise their management without the need for them to go to intensive care. We can also monitor the patients’ vital signs on a screen located in a different part of the hospital and we hope that, eventually, this will mean that as well as keeping our patients safe, we can reduce exposure to the virus for our staff.”

improve outcomes by avoiding the dangers associated with hospital admission. Not only does home-based care offer greater mobility for patients but it also allows for community based early interventions to prevent readmissions. With the PSE, healthcare professionals can receive complete and clinically accurate information about their patients’ health status directly from the patients’ homes or other locations outside the hospital. By effectively extending critical care pathways outside the hospital, patients can remain under the direct care of their consulting physicians and specialised care teams. The real-time patient data and early warning alerts are delivered to central monitoring stations and personal mobile devices, and are readily integrated with the provider’s electronic medical records system. “Everyone wants patients out of hospital

faster or, better still, not to be in hospital at all. These devices, which were pioneered within the hospital environment, are now starting to be used to provide much higher acuity care to patients at home. This has to be a good thing. In the current situation, why would you want to be in hospital if you don’t have to?” Errey concluded.


References 1 Meirowitz N, Efficacy of continuous monitoring of maternal temperature during labor using wireless axillary sensors, American Journal of Obstetrics and Gynecology, January 2019.

2 Jansen C, Chatterjee DA, Thomsen KL, et al. Significant reduction in heart rate variability is a feature of acute decompensation of cirrhosis and predicts 90 day mortality. Aliment Pharmacol Ther. 2019;00:1–12.

3 Duncan, H.P., Fule, B., Rice, I. et al. Wireless monitoring and real-time adaptive predictive indicator of deterioration. Sci Rep 10, 11366 (2020).


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