Early Recognition Of The Deteriorating Surgical Patient Using HealthPatch MD, A Wireless And Wearable Vital Signs Monitor – An Early Clinical Feasibility Study

Huizinga, E (2017) Early Recognition Of The Deteriorating Surgical Patient Using HealthPatch MD, A Wireless And Wearable Vital Signs Monitor – An Early Clinical Feasibility Study.

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Abstract:After major surgery, patients are at increased risk of adverse outcomes, such as complications and increased hospital length of stay and they have increased morbidity and mortality. To enhance patient safety, vital signs (e.g. heart rate and respiratory rate) are monitored. However, when patients move from high care wards (e.g. intensive or medium care) to regular wards, the frequency and quality of monitoring decrease. As a consequence, patient safety may be compromised. After discharge from the hospital, monitoring is virtually unavailable and the probability of timely recognition of deterioration increases substantially. However, because it is known that certain vital signs can show early changes before adverse events occur, patient safety may be enhanced during hospital admission and after discharge if these were monitored. To monitor in an accessible manner while not encumbering patients, caregivers and medical personnel, it could be a solution to use portable, wireless and non-invasive sensors called wearables. This study has investigated one such wearable, HealthPatch MD by Vital Connect, by performing measurements with it on the surgical medium care ward at the UMC Utrecht. The goal was to study the principles that such a wearable uses, assess its performance in clinical practice and comparing its measurements with a regular patient monitor (Spacelabs XPREZZON). Measurements were done in 35 participations. Using Bland-Altman analysis for repeated measurements, it was found that heart rate accuracy is acceptable compared to Spacelabs. Respiratory rate is not measured accurately enough to be considered acceptable. However, it remains unknown if Spacelabs is a good reference for respiratory rate, because this monitor is not the gold standard. To use this type of data, obtained by a wearable monitor, for early recognition of the deteriorating patient, a model needs to be developed to predict a measure of risk of decline. The Early Warning Score (EWS) is such a measure that is currently used in clinical practice. If EWS were predictable using a wearable vital signs monitor, that monitor may be able to predict patient decline as well. Because in this study not enough data was obtained collected, such a model could not be developed. However, various prediction modelling techniques that can be applied to this type of data are described in this thesis.
Item Type:Essay (Master)
Clients:
University Medical Center Utrecht, Utrecht, The Netherlands
University Medical Center Utrecht, Utrecht, The Netherlands
Faculty:TNW: Science and Technology
Subject:44 medicine
Programme:Technical Medicine MSc (60033)
Link to this item:http://purl.utwente.nl/essays/72821
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