Clinical outcomes of patients admitted to the hospital depend heavily on early detection of clinical deterioration, timely response by staff, and appropriate medical intervention targeted at treating the underlying cause.
Risk stratification models that predict the prognosis of patients admitted to the hospital have been around for a long time; however, over the past decade, significant efforts have gone into the development and validation of early warning scoring (EWS) protocols that predict clinical deterioration. Typically, EWS protocols use changes in vital signs to determine the rapidity and severity of clinical deterioration and make suggestions to the care team, based on a validated protocol. Numerous EWS methods exist, and they use physiological parameters including but not limited to: respiratory rate, heart rate, blood pressure, oxygen saturation, level of consciousness, temperature, etc. I believe EWS protocols are ideal for routine use among hospitalized patients who may experience unexpected clinical deterioration as well as patients presenting to the emergency department to determine the appropriate level of care – regular inpatient floor, intermediate care (or step-down unit).
EWS protocols have been evaluated for their performance and early studies show that they result in an increase in rapid response calls as well as decrease in in-hospital cardiac arrests. Thus, a few years ago, the National Health Service in the UK developed a National Early Warning Score (NEWS) in hopes of providing standardization, driving broader clinical adoption, and improving patient safety and clinical outcomes. Throughout the development process, NEWS was compared against a number of other EWS protocols and has been shown to have very high sensitivity and good discriminatory power for predicting acute mortality.
Despite the availability of automated EWS protocols and their demonstrated benefits, clinical adoption has been slow. In many hospitals, nurses still measure patient vital signs and calculate EWS manually, and they are required to transcribe the data they collect into the electronic medical record (EMR). The paper-based method of scoring is both time consuming and susceptible to omission and error, which has led to poor compliance with the tool and missed opportunities to recognize clinical deterioration.
Philips has a new wearable biosensor that, when used in system connectivity with their existing IntelliVue Guardian Solution (Philips’ Automated Early Warning Scoring system), has the potential to aid the clinician in detecting clinical deterioration.
The single-use, self-adhesive sensor, which weighs approximately twelve grams, automatically collects key vital signs, which it communicates wirelessly to the IntelliVue Guardian software, a software that automatically calculates a patient’s EWS. The sensor measures respiratory rate, heart rate, body posture and detects falls. Its battery that lasts for four days—the average stay for a patient in the General Care Floor.
Perhaps of most clinical importance, in my opinion, is the fact that the wearable biosensor automatically captures the respiratory rate and incorporates this into the EWS. Too often inaccurately captured or altogether neglected in on the General Care Floor, respiratory rate has been found to be an incredibly reliable predictor of deterioration.
This biosensor will allow healthcare providers to easily monitor the vitals of non-critically ill patients on the General Care Floor between spot-check rounds, and aid the clinician in detecting changes that might suggest a patient needs escalation in their care. The output from the sensor and software is displayed on a Philips vital signs monitor, desktop and a dashboard, independent of the EMR — allowing nurses quick and easy access to patient’s vitals on the bedside or to a color-scheme based escalation protocol for each patient under his/her care.
The biosensor automatically records vital signs which could ease the burden of manual documentation, avoid latency feeding information into the EMR, thereby improving compliance with recommended frequency for capturing vital signs. I believe there could be several clinical applications for such a device, but a few high-value clinical use case examples include: a) physiologic monitoring of routine patients on General Care Floors; b) remote patient monitoring for those discharged to home or a post-acute care facility that are at high risk for hospital readmissions.
I believe, wearable technology, such as this device could hold tremendous promise to transform patient care, but as with any new medical device, more research is needed to build a strong body of evidence for wide clinical adoption. Wearable solutions need to be tested in both the inpatient and outpatient setting to establish validity for the various clinical applications referenced above, for broad clinical adoption. It’s exciting to see that Philips is working to improve patient care by integrating wearables into their EWS software. I believe wearable sensors such as this one will have an important role to play in early intervention, and I expect wearables to become a future staple in the most effective methods of patient monitoring.
 Smith MEB, Chiovaro JC, O’Neil M, et al. Early Warning System Scores: A Systematic Review [Internet]. Washington (DC): Department of Veterans Affairs (US); 2014 Jan.
 Royal College of Physicians. National Early Warning Score (NEWS): Standardising the assessment of acute- illness severity in the NHS. Report of a working party. London: RCP, 2012.
 Elliot, Malcolm, et al. “Critical care: The eight vital signs of patient monitoring.” British journal of nursing (Mark Allen Publishing) 21(10):621-5 · May 2012
Dr. Majmudar is a practicing cardiologist and Associate Director of the Healthcare Transformation Lab at Massachusetts General Hospital, and an Instructor at Harvard Medical School. He is an active member of the healthcare innovation and entrepreneurship community, with a specific interest in technology-enabled healthcare innovation. He was a founding member and chief clinical officer of Quanttus, Inc. a venture-backed medical wearables startup. He is also a lecturer in the Harvard-MIT HST Program, and co-faculty for the course Healthcare Ventures.Dr. Majmudar attended Northwestern University Feinberg School of Medicine and then completed residency training in Internal Medicine at The Johns Hopkins Hospital, followed by a fellowship in Cardiology at the Brigham and Women’s Hospital and Duke University Medical Center. He also holds a patent and has had several publications in high-impact journals, such as Nature, Circulation, and Journal of Healthcare Delivery and Implementation Science.
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