Interim analysis from FLOODLIGHT: a prospective pilot study to evaluate the feasibility of conducting remote patient monitoring with the use of digital technology in patients with multiple sclerosis

Author(s):  
Patricia Mulero
Hypertension ◽  
2021 ◽  
Vol 78 (Suppl_1) ◽  
Author(s):  
Ashish Sarraju ◽  
Meg Babakhanian ◽  
Irvin Szeto ◽  
Clark Seninger ◽  
Tara I Chang ◽  
...  

Introduction: While remote patient monitoring (RPM) for hypertension (HTN) continues to grow in the United States, most systems are third party, employer-directed, or do not directly lead to changes in medication management. Systems that address these issues may reduce therapeutic inertia and lead to more rapid control of blood pressure (BP). We developed a clinician-facing HTN RPM system with evidence-based customizable medication titration protocols that integrate with a patient mobile app and Bluetooth®-connected BP cuff. We report interim results from the pilot implementation of this system. Hypothesis: In a pilot study, an RPM system with patient and clinician-facing platforms and a semi-automated protocol will achieve high engagement with actionable user feedback. Methods: We performed a single arm, single center study with five clinicians from primary care (3) and cardiology (2). Eligible patients had essential hypertension (BP >130/80 mmHg) and a smartphone (iPhone, Android). Patients used a Bluetooth®-connected cuff that sent readings to a patient app and a clinician dashboard. Based on BP and comorbidities, a protocol provided medication titration recommendations for clinicians. In this 12-week study, we assessed feasibility through user feedback, user engagement (defined as the number of BP measurements), and changes in systolic (SBP, mmHg) and diastolic BP (DBP, mmHg). Results: We enrolled 18 patients (age 51 + 11y; 94% male; 29% White). Baseline SBP was 133 + 7.8 and DBP was 87 + 7.1. At a mean follow-up of 4.7 weeks, there were 15 + 11 weekly BP measurements per patient. Mean per-patient decreases in SBP and DBP were 12 (95% CI 5.8-18, p<0.001) and 7.1 (95% CI 3.1-11, p = 0.002), respectively. A total of 77.8% (14/18) patients continued BP measurements without attrition. Key feedback included improved cuff-mobile app connectivity (patients) and increased medication choices in protocols (clinicians). Conclusions: In interim results of a pilot study, an RPM HTN system was implemented with high engagement, evidence of BP reduction, and actionable feedback. Complete results including medication and BP changes are anticipated by September 2020 and will guide a planned, funded, large, multicenter cluster randomized trial.


Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 776
Author(s):  
Xiaohui Tao ◽  
Thanveer Basha Shaik ◽  
Niall Higgins ◽  
Raj Gururajan ◽  
Xujuan Zhou

Remote Patient Monitoring (RPM) has gained great popularity with an aim to measure vital signs and gain patient related information in clinics. RPM can be achieved with noninvasive digital technology without hindering a patient’s daily activities and can enhance the efficiency of healthcare delivery in acute clinical settings. In this study, an RPM system was built using radio frequency identification (RFID) technology for early detection of suicidal behaviour in a hospital-based mental health facility. A range of machine learning models such as Linear Regression, Decision Tree, Random Forest, and XGBoost were investigated to help determine the optimum fixed positions of RFID reader–antennas in a simulated hospital ward. Empirical experiments showed that Decision Tree had the best performance compared to Random Forest and XGBoost models. An Ensemble Learning model was also developed, took advantage of these machine learning models based on their individual performance. The research set a path to analyse dynamic moving RFID tags and builds an RPM system to help retrieve patient vital signs such as heart rate, pulse rate, respiration rate and subtle motions to make this research state-of-the-art in terms of managing acute suicidal and self-harm behaviour in a mental health ward.


2021 ◽  
Vol 46 (5) ◽  
pp. 100800
Author(s):  
Abdulaziz Joury ◽  
Tamunoinemi Bob-Manuel ◽  
Alexandra Sanchez ◽  
Fnu Srinithya ◽  
Amber Sleem ◽  
...  

CHEST Journal ◽  
2021 ◽  
Vol 159 (2) ◽  
pp. 477-478
Author(s):  
Neeraj R. Desai ◽  
Edward J. Diamond

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