scholarly journals Testing the Feasibility of Remote Patient Monitoring in Prenatal Care Using a Mobile App and Connected Devices: A Prospective Observational Trial

2016 ◽  
Vol 5 (4) ◽  
pp. e200 ◽  
Author(s):  
Kathryn I Marko ◽  
Jill M Krapf ◽  
Andrew C Meltzer ◽  
Julia Oh ◽  
Nihar Ganju ◽  
...  
Keyword(s):  
Prenatal Care ◽  
Patient Monitoring ◽  
Mobile App ◽  
Remote Patient Monitoring ◽  
Observational Trial ◽  
Remote Patient

scholarly journals Implementation of a mHealth solution to remotely monitor patients on a cardiac surgical waiting list: service evaluation

JAMIA Open ◽  
2021 ◽  
Vol 4 (3) ◽  
Author(s):  
Bernard Dillon Obika ◽  
Nikola Dolezova ◽  
Sonia Ponzo ◽  
Sophie Valentine ◽  
Sachin Shah ◽  
...  
Keyword(s):  
Patient Monitoring ◽  
Elective Surgery ◽  
Digital Health ◽  
Service Evaluation ◽  
Mobile App ◽  
Waiting List ◽  
Remote Patient Monitoring ◽  
Remote Patient ◽  
Viable Mechanism ◽  
Monitoring Platform

Abstract Background The emergence of COVID-19 resulted in postponement of nonemergent surgical procedures for cardiac patients in London. mHealth represented a potentially viable mechanism for highlighting deteriorating patients on the lengthened cardiac surgical waiting lists. Objective To evaluate the deployment of a digital health solution to support continuous triaging of patients on a cardiac surgical waiting list. Method An NHS trust utilized an app-based mHealth solution (Huma Therapeutics) to help gather vital information on patients awaiting cardiac surgery (valvular and coronary surgery). Patients at a tertiary cardiac center on a waiting list for elective surgery were given the option to be monitored remotely via a mobile app until their date of surgery. Patients were asked to enter their symptoms once a week. The clinical team monitored this information remotely, prompting intervention for those patients who needed it. Results Five hundred and twenty-five patients were on boarded onto the app. Of the 525 patients using the solution, 51 (9.71%) were identified as at risk of deteriorating based on data captured via the remote patient monitoring platform and subsequently escalated to their respective consultant. 81.7% of patients input at least one symptom after they were on boarded on the platform. Discussion Although not a generalizable study, this change in practice clearly demonstrates the feasibility and potential benefit digital remote patient monitoring can have in triaging large surgical wait lists, ensuring those that need care urgently receive it. We recommend further study into the potential beneficial outcomes from preoperative cardiac mHealth solutions.

scholarly journals Mobile app-based Remote Patient Monitoring in Acute Medical Conditions: A Prospective Feasibility Study Exploring Digital Health Solutions on Clinical Workload during the COVID Crisis. (Preprint)

2020 ◽  
Author(s):  
Sachin Shailendra Shah ◽  
Andrew Gvozdanovic ◽  
Matthew Knight ◽  
Julien Gagnon
Keyword(s):  
Feasibility Study ◽  
Patient Monitoring ◽  
Mobile App ◽  
Full Time ◽  
Remote Patient Monitoring ◽  
Phone Calls ◽  
Clinical Scenarios ◽  
Remote Patient ◽  
The Impact ◽  
Clinical Workload

BACKGROUND Digital remote patient monitoring (RPM) can add value to virtual wards; this has become more apparent in the context of the COVID-19 pandemic. Healthcare providers are overwhelmed resulting in clinical teams spread more thinly. We aim to assess the impact of the introduction of an app-based RPM (Huma Therapeutics) on a clinician's workload in the context of a COVID-19 specific virtual ward. OBJECTIVE This prospective feasibility study aims to evaluate the health economic effect (in terms of clinical workload) a mobile app has on a telephone based virtual ward in the monitoring of COVID-19 patients clinically ready for discharge from hospital. METHODS A prospective feasibility study was carried out over one month where clinician workload was monitored, and full time equivalents (FTE) savings equated. An NHS hospital repurposed a telephone-based respiratory virtual ward for COVID-19. Amber status (NHS definition) COVID-19 patients were monitored for 14 days post-discharge to help identify deteriorating patients earlier. A smartphone-based app was introduced to monitor data points submitted by the patients with telephone calls used for communication. A comparison of clinical workload between those monitored by telephone only (Cohort 1) with those monitored via mobile app and telephone (Cohort 2) was undertaken. RESULTS 56 patients were enrolled in the app-based virtual ward (Cohort 2). Digital RPM reduced the number of phone calls from a mean total of 9 to 4 over monitoring period. There was no change in the mean duration of phone calls (8.5minutes), and no reports of readmissions or mortality. This equates to a mean saving of 47.60 working hours. This translates to 3.30 fewer FTEs (raw phone call data), resulting in 1.1 fewer FTEs required to monitor 100 patients when adjusted for time spent reviewing app data. Individual clinicians were averaging 10.9 minutes per day. CONCLUSIONS Smartphone-based RPM technologies may offer tangible reductions in clinician workload at a time of severe service strain. In this small pilot, we demonstrate the economic and operational impact digital RPM technology can have in improving working efficiency and reducing operational costs. Whilst this particular RPM solution was deployed for the COVID-19 pandemic, it may set a precedent for wider utilisation of digital RPM solutions in other clinical scenarios where increased care delivery efficiency is sought. CLINICALTRIAL

Abstract P120: Feasibility Of An Asynchronous, Semi-Automated Remote Patient Monitoring Blood Pressure Management System

Hypertension ◽  
2021 ◽  
Vol 78 (Suppl_1) ◽  
Author(s):  
Ashish Sarraju ◽  
Meg Babakhanian ◽  
Irvin Szeto ◽  
Clark Seninger ◽  
Tara I Chang ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Pilot Study ◽  
Patient Monitoring ◽  
The United States ◽  
User Feedback ◽  
Mobile App ◽  
Remote Patient Monitoring ◽  
Rpm System ◽  
Remote Patient ◽  
High Engagement

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.

scholarly journals Remote Patient Monitoring Using Radio Frequency Identification (RFID) Technology and Machine Learning for Early Detection of Suicidal Behaviour in Mental Health Facilities

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 776
Author(s):  
Xiaohui Tao ◽  
Thanveer Basha Shaik ◽  
Niall Higgins ◽  
Raj Gururajan ◽  
Xujuan Zhou
Keyword(s):  
Mental Health ◽  
Machine Learning ◽  
Radio Frequency Identification ◽  
Patient Monitoring ◽  
Vital Signs ◽  
Remote Patient Monitoring ◽  
Rfid Technology ◽  
Rpm System ◽  
Frequency Identification ◽  
Remote Patient

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.

Leadless and Wireless Cardiac Devices: The Next Frontier in Remote Patient Monitoring

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