scholarly journals Novel Data Collection and Analytics Tools for Remote Patient Monitoring in Heart Failure (Nov-RPM-HF) Trial: Protocol for Trial Design (Preprint)

10.2196/32873 ◽  
2021 ◽  
Author(s):  
Ankit Bhatia ◽  
Gregory Ewald ◽  
Thomas Maddox
Keyword(s):  
Heart Failure ◽  
Data Collection ◽  
Trial Design ◽  
Patient Monitoring ◽  
Trial Protocol ◽  
Remote Patient Monitoring ◽  
Remote Patient

Novel Data Collection and Analytics Tools for Remote Patient Monitoring in Heart Failure (Nov-RPM-HF) Trial: Rationale of Trial Design (Preprint)

2021 ◽  
Author(s):  
Ankit Bhatia ◽  
Gregory Ewald ◽  
Thomas Maddox
Keyword(s):  
Heart Failure ◽  
Data Collection ◽  
Patient Monitoring ◽  
Patient Adherence ◽  
Performance Status ◽  
Prospective Trial ◽  
Emergency Department Visits ◽  
Remote Patient Monitoring ◽  
Home Based ◽  
Remote Patient

UNSTRUCTURED Heart Failure (HF) remains a leading cause of mortality, and a major driver of healthcare utilization. Effective outpatient management requires the ability to identify and manage impending HF decompensation. Remote patient monitoring (RPM) aims to further address this current need in HF care. To date, RPM approaches employing noninvasive, home-based patient sensors have failed to demonstrate clinical efficacy. The Novel Data Collection and Analytics Tools for Remote Patient Monitoring in Heart Failure Trial (Nov-RPM-HF) aims to address current noninvasive RPM limitations. Nov-RPM-HF will evaluate a clinician-codesigned RPM platform employing emerging data collection and presentation tools. These tools include: (1) a ballistocardiograph to monitor nocturnal patient biometrics, such as heart and respiratory rate, (2) clinical alerts for abnormal biometrics, and (3) longitudinal data presentation for clinician review. Nov-RPM-HF is a 100-patient single-center prospective trial, evaluating patients over 6 months. Outcomes will include: (1) patient adherence to data collection, (2) patient/clinician-perceived utility of the RPM platform, (3) medication changes- including the titration of guideline-directed medical therapy to target doses, (4) HF symptoms/performance status, and (5) unplanned HF hospitalizations or emergency department visits. The results will help to inform the role of noninvasive RPM as a viable clinical management strategy in HF care.

Remote Patient Monitoring in Chronic Heart Failure

2013 ◽  
Vol 21 (3) ◽  
pp. 141-150 ◽  
Author(s):  
Chandrasekar Palaniswamy ◽  
Aaron Mishkin ◽  
Wilbert S. Aronow ◽  
Ankur Kalra ◽  
William H. Frishman
Keyword(s):  
Heart Failure ◽  
Chronic Heart Failure ◽  
Patient Monitoring ◽  
Remote Patient Monitoring ◽  
Remote Patient

scholarly journals Enabling Remote Patient Monitoring Through the Use of Smart Thermostat Data in Canada: Exploratory Study (Preprint)

2020 ◽  
Author(s):  
Kirti Sundar Sahu ◽  
Arlene Oetomo ◽  
Plinio Pelegrini Morita
Keyword(s):  
Data Collection ◽  
Health Monitoring ◽  
Smart Home ◽  
Patient Monitoring ◽  
Health Agency ◽  
Motion Sensors ◽  
Remote Patient Monitoring ◽  
The Public ◽  
Remote Patient ◽  
Smart Thermostat

BACKGROUND Advances in technology have made the development of remote patient monitoring possible in recent years. However, there is still room for innovation in the types of technologies that are developed, used, and implemented. The smart thermostat solutions provided in this study can expand beyond typically defined features and be used for improved holistic health monitoring purposes. OBJECTIVE The aim of this study is to validate the hypothesis that remote motion sensors could be used to quantify and track an individual’s movements around the house. On the basis of our results, the next step would be to determine if using remote motion sensors could be a novel data collection method compared with the national census-level surveys administered by governmental bodies. The results will be used to inform a more extensive implementation study of similar smart home technologies to gather data for machine learning algorithms and to build upon pattern recognition and comprehensive health monitoring. METHODS We conducted a pilot study with a sample size of 8 to validate the use of remote motion sensors to quantify movement in the house. A large database containing data from smart home thermostats was analyzed to compare the following indicators; sleep, physical activity, and sedentary behavior. These indicators were developed by the Public Health Agency of Canada and are collected through traditional survey methods. RESULTS The results showed a significant Spearman rank correlation coefficient of 0.8 (<i>P&lt;</i>.001), which indicates a positive linear association between the total number of sensors activated and the total number of indoor steps traveled by study participants. In addition, the indicators of sleep, physical activity, and sedentary behavior were all found to be highly comparable with those attained by the Public Health Agency of Canada. CONCLUSIONS The findings demonstrate that remote motion sensors data from a smart thermostat solution are a viable option when compared with traditional survey data collection methods for health data collection and are also a form of zero-effort technology that can be used to monitor the activity levels and nature of activity of occupants within the home. CLINICALTRIAL

scholarly journals Enabling Remote Patient Monitoring Through the Use of Smart Thermostat Data in Canada: Exploratory Study

10.2196/21016 ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. e21016
Author(s):  
Kirti Sundar Sahu ◽  
Arlene Oetomo ◽  
Plinio Pelegrini Morita
Keyword(s):  
Data Collection ◽  
Health Monitoring ◽  
Smart Home ◽  
Patient Monitoring ◽  
Health Agency ◽  
Motion Sensors ◽  
Remote Patient Monitoring ◽  
The Public ◽  
Remote Patient ◽  
Smart Thermostat

Background Advances in technology have made the development of remote patient monitoring possible in recent years. However, there is still room for innovation in the types of technologies that are developed, used, and implemented. The smart thermostat solutions provided in this study can expand beyond typically defined features and be used for improved holistic health monitoring purposes. Objective The aim of this study is to validate the hypothesis that remote motion sensors could be used to quantify and track an individual’s movements around the house. On the basis of our results, the next step would be to determine if using remote motion sensors could be a novel data collection method compared with the national census-level surveys administered by governmental bodies. The results will be used to inform a more extensive implementation study of similar smart home technologies to gather data for machine learning algorithms and to build upon pattern recognition and comprehensive health monitoring. Methods We conducted a pilot study with a sample size of 8 to validate the use of remote motion sensors to quantify movement in the house. A large database containing data from smart home thermostats was analyzed to compare the following indicators; sleep, physical activity, and sedentary behavior. These indicators were developed by the Public Health Agency of Canada and are collected through traditional survey methods. Results The results showed a significant Spearman rank correlation coefficient of 0.8 (P<.001), which indicates a positive linear association between the total number of sensors activated and the total number of indoor steps traveled by study participants. In addition, the indicators of sleep, physical activity, and sedentary behavior were all found to be highly comparable with those attained by the Public Health Agency of Canada. Conclusions The findings demonstrate that remote motion sensors data from a smart thermostat solution are a viable option when compared with traditional survey data collection methods for health data collection and are also a form of zero-effort technology that can be used to monitor the activity levels and nature of activity of occupants within the home.

The Impact of Remote Patient Monitoring (Telehealth) upon Medicare Beneficiaries with Heart Failure

2012 ◽  
Vol 18 (2) ◽  
pp. 101-108 ◽  
Author(s):  
Renée Pekmezaris ◽  
Irina Mitzner ◽  
Kathleen R. Pecinka ◽  
Christian N. Nouryan ◽  
Martin L. Lesser ◽  
...  
Keyword(s):  
Heart Failure ◽  
Patient Monitoring ◽  
Medicare Beneficiaries ◽  
Remote Patient Monitoring ◽  
Remote Patient ◽  
The Impact
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