Transparent sharing of digital health data: A call to action

Slotwiner, David J.; Tarakji, Khaldoun G.; Al‐Khatib, Sana M.; Passman, Rod; Saxon, Leslie A.; Peters, Nicholas S.; McCall, Debbe; Turakhia, Mintu P.; Schaeffer, Jill; Mendenhall, G. Stuart; Hindricks, Gerhard; Narayan, Sanjiv M.; Davenport, Elizabeth; Marrouche, Nassir F.

doi:10.1016/j.hrthm.2019.04.042

Cited by 27 publications

(16 citation statements)

References 16 publications

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“…The current lack of infrastructure to facilitate actions in response to data from wearable devices might limit their use in detecting life-threatening arrhythmias. However, professional society guidelines have provided recommendations on the use of wearable cardioverter–defibrillators to prevent sudden cardiac death 95 and have called for increased transparency in monitoring data from CIEDs and consumer arrhythmia-monitoring devices 96 .…”

Section: Cardiovascular Monitoring Guidelinesmentioning

confidence: 99%

Integration of novel monitoring devices with machine learning technology for scalable cardiovascular management

et al. 2020

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Ambulatory monitoring is increasingly important for cardiovascular care but is often limited by the unpredictability of cardiovascular events, the intermittent nature of ambulatory monitors and the variable clinical significance of recorded data in patients. Technological advances in computing have led to the introduction of novel physiological biosignals that can increase the frequency at which abnormalities in cardiovascular parameters can be detected, making expert-level, automated diagnosis a reality. However, use of these biosignals for diagnosis also raises numerous concerns related to accuracy and actionability within clinical guidelines, in addition to medico-legal and ethical issues. Analytical methods such as machine learning can potentially increase the accuracy and improve the actionability of device-based diagnoses. Coupled with interoperability of data to widen access to all stakeholders, seamless connectivity (an internet of things) and maintenance of anonymity, this approach could ultimately facilitate near-real-time diagnosis and therapy. T he se tools are increasingly recognized by regulatory a g e n c ies a n d p r o f e s s ional m e d ic al s oc ie ti es, but several technical and ethical issues remain. In this Review, we describe the current state of cardiovascular monitoring along the continuum from biosignal acquisition to the identification of novel biosensors and the development of analytical techniques and ultimately to regulatory and ethical issues. Furthermore, we outline new paradigms for cardiovascular monitoring.

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Section: Cardiovascular Monitoring Guidelinesmentioning

confidence: 99%

Integration of novel monitoring devices with machine learning technology for scalable cardiovascular management

et al. 2020

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“…A recent HRS statement advocates for transparent and secure access by patients to their digital data 332 . This enables active participation and appropriate self‐management.…”

Section: Patient Self‐management—integrated Chronic Carementioning

confidence: 99%

2021 ISHNE/HRS/EHRA/APHRS collaborative statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals

Varma

Cygankiewicz

Turakhia

et al. 2021

Journal of Arrhythmia

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This collaborative statement from the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society describes the current status of mobile health (“mHealth”) technologies in arrhythmia management. The range of digital medical tools and heart rhythm disorders that they may be applied to and clinical decisions that may be enabled are discussed. The facilitation of comorbidity and lifestyle management (increasingly recognized to play a role in heart rhythm disorders) and patient self‐management are novel aspects of mHealth. The promises of predictive analytics but also operational challenges in embedding mHealth into routine clinical care are explored.

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“…The user will be required to key in specific data such as the laboratory tests done, the procedures undergone and the drugs taken. The data will then be sent to EHRs in the user's hospital of choice for clinician review before being uploaded to the cloud (Slotwiner et al, 2019). Depending on the information transferred to the caregivers, the healthcare providers can determine the medical state of the user and respond accordingly.…”

Section: Medical Recordsmentioning

confidence: 99%

Integration of Smart Wearable Devices and Cloud Computing in the Kenyan Public Health Care System

2021

IKM

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The utilization of smart wearable devices and cloud computing in the Kenyan public health care system will facilitate real-time patient monitoring and management. The shortage of certified healthcare professionals and the limited access to quality specialized care for individuals in remote settings has prompted the adoption of wearable devices and cloud computing strategies in Kenya. However, there lacks a clear framework design of integrating the technologies in the public health sector. This article evaluates the current status of healthcare systems in Kenya. It also investigates the existing mobile health and cloud computing services in the country while evaluating the main legal concerns inherent to the utilization of the technologies. The document further outlines a framework design for a mobile application named GB Health. The application incorporates cloud computing and smart wearable devices in the Kenyan public health care system. The design will enhance workflow and patient outcomes in the sector.

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Transparent sharing of digital health data: A call to action

Abstract: and 7 Functioning as the lay volunteer/patient representative.

Cited by 27 publications

References 16 publications

Integration of novel monitoring devices with machine learning technology for scalable cardiovascular management

Integration of novel monitoring devices with machine learning technology for scalable cardiovascular management

2021 ISHNE/HRS/EHRA/APHRS collaborative statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals

Integration of Smart Wearable Devices and Cloud Computing in the Kenyan Public Health Care System

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