Identifying Emerging and Future Risks in Remote Health Monitoring and Treatment

Identifying Emerging and Future Risks in Remote Health Monitoring and TreatmentSince 2007, ENISA has been conducting a series of activities towards developing a comprehensive framework for identifying and assessing emerging and future risks (EFR). As a result of these activities, ENISA has constructed an EFR Framework. The EFR Framework is scenario-based and consists of certain phases for the formulation and analysis of scenarios, mobilisation of the necessary expertise (human resources) to assess and analyse the scenarios and leveraging of the management capabilities to collect and disseminate assessed information (e.g., scenario descriptions, threats, vulnerabilities, assets, impacts, risks, etc.).

The agency also sought to validate a European capacity for the evaluation of those risks to network and information security that may emerge in the near term, i.e. over the next three years. The work in this area is relatively new and, as such, calls for the interaction and co-operation of many leading experts from different disciplines, which is why ENISA established an EFR Stakeholder Forum and consulted with other subject matter experts. The EFR Stakeholder Forum, comprising partners and experts from industry, EU organisations and Member States, supports the agency in its deliberations on and assessment of EFRs and has contributed significantly to this pilot.

The pilot was undertaken in order to test and provide a "proof-of-concept" of the developed and proposed EFR Framework. It is based on a scenario in the area of remote health monitoring and treatment, an area which was selected after discussions with the EFR Stakeholder Forum. This report presents the results of the pilot exercise.

Download "Being diabetic in 2011" Identifying Emerging and Future Risks in Remote Health Monitoring and Treatment (.pdf 958 KB).

Download from the eHealthNews.EU Portal's mirror: "Being diabetic in 2011" Identifying Emerging and Future Risks in Remote Health Monitoring and Treatment (.pdf 958 KB).

For further information, please visit:
http://enisa.europa.eu

Most Popular Now

500 Patient Images per Second Shared thr…

The image exchange portal, widely known in the NHS as the IEP, is now being used to share as many as 500 images each second - including x-rays, CT, MRI...

Is Your Marketing Effective for an NHS C…

How can you make sure you get the right message across to an NHS chief information officer, or chief nursing information officer? Replay this webinar with Professor Natasha Phillips, former...

We could Soon Use AI to Detect Brain Tum…

A new paper in Biology Methods and Protocols, published by Oxford University Press, shows that scientists can train artificial intelligence (AI) models to distinguish brain tumors from healthy tissue. AI...

Welcome Evo, Generative AI for the Genom…

Brian Hie runs the Laboratory of Evolutionary Design at Stanford, where he works at the crossroads of artificial intelligence and biology. Not long ago, Hie pondered a provocative question: If...

Telehealth Significantly Boosts Treatmen…

New research reveals a dramatic improvement in diagnosing and curing people living with hepatitis C in rural communities using both telemedicine and support from peers with lived experience in drug...

AI can Predict Study Results Better than…

Large language models, a type of AI that analyses text, can predict the results of proposed neuroscience studies more accurately than human experts, finds a new study led by UCL...

Using AI to Treat Infections more Accura…

New research from the Centres for Antimicrobial Optimisation Network (CAMO-Net) at the University of Liverpool has shown that using artificial intelligence (AI) can improve how we treat urinary tract infections...

Research Study Shows the Cost-Effectiven…

Earlier research showed that primary care clinicians using AI-ECG tools identified more unknown cases of a weak heart pump, also called low ejection fraction, than without AI. New study findings...

New Guidance for Ensuring AI Safety in C…

As artificial intelligence (AI) becomes more prevalent in health care, organizations and clinicians must take steps to ensure its safe implementation and use in real-world clinical settings, according to an...

Remote Telemedicine Tool Found Highly Ac…

Collecting images of suspicious-looking skin growths and sending them off-site for specialists to analyze is as accurate in identifying skin cancers as having a dermatologist examine them in person, a...

Philips Aims to Advance Cardiac MRI Tech…

Royal Philips (NYSE: PHG, AEX: PHIA) and Mayo Clinic announced a research collaboration aimed at advancing MRI for cardiac applications. Through this investigation, Philips and Mayo Clinic will look to...

Deep Learning Model Accurately Diagnoses…

Using just one inhalation lung CT scan, a deep learning model can accurately diagnose and stage chronic obstructive pulmonary disease (COPD), according to a study published today in Radiology: Cardiothoracic...