Business Efficient Security for Health

Healthcare providers are totally reliant on electronic systems for the processing of patient data. Patient records contain some of the most sensitive and private information about individuals that is imaginable. Without appropriate PETs and SETs in place, there is an obvious risk that patient data will be accessed and used unlawfully.

The privacy and security of patient data is now subject to heightened public interest and regulatory attention, following many high profile cases of privacy and security breaches.

The law now has a very low tolerance for lapses of privacy and security in the healthcare sector. This is evidenced in the enforcement action taken by regulators and in court judgements across Europe. Failure to comply with the law can lead to very serious legal consequences, including criminal prosecutions, penalties and sanctions, and significant operational challenges, such as business disruption, financial loss and damage to brand and reputation. In the last 3 years, the Spanish data protection authority has issued fines of over €40 million and the UK data protection regulator has issued fines of over £5 million for breaches of data protection law. These figures will be significantly higher when the proposed mega fines in the draft EU Data Protection Regulation are approved.

Download from eHealthNews.eu: Business Efficient Security for Health (.pdf, 4.251 KB).

About Imprivata
Imprivata is a leading provider of authentication and access management solutions for the healthcare industry. Imprivata's single sign-on, authentication management and secure communications solutions enable fast, secure and more efficient access to healthcare information technology systems to address multiple security challenges and improve provider productivity for better focus on patient care.

Most Popular Now

AI System Helps Doctors Identify Patient…

A new study from Vanderbilt University Medical Center shows that clinical alerts driven by artificial intelligence (AI) can help doctors identify patients at risk for suicide, potentially improving prevention efforts...

Smartphone App can Help Reduce Opioid Us…

Patients with opioid use disorder can reduce their days of opioid use and stay in treatment longer when using a smartphone app as supportive therapy in combination with medication, a...

AI's New Move: Transforming Skin Ca…

Pioneering research has unveiled a powerful new tool in the fight against skin cancer, combining cutting-edge artificial intelligence (AI) with deep learning to enhance the precision of skin lesion classification...

Leveraging AI to Assist Clinicians with …

Physical examinations are important diagnostic tools that can reveal critical insights into a patient's health, but complex conditions may be overlooked if a clinician lacks specialized training in that area...

AI can Improve Ovarian Cancer Diagnoses

A new international study led by researchers at Karolinska Institutet in Sweden shows that AI-based models can outperform human experts at identifying ovarian cancer in ultrasound images. The study is...

Predicting the Progression of Autoimmune…

Autoimmune diseases, where the immune system mistakenly attacks the body's own healthy cells and tissues, often have a preclinical stage before diagnosis that’s characterized by mild symptoms or certain antibodies...

Major EU Project to Investigate Societal…

A new €3 million EU research project led by University College Dublin (UCD) Centre for Digital Policy will explore the benefits and risks of Artificial Intelligence (AI) from a societal...

New AI Tool Uses Routine Blood Tests to …

Doctors around the world may soon have access to a new tool that could better predict whether individual cancer patients will benefit from immune checkpoint inhibitors - a type of...

Using AI to Uncover Hospital Patients�…

Across the United States, no hospital is the same. Equipment, staffing, technical capabilities, and patient populations can all differ. So, while the profiles developed for people with common conditions may...

New Method Tracks the 'Learning Cur…

Introducing Annotatability - a powerful new framework to address a major challenge in biological research by examining how artificial neural networks learn to label genomic data. Genomic datasets often contain...