Digital Health Supporting Screening and Diagnosis

Digital Health devices, such as smartphones, wearable devices and other similar technology, have been revolutionizing tracking and feedback of fitness and wellness objectives in the consumer space.

Virtual healthcare has and continues to see significant innovation and growth, with the speed at which consumers and patients receive results and are able to connect with healthcare professionals continuing to drive development.

Clinicians are increasingly connected and electronically enabled, and healthcare is moving more towards virtualised anytime diagnosis and support from the more traditional hospital and clinical setting. Artificial intelligence and increasingly Internet of all things are being incorporated into diagnostic tools to improve and assist clinicians (and patients) to help analyse, guide and record clinical exams. This has a very wide spectrum, from heart rate and vital signs monitoring to mobile laboratories and so much more.

Businesses in this arena can have operating models that involve a blend of technology. For example, the use of cameras to capture wounds or accident sites, which are shared with clinicians to diagnose and treat, through to Artificial Intelligence algorithms for medical imaging to identify and localise abnormalities on X-rays, or providers of services for online triage.

There are significant liability risks for those involved in providing such services, and the lines between the differing parties can be blurred. In the event of a mis-diagnosis or issue with medical care, is this due to a medical diagnosis, error or advice, or does this link to the App or technology company error in imaging or software faults, or other partners in the chain who may be held liable for compensation and for any injustices or wrongs raised by user?

The growth in the digital screening and diagnosis sector is undeniable, however, risks around liabilities that can be incurred have to be recognised.

• Companies that handle data collected from the device if part of the service. Those that are designing, developing, AI, Chat bots or services linked to support and more
• Companies in a vendor capacity, i.e. software houses. The range of examples is endless, from data security concerns i.e. hacking and theft of users details, through to the failure of software in a device causing a mis-diagnosis.

The range of interconnected services and devices will only continue to grow, which in turn will only increase the use and sharing of data and professional responsibilities. This means the emergence of new and evolving risks. A good insurance programme is of course a backstop for the potential financial impact of such risks.

Claims examples

1. The claimant alleged one week of pain due to an insured’s assistant’s failure to conduct a physical exam, which would have revealed a piece of glass in his foot. The claimant also alleged negligence in prescribing antibiotics without informed consent and claimed the prescribed penicillin derivative could have resulted in a need for an epi-pen, which might have been fatal as the claimant had a pre-existing aortic aneurysm.
2. A medical imaging company created a mobile application which interrelates with tele-radiologists. In this event, which eventually led to death - a patient experienced trauma due to the delay in image availability. Although both parties were sued, after investigation, it was alleged by the reporting facility that the death of the patient was due to a slow transfer of images from the radiology picture, archiving and communications system.

Examples of claims scenarios are not based on actual claims, but are highlighted and shared to evidence where claims may emanate, it should also be noted that insurance coverage provided is very much on a client by client basis so may not provide all the coverage for the examples shown in this ‘discussion document’.