Health Education England publishes AI and digital capability framework

Health Education England (HEE) has published a skills and capabilities framework to support health and care teams with artificial intelligence (AI) and health tech solutions.

Entitled ‘Artificial Intelligence (AI) and Digital Healthcare Technologies Capability Framework’, it builds on previous digital literacy frameworks, and covers six primary areas: digital implementation; digital health for patients and the public; ethical, legal and regulatory considerations; human factors, health data management; and artificial intelligence.

It aims to recognise and support the learning needs of health and care teams, and “allow individual learners to understand their needs in the digital healthcare technology space, across various workforce archetypes, of users, embedders, creators, drivers, and shapers”. It also segments capabilities by four levels, laying out a capability statement for each level, and then highlights available learning resources available.

The framework focuses on:

Digital implementation 

The first element the framework focuses on is digital implementation and identifying different levels of digital maturity.

At the basic level of capability, health and care professionals must be aware of digital enablers and distinguish the main features of tablets, mobile apps, electronic health records and smartwatches.

At the highest level of capability an individual can “capture and model existing information/data pathways” in their organisation to understand current workflows and prepare digital transformation projects.

Digital health for patients and the public 

This includes technology and tools such as wearable tech, mobile apps and telehealth; for example, those used for patient monitoring, communication, direct delivery of care and interventions.

At the basic level of capability, health and care professionals must be aware of a several digital NHS resources relevant to their role or team. They must be able to “give guidance to patients to access and use them appropriately and provide support”.

At the highest level of capability an individual can suggest “digital resources through policies and guidelines to patients and the public for various health conditions based on the Digital Technology Assessment Criteria”.

Ethical, legal and regulatory considerations 

The framework highlights the ethical concerns that surround the use of AI in medical care. It notes that these tools have the “potential to increase or continue to reflect pre-existing biases and inequalities” and increase the digital divide. To address this, the capability aims to “promote equity, fairness and transparency”.

At the basic level of capability, an individual understands the ethical responsibility of AI and digital technology ensuring that processes and systems are transparent, fair and equitable for patients, staff and the public.

At the highest level of capability, a health and care professional must be aware of data collection tools and system to be created for “patient/user diversity so that the output of data processing/analysis will not cause or increase health inequalities”.

Human factors 

This capability covers management and leadership skills and abilities, including change management, culture, and understanding of existing workflows and patient pathways. One of the capability statements is to practice patient and user centred design, acknowledging working with patients and users “to gather and produce requirements, for example, user stories, personas, UML diagrams, etc., to set priorities and evaluate and integrate technologies”.

Health data management / cyber security

Regarding health data management, the framework highlights a capability of understanding “where and how data are stored as well as data-flows and how they are applied to various pathways”.

This part of the framework provides a capability assessment for health and care professionals to be aware of data management/cyber security, to both meet legal requirements and secure public trust, from theft, loss and attacks.

Artificial intelligence 

On AI tech, the framework highlights that at the basic level of capability, health and care professionals must be able to understand the umbrella term of AI in defining digital technologies. They must be aware that AI is “common in modern technology and can list uses of AI outside healthcare”.

The highest level of capability highlights that an individual must be able to describe the types of AI biases that can affect systems such as reporting, group attribution, implicit, and selection. As for using and implementing AI systems, the framework highlights the need to see a “closer working relationship between human experts and AI systems”.

To view the framework, please click here.