Reproduced from "Our data-driven future in healthcare: People and partnerships at the heart of health related technologies", a report published by The Academy of Medical Sciences, UK


The set of rules used by a technology to analyse and process data to produce a specific output.

Anonymised data

Data where identifying details/information have been removed or encrypted. There are two types of anonymised information – depersonalised and anonymous, which carry different risks of re-identification.


Where it is not possible to identify an individual from the data as information has been combined from multiple individuals.

Artificial intelligence (AI)

Technologies that have the ability to perform tasks that would otherwise require human intelligence, or which conduct analyses which are either too complex or laborious for a human to carry out, such as visual perception, speech recognition or language translation. They usually have the capacity to learn or adapt to new experiences or stimuli.

Black box systems

Systems or technologies that have limited technical transparency around the processes by which they reach their output, as the algorithms they use are complex and dynamic.


Cost-effectiveness analysis

Evaluation of the effectiveness of two or more interventions relative to their cost to inform decision-making. The aim when assessing new interventions is to identify those that maximise outcomes and minimise costs.

Data-driven technologies

Technologies that work by collecting, using and analysing patient data to support the care of individuals, NHS services, public health, or medical research and innovation. For example, using AI and machine learning to analyse patient data collected in the course of NHS care, which may also be linked to social care data or to data collected by patients themselves such as through wearable technologies and mobile apps.

Data governance

The management of data throughout the life cycle, including ways to ensure data integrity and security, and managing access.


Data integrity

The overall quality and validity of data, which depends on factors including provenance, accuracy, reliability and consistency over its life cycle.

Data life cycle

The different stages of the patient data journey. This involves various organisations and processes, including the generation and collection of data, curation, storage, access, use and its eventual destruction or legacy.

Data processing

The processing or curation of data to allow them to be used more effectively or linked with other datasets.

Depersonalised data

Data which have had any personal identifiers removed or encrypted. There is still a risk of re-identification of an individual if other potential identifiers remain or if the data are linked with other data sources.

Digital literacy

The capabilities and understanding required to allow an individual to effectively engage with a data-driven technology or the processes that surround its use.

Digital maturity

The extent to which an organisation makes use of digital technology to achieve a health and care system that is paper-free at the point of care. This includes consideration of the extent to which providers are able to plan and deploy digital services, have the capability to use digital technology to support delivery of care, and have the underlying infrastructure in place to support these capabilities.

Electronic Health Records (EHRs)

Digital records of a patient’s medical history, health and care.


Healthcare professional

A person who is qualified and allowed by regulatory bodies to provide healthcare to a patient. They include: medical and dental staff; nurses, midwives and health visitors; professionals allied to medicine such as clinical psychologists, dieticians and physiotherapists; ambulance staff and paramedics; and other professionals who

have direct patient contact, such as pharmacists.


Individual care

Healthcare processes or services (such as diagnosis, treatment, management or monitoring) directed at an individual for their care or treatment. ‘Individual care’ is commonly termed ‘direct care’.

Internet of Things

Technologies and platforms embedded in everyday objects that are connected to each other via the internet, which enables them to interact through collecting, linking and exchanging data.

Machine learning

A specific type of algorithm which enables technologies to learn from experience as well as data, and so evolves over time as it learns without human input.

Natural Language Processing

A type of AI which extracts, processes, analyses and interprets written and spoken language.

NHS data stewards Individuals in NHS organisations, or those acting on their behalf, who are responsible for the stewardship and curation of patient data, including controlling how, when and by whom it is collected, stored, accessed or otherwise used.

Patient data

Health-related information about patients that is created or used as part of their NHS care (such as a healthcare professional’s notes and care records, vital signs, laboratory test results, medical images and letters). For the purposes of this report, this may also be linked to information they have collected themselves, or to information collected as part of their related social care. These data may be personally identifiable or anonymised. Anonymised data may comprise depersonalised or anonymous data.

Personally identifiable data

Data that contain personal information that could identify an individual.