Artificial intelligence-based technologies to aid lung function measurement for the diagnosis of suspected lung conditions: Early Value Assessment

Lung function measurement, also called lung function test, pulmonary function test (PFT), or breathing test, measures how well the lungs are working. There are several tests measuring the lung function, including peak flow test, spirometry and bronchodilator responsiveness (reversibility) test, lung volume measurement, gas transfer test, respiratory muscle strength, exhaled carbon monoxide levels, and fractional exhaled nitric oxide testing (FeNO). NICE will conduct an early value assessment into lung function measurement.

Status:

In progress

Technology type:

Device

Decision:

Selected

Reason for decision:

Anticipate the topic will be of importance to patients, carers, professionals, commissioners and the health of the public to ensure clinical benefit is realised, inequalities in use addressed, and help them make the best use of NHS resources

Description:

This topic area has been identified by NICE as a clinical area of importance. Respiratory disease affects one in 5 people and is the third biggest cause of death in England. The most common lung conditions are asthma and chronic pulmonary obstructive disorder (COPD). Symptoms may be common to a number of conditions, and can include wheezing, breathlessness and coughing. Objective lung function measurement tests are therefore needed to confirm the diagnosis for people with suspected lung disease. There are artificial intelligence (AI) supported technologies which could aid clinicians by interpreting lung function measurement results alongside consideration of the person’s clinical history to suggest a likely diagnosis. In current practice there are a number of challenges with lung function measurement tests such as spirometry. Firstly, access to testing has been a challenge in primary care since COVID-19, with many areas of the country having had no test access for many years. Secondly, some people may find it difficult to do the breathing technique that is required to successfully complete some tests. Where tests are available and can be performed, having enough skilled health care professionals who can quality assure and correctly interpret test results is another challenge in primary care settings. Healthcare providers should be skilled in quality assuring lung function measurement tests to ensure the results are reliable. Interpretation of test results alongside the person’s clinical history requires skill and experience to ensure a correct diagnosis is made. These issues mean that diagnosis of lung conditions often takes place following a referral to secondary care where there is better access to specialist testing equipment and experience. This means that receiving a correct diagnosis and access to appropriate treatment can be delayed. AI-supported technologies for lung function measurement have the potential to improve the number of accurate diagnoses of lung conditions made in community and primary care settings. This could mean earlier diagnosis and access to treatment, leading to better patient outcomes. Such technologies may also have benefits for the NHS by enabling less-experienced healthcare professionals to confirm a diagnosis. NICE’s HealthTech programme will assess the clinical and cost-effectiveness of using AI technologies to aid lung function measurement for the diagnosis of suspected lung conditions in order to make recommendations on their use in the NHS.

Provisional Schedule

Scoping workshop:

11 August 2025

Scope published:

26 August 2025

Committee meeting: 1:

18 November 2025

Draft guidance:

07 January 2026 - 21 January 2026

Committee meeting: 2 (if required):

03 February 2026

Resolution:

05 March 2026

Expected publication:

02 April 2026

Project Team

Project lead

Catherine Pank

Email enquiries

If you have any queries please email [email protected]

Stakeholders

External assessment group

The Newcastle Upon Tyne Hospitals NHS Foundation Trust (NuTH)

Timeline

Key events during the development of the guidance:

For further information on our processes and methods, please see our early value assessment interim statement.