In the UK, deaths due to asthma attacks are at their highest level for a decade, but with better diagnostics and tailoring of treatment to asthma sub-type, these could be reduced.  When it comes to asthma diagnosis, innovation is slow. Asthma Diagnostics: A 21st Century Challenge, a new report released by Asthma UK today, highlights the impact of poor diagnostic tools on people with asthma, healthcare professionals, and the NHS. The report proposes more investment and a collaborative research approach.
There are 5.4 million people in the UK who have asthma, but lack of mechanistic understanding means it has been treated as a single condition with inhaled corticosteroids and bronchodilators.  However, “asthma” is a heterogeneous condition caused by many different mechanisms. Leading academics say “asthma” should be considered an umbrella term for several conditions of the airways.  It is not sufficient to know if someone has asthma, we need to know what type they have so they can get the most appropriate treatment. Tests that can do this show promise, but are still in their infancy.
Historically, a diagnosis has been made by seeing if a patient’s symptoms respond to treatment (“trial by treatment”). But simply assuming a patient has “asthma” and prescribing and monitoring their response to treatment means many may be treated sub-optimally. Also, there is the risk of overdiagnosis. People who don’t have asthma may end up taking inappropriate treatment and might suffer side effects as a result. 
It is an inefficient way of spending NHS money. Currently, the NHS spends £1.1billion on asthma care each year, 60% of which is spent on drugs. Yet at least 50% of people with asthma may respond poorly to one of the predominant treatments—inhaled corticosteroids. 
While new NICE guidelines for asthma now explicitly encourage healthcare professionals to use objective testing instead of trial by treatment, in practice it will take time to implement. Training in existing tools like spirometry is expensive and time-consuming.
When diagnostic tests are used in their current form, they are often inadequate. It is particularly challenging to diagnose pre-school children and differentiate between asthma and viral or transient wheeze, and existing tests are too invasive (and expensive) for routine use. Anecdotal evidence from parents in touch with Asthma UK reveal stories of multiple hospital admissions for wheezing symptoms but no definite diagnosis. This can be frustrating for everyone concerned and result in both over- and under-treatment. 
Adults don’t fare much better in being diagnosed effectively. Because asthma is an intermittent, variable condition, tests are only useful if the person is symptomatic on testing and currently there is no simple, non-invasive way of assessing airway hyperreactivity or inflammation over time.
So, what’s the solution? One option is investment in improving existing asthma diagnostic tools and developing new tools. Focus should be based on emerging inflammatory and other biomarkers that can accurately differentiate between different types of asthma. Researchers and device manufacturers need to work together to harness the power of artificial intelligence—creating diagnostic algorithms that could transform the ability of non-specialist healthcare professionals to make an accurate diagnosis. [5,6]
The development and routine use of smart (Bluetooth-connected) inhalers that could passively collect data and transmit it to a patient’s GP, or store it in a mobile phone for future use would enable symptoms to be monitored over time.  It would also provide a more accurate diagnostic picture. This all requires funders, SMEs, researchers and healthcare providers to collaborate in a cross-sector, “team science” approach, sharing data to enable faster progress. People with asthma need to be involved to ensure devices and diagnostic tools are acceptable to them and regulators will need to ensure new technologies are licensed and regulated appropriately. The NHS needs to develop new ways of getting new evidence based and cost effective technologies adopted at scale.
Improved asthma diagnostics would enable people with asthma to get a more accurate diagnosis and personalised treatment, which would likely reduce admissions and asthma deaths. With the global asthma population due to reach 400 million in 2025, there could also be economic benefit to developing better diagnostic tools. Interested stakeholders need to work together to solve this “grand challenge.”
Samantha Walker is director of Policy and Research at Asthma UK and holds a PhD looking at the impact of allergen immunotherapy on allergy and asthma. She has worked in this field for over 25 years, running and designing research projects and teaching and lecturing healthcare professionals.
Competing interests: None further declared.
1. Hospital admissions: Data sourced via bespoke requests to NHS Digital (England), ISD (Scotland), PEDW (Wales), Department of Health (Northern Ireland). Deaths: England & Wales – Office for National Statistics (ONS) https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/causesofdeath); National Records of Scotland (NRS) https://www.nrscotland.gov.uk/search/node/deaths; Northern Ireland Statistics and Research Agency (NISRA) https://www.nisra.gov.uk/statistics/birthsdeaths-and-marriages/deaths).
2. Pavord ID, Beasley R, Agusti A et al. After Asthma: Redefining Airways Diseases. The Lancet Commissions 2017. DOI: https://doi.org/10.1016/S0140-6736(17)30879-6
3 . Bush A and Fleming L. Is asthma overdiagnosed? Arch Dis Child August 2016 Vol 101 No 8. DOI: http://dx.doi.org/10.1136/archdischild-2015-309053
4. McGrath KW, Icitovic N, Boushey HA et al. A Large Subgroup of Mild-to-Moderate Asthma Is Persistently Noneosinophilic American Journal of Respiratory and Critical Care Medicine 2012;185(6):612-619. DOI: https://doi.org/10.1164/rccm.201109-1640OC.
5. Jiang F, Jiang Y, Zhi H, et al. Artificial intelligence in healthcare: past, present and future. Stroke and Vascular Neurology 2017;svn-2017-000101. doi: 10.1136/svn-2017-000101
6. Badnjevic, Almir, et al. “Neuro-fuzzy classification of asthma and chronic obstructive pulmonary disease.” BMC medical informatics and decision making 15.3 (2015): S1
7. Asthma UK, Smart Asthma (2017): https://www.asthma.org.uk/globalassets/get-involved/external-affairs-campaigns/publications/smart-asthma/auk_smartasthma_feb2017.pdf