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    Draft Guidance for HTE10063 Digital technologies to support self-management of asthma

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    4 Committee discussion

    The medical technologies advisory committee considered evidence on digital technologies to support self-management of asthma from several sources. This included evidence submitted by the companies, a review of clinical and cost evidence by the external assessment group (EAG), and responses from stakeholders. Full details are available in the project documents for this guidance.

    The condition

    4.1

    Asthma is a long-term respiratory condition that can affect children, young people and adults. It happens when the airways swell and narrow because of allergies or other stimuli, making it hard to breathe. This can cause symptoms such as recurring episodes of wheezing, shortness of breath, chest tightness and coughing. The symptoms may get worse over time and can limit a person's ability to undertake daily activities. There may also be flare-ups or exacerbations, which can result in hospitalisation.

    Current practice

    4.2

    Recommendations for self-management of asthma are in section 1.14 of the BTS, NICE and SIGN guideline on asthma. These include offering a personalised asthma action plan (PAAP) to adults, young people and children aged 5 and over with a diagnosis of asthma (and their families or carers, if appropriate). A PAAP should include:

    • information on minimising exposure to asthma triggers

    • guidance on increasing inhaled corticosteroid dose if asthma control worsens and guidance on what to do if symptoms do not improve

    • advice on when to contact a healthcare professional if asthma control deteriorates.

    4.3

    Clinical experts reported that in current practice PAAPs are not always provided. They added that, even when they are provided, some people can misplace or forget their PAAP. Some people may also find it difficult to remember the steps in their PAAP or may apply them incorrectly because they do not fully understand their PAAP.

    Unmet need

    4.4

    Uncontrolled asthma is common and can lead to emergency department visits, hospital admissions and avoidable deaths. Clinical experts said that many people do not have structured self-management support. They added that people can have poor engagement with written action plans, incorrect inhaler technique and non-adherence with medications. People do not always get tailored advice, especially young people, people who are underserved and people who are newly diagnosed. Asthma service provision varies, and inequalities are barriers to access and quality of care. Clinical experts reported that self-management is key in managing asthma, and there is a significant unmet need for effective self-management support.

    Patient considerations

    4.5

    A patient expert explained how reminders from a digital technology had helped them remember to take their medication. They said that using the technology had reduced their anxiety about managing their asthma. They said that it also helped improve efficiency and focus at GP appointments because of data sharing and because their PAAP was stored digitally. But the patient expert cautioned that these tools should complement and not replace current care. They highlighted that the technologies could help overcome barriers such as poor engagement with written PAAPs and incorrect inhaler technique. They emphasised that digital technologies needed to be simple and inclusive and should consider diverse needs and incorporate safeguarding when used by younger people.

    Clinical effectiveness

    Evidence base

    4.6

    The evidence comprised:

    • 5 published studies, including:

      • 1 UK observational study

      • 1 UK service evaluation

      • 3 international studies (including 1 randomised controlled trial)

    • 10 unpublished studies

    • 5 conference abstracts.

      The committee acknowledged that the quantity and quality of studies for each technology vary. Some of the evidence from peer-reviewed studies was done outside of the UK, in Sweden, the US, Thailand and the Netherlands. Clinical experts explained that because of differences in healthcare settings and care pathways this evidence is unlikely to be generalisable to NHS clinical practice. So, the committee agreed that UK-based evidence is needed.

    4.7

    Qualitative data exploring patient perspectives, usability and acceptability was available for 4 technologies. There is limited evidence on user experience from the UK.

    Impact on asthma and patient outcomes

    4.8

    The committee noted that evidence focused on clinical outcomes (asthma control and exacerbations) and patient-reported outcomes (quality of life and acceptability) and included some data on medication use and adherence. The committee noted that evidence from some of the studies suggests that digital technologies:

    • improve asthma-control and quality-of-life scores

    • reduce hospitalisations or emergency department visits

    • reduce rescue medication use or increase controller medication use.

      The committee agreed that early evidence suggests that digital technologies can support self-management of asthma.

    4.9

    When reported, ease of use and acceptability was generally high. The committee noted that qualitative evidence suggests digital technologies may improve symptom awareness and understanding of asthma.

    Clinical evidence gaps

    4.10

    The committee noted several evidence gaps that should be addressed in future research. It said that demographics (such as age, sex, ethnicity and socioeconomic status) and clinical details (such as asthma control and comorbidities) were poorly reported. It also said that disease severity was inconsistently defined across studies. Evidence was mainly related to uncontrolled asthma populations, which it said limited generalisability to the wider asthma population. Other limitations included a reliance on self-reported outcomes, variation in measurement tools, small sample sizes and short follow-up periods (less than 12 months). Evidence was lacking for some subgroups including children under 5 (supported by parents and carers), people with severe asthma and people who are newly diagnosed. The committee agreed that further evidence is needed to address these gaps and strengthen confidence in the clinical effectiveness of digital technologies to support self-management of asthma.

    4.11

    The committee highlighted the need to generate evidence using validated tools (such as asthma control test, asthma quality of life questionnaire, asthma control questionnaire, lung function tests) to assess the impact of the technologies on key asthma outcomes, particularly in the longer term. It also highlighted the need for robust peer-reviewed studies with adequate sample sizes and to include diverse populations, including children, adolescents and people with severe or newly diagnosed asthma. It agreed that further qualitative evidence on whether the technologies can help improve people's knowledge, support self-management and promote appropriate use of their PAAPs and treatment regimens would also be useful.

    Value of connected devices

    4.12

    The committee noted that some of the apps can be connected to spirometers, peak flow meters or smart inhalers, enabling people to track and monitor lung function, medication use and inhaler technique. Clinical experts explained that there is currently no evidence that tracking lung function is linked to improved outcomes, and questioned the additional value of having connected devices. They also noted that there is no evidence to suggest whether spirometry or peak flow would be more useful as an add on. They added that there may be resource implications for training people to use these devices properly and questioned how reliable the outputs would be, particularly for spirometry. Company representatives confirmed that the apps can also be used independently without connected devices. The committee concluded that further evidence is needed to determine whether the addition of a connected device affects outcomes such as asthma control or exacerbations.

    Safety

    4.13

    The committee noted that there were no adverse events reported and discussed the safety of using the technologies in the NHS during the evidence generation period. It noted the nature of the technologies, which are intended for self-management and should not replace clinical review. Clinical experts added that for most people self-management is currently based on a written PAAP. They said that additional features, such as education, symptom tracking and a digital plan, are unlikely to represent a clinical risk. The committee noted that data security and privacy risks should be mitigated through standard compliance measures and regulations. Clinical experts highlighted that feedback from the patient survey noted an overfocus on data and questioned whether tracking symptoms or lung function could lead to anxiety for some people. The committee agreed that it would be important to collect data on quality of life to see whether there were any adverse effects of increased tracking. The committee concluded that the overall clinical risk of using these digital technologies during the evidence generation period is low.

    Barriers to implementation and uptake

    4.14

    The committee noted that a patient survey provided useful insights and was informative, but was not fully representative of the UK population. So the committee said that caution is needed when generalising feedback on usability and accessibility. It noted that, although these technologies are not yet widely used, people reported positive experiences but with varying ease of use. But concerns were noted around privacy and data sharing. Practical issues such as lack of a smartphone or internet access were identified as barriers for some people. The committee also noted the British Thoracic Society's submission, which noted risks such as short-term increased healthcare use, widening inequalities and implementation challenges. The committee agreed that more data on healthcare resource use is needed and that barriers to use (such as device access, connectivity and digital literacy) and implementation would need to be considered. It said that further evidence exploring these barriers in diverse populations would be useful.

    Cost effectiveness

    Economic model

    4.15

    An exploratory economic model was developed to identify key cost and utility drivers and areas of uncertainty for digital technologies for self-management of asthma compared with standard self-management programmes. Because of the lack of data on clinical outcomes, the model could not be fully developed and was instead used to explore different value propositions. Improved asthma control was considered the most plausible scenario, based on the clinical evidence, despite uncertainty in the magnitude and duration. For this reason, the clinical impact of the technologies was assumed to be the same for all technologies. The EAG used a 5-year time horizon but noted that the time period for most clinical studies was less than a year. The EAG did not include any subgroup analyses in the economic model because there was not enough evidence to inform inputs. The committee concluded that the model structure was appropriate and that the results suggested that the technologies could plausibly be cost effective if they could improve asthma control. But it stated that the inputs were highly uncertain because of very limited clinical evidence and that further evidence generation is needed to address this uncertainty.

    Technology costs

    4.16

    The committee highlighted that the cost of the technologies is currently the key driver in the model. But it acknowledged that the clinical impact was assumed to be the same for all technologies because of a lack of data (see section 3.15). So, the clinical impact would not affect the model's results. The committee noted that costs varied widely between technologies and that technologies with connected devices had higher costs. The committee recalled that there was no clinical evidence to suggest that the addition of a connected device improves outcomes more than a standalone app (see section 3.12) The committee concluded that further evidence generation could reduce uncertainty around clinical outcomes and strengthen future evaluations, particularly for more expensive technologies.

    Uptake and attrition rates

    4.17

    The committee noted that initial uptake and dropout (attrition) rates appear to be important drivers in the model for some technologies and there is currently no data available. The committee agreed that further evidence generation should include reporting on uptake and dropout rates and that qualitative data on user experience would be useful to understand the impact on different groups.

    Equality considerations

    4.18

    The final scope and the equality impact assessment describe the equality considerations for this assessment. The committee noted that the patient survey highlighted some barriers in accessing the technologies, such as neurodiversity, cognitive impairments and communication difficulties. All the companies confirmed that the apps can use the accessibility and adaptability features on a smartphone. They also confirmed that multiple language options are either already available or in development. The committee highlighted the importance of gathering insights from more ethnically diverse groups and from people for whom English is not their first language. It said that this would identify barriers that might affect equality of access. The committee emphasised that future engagement should prioritise diversity and inclusion to ensure digital tools are designed and evaluated to address potential inequalities and support equitable access for all patient groups. The committee thought that, by providing an alternative format of the PAAP and more personalised support, digital technologies could reduce inequalities in care and help engage younger people. It emphasised the importance of involving young people, as well as their parents and carers, in evidence generation.