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    Evidence generation plan for HTE10063 Digital technologies to support asthma self-management

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    6 Implementation considerations

    The following considerations around implementing the evidence generation process have been identified through working with system partners:

    • The companies should provide training for staff in using the technologies, when support is needed. The training and implementation period should be before the data collection period and be sufficient to account for potential learning effects.

    • Evidence generation should be overseen by a steering group that includes researchers, commissioners, practitioners and people with lived experience.

    • The evidence generation process is most likely to succeed with dedicated research staff, to reduce the burden on NHS staff.

    • Sites should be carefully selected to maximise data collection, when appropriate, and ensure that services representative of those in the NHS are included.

    • Careful planning of the approach to information governance is vital. The companies should have appropriate structures and policies in place to ensure that the data is handled in a confidential and secure manner and in line with appropriate ethical and quality standards.

    The following barriers to implementing the evidence generation process have been identified through working with system partners:

    • the availability of research funds for data collection, analysis and reporting, as well as NHS funding to cover the costs of implementing the technologies in clinical practice

    • lack of expertise and staff to collect data

    • burden on clinical staff, such as needing training before implementation, data collection and follow up

    • variable levels of digital literacy, affecting uptake and use of the technologies

    • support for languages other than English, affecting the uptake and use of the technologies.

    The committee also highlighted practical considerations for implementation:

    • Some outcomes (such as lung function indices) have different relevance across age groups. For example, in children, forced expiratory volume in 1 second (FEV1) is less reliable, but symptom patterns and exacerbation history may be more informative for decision making.

    • Technologies may be used for routine day-to-day management or to support remote clinical assessment. These 2 use cases have different implications for cost effectiveness, safety monitoring and staff workload.

    • Improving adherence is not an end in itself; the focus should remain on downstream clinical outcomes, such as reducing exacerbations, steroid use, emergency department visits and symptom improvement.

    • Automatic data collection is preferable. Manual entry may decline over time, reducing data quality and completeness.

    ISBN: [to be added at publication]