Evidence generation plan for digital front door technologies to gather service user information for NHS Talking Therapies for anxiety and depression assessments
2 Evidence gaps
This section describes the evidence gaps, why they need to be addressed and their relative importance for future committee decision making.
The committee will not be able to make a positive recommendation without the essential evidence gaps (see section 2.1) being addressed. The companies can strengthen the evidence base by also addressing as many other evidence gaps (see section 2.2) as possible. This will help the committee to make a recommendation by ensuring it has a better understanding of the patient or healthcare system benefits of the technologies.
2.1 Essential evidence for future committee decision making
Quality of information collected by the digital technologies and impact on clinical assessment
Evidence on the quality of the information collected by the technologies, and their impact on subsequent clinical assessment is limited. The potential time-savings offered by the technologies could improve the quality of the clinical assessment. They could do this by reducing the time spent on gathering or revising routinely-collected information and increasing the time spent on in-depth conversations to better identify problems and start treatment. More evidence on time-savings will also support future cost-effectiveness modelling.
Impact of the technologies on clinical decision making and quality of life
A higher-quality clinical assessment could improve the chances of identifying the correct treatment pathway. There is limited evidence around the impact of the technologies on clinical decision making. More evidence on the impact of changes in treatments or service use after using the technologies will support future clinical- and cost-effectiveness modelling. The potential impact could include changes in:
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treatment (prescribed medicines or the intensity of the psychological treatment)
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the service pathway followed compared with current practice
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clinical outcomes, ideally measured using:
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problem descriptors (for example, the International Statistical Classification of Diseases and Related Health Problems 10th Revision [ICD‑10])
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the Patient Health Questionnaire‑9 (PHQ‑9) for depression
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the Anxiety Disorder Specific Measure (ADSM) for anxiety
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the Work and Social Adjustment Scale (WSAS) for the extent to which mental health problems interfere with daily life.
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If additional features outside of the current scope of this assessment are being used (for example, technology-derived problem descriptors to support diagnoses), more data on the accuracy of the problem descriptors in relation to a 'gold standard' is needed.
Resource and service impact
More evidence is needed to determine whether the technologies offer time-savings before or during a clinical assessment, and if there is any impact on administrative burden. Evidence is also needed on whether any time-savings offered translate into improvements in system efficiencies. To reduce uncertainty around the potential burden on NHS Talking Therapies services, data is needed on the:
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number of self-referrals from using the technologies
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proportion of people who complete a successful course of treatment.
More information is also needed on the costs of using the technologies in the NHS to support future economic modelling.
2.2 Evidence that further supports committee decision making
User engagement and experience
More evidence on intervention completion rates and user-reported outcomes, including user preferences and acceptability, will help NICE's committee:
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assess the real-world uptake of the technologies
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identify any potential barriers to using the technologies.
There is some evidence that the technologies may improve access to mental health services for people from ethnic minority backgrounds. Further data collection on user characteristics (for example, ethnic background) or service characteristics (for example, geographic location or service size) will support subgroup analyses to assess accessibility of the technologies in different populations.
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