Sleepio to treat insomnia symptoms
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4 Committee discussion
Treatment pathway
Sleepio can be used to treat symptoms of insomnia
4.1 The evaluation considered Sleepio as a treatment for the symptoms of insomnia. The proposed patient population included people with symptoms or a diagnosis of insomnia. The committee accepted that this broad population was relevant and understood people could either be referred to this technology by their GP, or choose to self-refer if they live in a region where Sleepio is available. The committee accepted that insomnia symptoms are a common problem and that Sleepio has the potential to benefit many people.
The most relevant comparator is treatment as usual including sleep hygiene advice and short-term medication
4.2 Sleepio provides a sleep improvement programme based on cognitive behavioural therapy for insomnia (CBT‑I) for people with insomnia or symptoms of insomnia. Clinical experts explained that the gold standard treatment for insomnia is face-to-face CBT‑I but its availability is very limited in the NHS. Instead, they agreed with the company that the most relevant comparator is 'treatment as usual', which includes sleep hygiene education and hypnotic medication. There are several other digital technologies that provide CBT‑I or other support for people with insomnia symptoms, but the uptake and use of these technologies is limited. The committee concluded that the appropriate comparator for Sleepio is treatment as usual consisting of sleep hygiene advice and short-term medication.
Sleepio could provide another CBT‑I option, the gold standard treatment for insomnia
4.3 Clinical experts explained that digital CBT‑I, such as Sleepio and other digital CBT‑I technologies, increases the options available to primary and secondary care practitioners when treating insomnia. They explained that the gold standard treatment for insomnia is face-to-face CBT-I but its availability is very limited in the NHS. Although face-to-face CBT-I has some advantages in solving specific patient needs, they thought that difital and face-to-face CBT-I are likely to be similar. The committee considered that there is space in the care pathway for Sleepio. It concluded that Sleepio would provide another option for people to access CBT‑I.
Clinical-effectiveness overview
Sleepio is effective at reducing insomnia symptoms compared with treatment as usual
4.4 The committee noted the large evidence base for Sleepio, and that the 28 studies in the evidence base included a range of patients who had a diagnosis or symptoms of insomnia. The EAC explained that changes in lifestyle are expected as part of treatment as usual, but it is unclear whether there was any explicit control for these factors in the evidence. The committee concluded that the evidence shows that Sleepio is more effective than treatment as usual in reducing symptoms of insomnia in adults.
There is no direct evidence comparing Sleepio with face-to-face CBT‑I or with other digitally facilitated CBT‑I
4.5 The EAC explained that no studies were identified in the literature that compared Sleepio with other methods of delivering CBT‑I directly, such as face-to-face CBT‑I or digital CBT‑I. Clinical experts confirmed that other digital devices are available that also deliver digital CBT‑I. They considered that the clinical effectiveness of Sleepio is likely to be comparable to other digital devices delivering CBT‑I as well as face-to-face CBT‑I, but also recognised that there are some advantages to the latter. The committee recognised the lack of comparative evidence between different delivery methods of CBT‑I was a limitation in the evidence.
Drop-out rates
There are high drop-out rates with Sleepio, but these are thought to be consistent with face-to-face CBT‑I
4.6 The evidence shows a high drop-out rate for people using Sleepio, from 11.2% (Luik et al. 2017) up to 61.6% (Freeman et al. 2017). High drop-out rates were also observed from the rollout of Sleepio in Buckinghamshire, these occurred throughout the programme from session 1 through to session 5. The committee noted that the meta-analysis (Soh et al. 2020) that compared digital CBT‑I (including Sleepio) and face-to-face CBT‑I reported similar levels of engagement and completion in both arms. Clinical experts explained that in some cases people's insomnia symptoms can resolve after sleep hygiene advice. Since Sleepio sessions 2 and 3 include sleep hygiene advice, it is possible some people's symptoms may resolve before completing all 6 sessions of the programme. However, the reason for drop-outs was not recorded so people may have left the programme because they did not experience any improvement in symptoms. The committee concluded the direction of bias as a result of high drop-out rates with Sleepio is unclear, but it recognised that high drop-out rates are common with CBT‑I in general and not specific to Sleepio.
Other patient benefits or issues
Following the Sleepio programme can be challenging but the Sleepio community provides support
4.7 The patient expert described the sleep restriction component and quarter hour rule as particularly challenging aspects of the Sleepio programme that were difficult to implement, especially in the beginning. These challenges were also reported by people who responded to the patient survey. The patient expert said the support from the Sleepio website community was particularly helpful during this time. The company said that the community is monitored by volunteers with experience of using Sleepio. It also said that Sleepio users can have a weekly session with a clinical psychologist if needed and 24‑hour customer service is available. The committee noted the importance of the Sleepio community and its role in supporting people using Sleepio.
Sleepio may be difficult to use for some people
4.8 Sleepio requires access to a computer and the internet and some people do not have a computer or the internet at home. The patient expert said that it was possible to use Sleepio by accessing the internet occasionally (for example, at a public library) and keeping a paper sleep diary, but that this was more difficult. Some users of Sleepio may find it difficult to use a computer, such as people with a visual or cognitive impairment, limited manual dexterity, or hearing impairment. The patient expert said that using Sleepio was relatively straightforward and that people with minimal computer skills could use it. But they agreed that some skill in using a computer is needed. They added that the Sleepio community can help people who need it. Also, Sleepio may be difficult to use for people who have limited English language skills. The company noted that the programme is being restructured so it can be translated into other languages. The committee accepted that Sleepio would be harder to use for some people.
Training
Patient selection and the implementation model used for introducing Sleepio might affect patient uptake and engagement
4.9 The company said that during the roll out of Sleepio they noticed that the different levels of training it provided for referring services (such as GP practices) affected the uptake of Sleepio. It said that training and support varies depending on the implementation model used to introduce it. In the 9 GP practices in the Buckinghamshire region, which used a comprehensive implementation model, the estimated uptake was 0.94%. Regions that did not have this implementation model had an uptake of 0.54% to 0.55% (Sampson et al. 2021). Clinical experts said patient selection was important to improve the chances of people using Sleepio properly and benefiting from it. They also said it would be helpful to give feedback to referrers, such as GPs, about how many people registered to use Sleepio, and how many were in remission. This would help understand outcomes and inform referral and training. The committee agreed that the training and support for referrers has an important effect on patient uptake and engagement.
Side effects and adverse events
Adverse events are rare in people using Sleepio
4.10 The EAC explained that very few adverse events were reported in the literature, and no serious adverse events were related to using Sleepio. Sleepio has been available in some regions of the NHS since 2013 and unpublished real-world evidence reports that over 100,000 people have used Sleepio in the UK. For full information about adverse events in the studies, see section 6 of the EAC's assessment report.
Sleepio is unlikely to harm people who have other sleeping disorders
4.11 Clinical experts said that some people who present with symptoms of insomnia might have underlying conditions causing their symptoms. They explained that using Sleepio in this population may delay them having more appropriate treatment but is unlikely to cause harm. The company said that it has procedures in place for managing risk and adverse events but that they are uncommon. The committee concluded that Sleepio is unlikely to harm people who experience sleeping difficulties because of an underlying condition.
Cost modelling overview
The economic model is uncertain because of limitations in the data available
4.12 The statistical analysis in Sampson et al. (2021) assumed that all changes in resource use over the study duration were because of the introduction of Sleepio. The committee had concerns about whether the variables included in the generalised linear model adequately captured all the important parameters, such as seasonal affect and comorbidities. The EAC reviewed the statistical analysis described in the study and confirmed that it was appropriate, and that it gave similar results to its own preferred statistical model. Despite some reassurance on the statistical analysis, the committee understood it was only possible to adjust for known confounders, and the quasi-experimental nature of the study means some uncertainty remains. The EAC also reported that it was not possible to link individual patient data from Sleepio with NHS resource use data. So, in the NHS data it is unclear which patients used Sleepio, if their symptoms improved with use, and what the associated resource impact was. This meant it was not possible to include remission status in the economic modelling. The committee accepted that the data available was limited, particularly around linking user data to NHS system data, and understood that this resulted in uncertainties in the economic modelling.
Using resource use data at 65 weeks to model how Sleepio affects primary care costs over 3 years is uncertain
4.13 The EAC accepted that resource use savings are likely to continue beyond the 65‑week follow-up reported in Sampson et al. (2021) but was not confident that the data can be extrapolated to 3 years. The EAC reported that the study used to justify the extrapolation of the data to 3 years (Blom et al. 2016) was on another intervention and may not be generalisable to Sleepio. The committee agreed that it was not certain about the suitability of using data reported at 65 weeks to project resource use savings up to 3 years. It concluded that more evidence was needed to support the extrapolation.
Potential for cost savings
Sleepio is cost incurring at 3 years compared with treatment as usual using the population-based cost model
4.14 Using the population-based cost model and reducing the uptake rate from 1% to 0.58%, increased the cost of Sleepio from £90 to £155.17 per user. The EAC base case found Sleepio was cost incurring compared with treatment as usual after 1 year and 3 years. The committee understood there were uncertainties in the modelling associated with the uptake rate and the extrapolation, but it concluded that Sleepio is unlikely to be cost saving if the population-based cost model isused.
The Scotland cost model is more likely to lead to cost savings with Sleepio
4.15 The company proposed an alternative cost model for Sleepio based on the number of people who register for Sleepio treatment (the Scotland cost model, see section 3.13). The committee discussed the EAC's cost comparison analysis based on this cost model and the population-based model described in the submission. It agreed that the Scotland cost model is more likely to lead to cost savings. However, it noted that the results using either costing model show that the technology is cost incurring after 1 year. The committee considered that, ideally for adoption, the technology should be cost saving based on the 1 year resource use data without extrapolation. The committee concluded that while the Scotland cost model is more likely to lead to cost savings, the choice of costing models gives commissioners flexibility to adopt the strategy that most closely meets their requirements.
Main cost drivers
Uptake is the main cost driver for the economic analysis
4.16 The uptake of Sleepio is estimated in the Thames Valley study (Sampson et al. 2021) as between 0.54% and 0.94%. The EAC explained that the economic model with population-based costing shows Sleepio to be cost incurring if the uptake is lower than 0.666%. The company had explained that the variation in uptake can be partly explained by the effectiveness of the implementation model. The company also suggested that, with the population-based cost model, it can agree a minimum uptake rate and apply a rebate if it is not met. The committee concluded that the uptake of Sleepio is a key driver of the economic modelling and that it needs to be more than 0.666% for the technology to be cost saving with the population-based cost model.
Further research
Real-world economic data collection is needed for at least 3 years to capture the cost savings associated with Sleepio
4.17 The committee agreed that the case for adopting Sleepio is plausible if the resource use savings can be evidenced over 3 years, rather than relying on extrapolated data. It therefore agreed that with the current costing models, more economic data collection is needed to validate the resource use savings extrapolated in the statistical analysis. This could be done by using data from regions in England where Sleepio is already being used, to generate resource use savings at 3 years. The company could attempt to link patient outcome data with NHS resource use data to allow costs to be stratified based on remission status.
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