The endorsement comes after clinical evidence showed that the Sleepio app has been comparatively more effective at reducing insomnia than sleeping pills and sleep hygiene.
The evidence presented to NICE’s medical technologies advisory committee is based on 12 randomised controlled trials.
The Sleepio app leverages an artificial intelligence (AI) algorithm to offer customised digital cognitive behavioural therapy for insomnia (CBT-I).
It runs a digital six-week self-help programme that includes a sleep test, weekly interactive CBT-I sessions and a diary recording the user’s sleeping patterns.
The programme focuses on identifying the patient’s thoughts, feelings and behaviours that trigger insomnia symptoms. Meanwhile, the cognitive therapy seeks to improve the way a user thinks about sleep and promote a healthy sleep routine.
According to NICE, the Sleepio app may benefit up to 800,000 people in England.
Additionally, an economic analysis determined that the annual healthcare costs of using the app were lower. This was primarily due to fewer GP appointments and a reduction in the number of prescriptions for sleeping pills.
NICE digital and Medtech acting director Jeanette Kusel said: “Until now people with insomnia have been offered sleeping pills and taught about sleep hygiene, so our committee’s recommendation of Sleepio provides GPs and their patients with a new treatment option.
“Our rigorous, transparent and evidence-based analysis has found that Sleepio is cost saving for the NHS compared with usual treatments in primary care. It will also reduce people with insomnia’s reliance on dependence forming drugs, such as zolpidem and zopiclone.
“This is a good example of where a digital health technology can help the NHS.”
The independent NICE committee has advised a pre-medical assessment for pregnant women and people with comorbidities before using Sleepio.
It also recommended additional research or data collection to assess the effectiveness of the app versus face-to-face CBT-I.
Recently, NICE recommended a new technology to help detect breast cancer spread in patients.