Project Details
Description
Meeting the mental health needs of children and young people (CYP) is an urgent priority givenrecentsteepincreases inthe prevalenceof mental healthdifficultiesand a correspondingescalation indemand for care. In 2021,a national longitudinal surveyofthe mental health of CYP in England foundthatone in six children aged 5 to 19years hada probable mental health disorder,increasing from between oneandnine and one in ten in 2017(NHS Digital, 2021).The same study found that 39.2% of 6-to 16-year-oldsand 52.5% of 17-to 23-year-olds had experienced deterioration in their mental health since 2017.
Increaseddemandforsupport creates a major challenge for the already stretched children and young people’s mental health system.Limited resources and increasingdemandhaveresulted in long waiting lists for treatment across the UK, and a recent survey of GPs(Pulse, 2022)suggests thatthresholds for accessing child and adolescentmental health services have increasedin most areas of the countryto prioritise those with only the most severe needs.This creates a majorbarrier to help-seeking and to accessing care, oftenresultinginfurtherdeteriorationin mental health and escalation in risk.Correspondingly, severalstudies have documentedincreasesin the number of CYP presenting to emergency departments in mental health crisissince the start of the COVID-19 pandemic(Brasso et al., 2022).
In Norfolk and Waveney, there are currently over 3000 CYP on waiting lists for mental healthservices. Without innovative whole-system solutions, we anticipate that waiting times for treatment will continue to rise as demandcontinuesto outweigh capacity. At present, considerable clinical capacity in the CYP mental health system is dedicated to managing and triaging referrals. When a referral is received by a service, a clinician must manuallyassess andtriageeach referral, a process that can take up to three hours. Oftenreferrals either do notcontain sufficient information fora safe triaging decision to be made ordo not meet the criteriafor thatparticular service and will subsequently bereturned orrejected.Currently 60% of CY mental health referrals from primary care in Norfolk and Waveney are rejected.Thiswastes many hours of professionals’time(boththe mental health clinician’s and the referring professional’s)that could be spent providing care and support. Moreover,resultant delays cause considerable distress for CYP and their families who can face a waitof18 monthsormore before receiving thesupportthey need.
We believe that digital innovation has the potential to transform the referral and triage process across the CYP mental health system.This project wouldcontribute to this transformation through exploring the role Artificial Intelligence(AI) could playinsupportingclinicianstotriage and assess referralsmore efficiently. This wouldfree up additional clinical capacity, therebyensuring that more CYP are able to access themental health supportthey need, when they need it.
Increaseddemandforsupport creates a major challenge for the already stretched children and young people’s mental health system.Limited resources and increasingdemandhaveresulted in long waiting lists for treatment across the UK, and a recent survey of GPs(Pulse, 2022)suggests thatthresholds for accessing child and adolescentmental health services have increasedin most areas of the countryto prioritise those with only the most severe needs.This creates a majorbarrier to help-seeking and to accessing care, oftenresultinginfurtherdeteriorationin mental health and escalation in risk.Correspondingly, severalstudies have documentedincreasesin the number of CYP presenting to emergency departments in mental health crisissince the start of the COVID-19 pandemic(Brasso et al., 2022).
In Norfolk and Waveney, there are currently over 3000 CYP on waiting lists for mental healthservices. Without innovative whole-system solutions, we anticipate that waiting times for treatment will continue to rise as demandcontinuesto outweigh capacity. At present, considerable clinical capacity in the CYP mental health system is dedicated to managing and triaging referrals. When a referral is received by a service, a clinician must manuallyassess andtriageeach referral, a process that can take up to three hours. Oftenreferrals either do notcontain sufficient information fora safe triaging decision to be made ordo not meet the criteriafor thatparticular service and will subsequently bereturned orrejected.Currently 60% of CY mental health referrals from primary care in Norfolk and Waveney are rejected.Thiswastes many hours of professionals’time(boththe mental health clinician’s and the referring professional’s)that could be spent providing care and support. Moreover,resultant delays cause considerable distress for CYP and their families who can face a waitof18 monthsormore before receiving thesupportthey need.
We believe that digital innovation has the potential to transform the referral and triage process across the CYP mental health system.This project wouldcontribute to this transformation through exploring the role Artificial Intelligence(AI) could playinsupportingclinicianstotriage and assess referralsmore efficiently. This wouldfree up additional clinical capacity, therebyensuring that more CYP are able to access themental health supportthey need, when they need it.
Layman's description
The vision for children and young people’s mental health in Norfolk and Waveney includes the principles of ‘no wrong door’ into services, the elimination ofgapsin service provision,and system ownership of the person in need. To achieve thisvision,it wasclear that a core element of the futureservicemodel mustbe easy access via a single phone numberandwebsite,with asingleinitial screening/assessmentprocessfor all CYP with mental health needs, i.e. an integratedfront door (IFD).This IFDservice will bein aset-up phasefrom October 2022 and is due toopen its doors to referrals in February 2023.
This project would explore the potential forArtificial Intelligence (AI) algorithms to be used within the IFD to help clinicians screen referrals andrecommend the most appropriate pathway of support.Research capacity building funding from UEAHSCPwould enable us tobring togetherthe team’s existing networks ofCYP mental health clinicians, operational managers and commissions, academics, innovation specialistsand industry professionals. These stakeholders would work togethertodevelop the clinical scoring system and serviceinclusion/exclusion criteriaframeworkthat would be neededtobuild a prototype AI algorithm.
We would then test theeffectivenessof the AI module in a sample of referralsin preparation for future research.We would alsoexplore the feasibility ofcreatinga live dashboard toinformthe IFD team on any changes to provider circumstances that may affecttheir ability toprocessreferrals in a timely manner. This would require all providers to flowregular metrics to allow us tokeep this dashboard updated.
This project would explore the potential forArtificial Intelligence (AI) algorithms to be used within the IFD to help clinicians screen referrals andrecommend the most appropriate pathway of support.Research capacity building funding from UEAHSCPwould enable us tobring togetherthe team’s existing networks ofCYP mental health clinicians, operational managers and commissions, academics, innovation specialistsand industry professionals. These stakeholders would work togethertodevelop the clinical scoring system and serviceinclusion/exclusion criteriaframeworkthat would be neededtobuild a prototype AI algorithm.
We would then test theeffectivenessof the AI module in a sample of referralsin preparation for future research.We would alsoexplore the feasibility ofcreatinga live dashboard toinformthe IFD team on any changes to provider circumstances that may affecttheir ability toprocessreferrals in a timely manner. This would require all providers to flowregular metrics to allow us tokeep this dashboard updated.
Key findings
Keyoutputs from this project will be:
•An eligibility framework clearly articulatingthecurrent inclusion/exclusion criteriaof each servicewithin the CYP mental health system.
•A co-produced e-referral formfor use as part of the new Integrated Front Doorof CYP mental health services across Norfolk and Waveney.
•Prototype AI algorithm foruse infuture research.
•Wireframe of AI bot programme for future development.
•New UEAHSCP research groupbringing together computer scientists with health and social care professionals, operational managers, commissioners andresearchers toconsider how the latest technological innovations could contribute to improved care,anddevelop future research projects to support the development of promising solutions.
•At least one peer-reviewed journal article, as well as the final project report to the Executive Management Groupwith recommendations on next steps, and accessible multi-media summaries for public audiences, including CYP and their families.
•An eligibility framework clearly articulatingthecurrent inclusion/exclusion criteriaof each servicewithin the CYP mental health system.
•A co-produced e-referral formfor use as part of the new Integrated Front Doorof CYP mental health services across Norfolk and Waveney.
•Prototype AI algorithm foruse infuture research.
•Wireframe of AI bot programme for future development.
•New UEAHSCP research groupbringing together computer scientists with health and social care professionals, operational managers, commissioners andresearchers toconsider how the latest technological innovations could contribute to improved care,anddevelop future research projects to support the development of promising solutions.
•At least one peer-reviewed journal article, as well as the final project report to the Executive Management Groupwith recommendations on next steps, and accessible multi-media summaries for public audiences, including CYP and their families.
Acronym | ASSIST(AI System Support In Service Triage) |
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Status | Finished |
Effective start/end date | 1/08/22 → 31/03/23 |