NHS mental health backlog spotlights passive digital biomarkers

New NHS England figures show 2.26 million people had open referrals to NHS-funded secondary mental health services at the end of April 2026, intensifying questions about how providers can monitor patients between appointments. Behavidence says passive digital biomarkers, built from smartphone behavior with user consent, could help clinicians spot deterioration earlier and direct care more effectively.

Why it matters: - NHS England’s latest monthly statistics show mental health services are under heavy strain, with 2.26 million open referrals at the end of April 2026. - The backlog includes 1.55 million adults and more than 520,000 children and young people. - Clinicians often have limited objective information about how a person’s mental health changes between appointments. - Passive digital biomarkers could give care teams another signal to prioritize limited resources, support people waiting for care and intervene sooner when symptoms worsen.

What happened: - NHS England Mental Health Services Monthly Statistics reported 2.26 million open referrals to NHS-funded secondary mental health services at the end of April 2026. - An open referral can mean a person is waiting for assessment, receiving treatment or still under clinical review. - Behavidence, a neuroscience company, highlighted the data as evidence of growing pressure on mental health care and argued for wider use of passive digital biomarkers. - The company says its technology analyzes everyday smartphone behavior, with informed user consent, to identify behavioral patterns associated with mental health.

The details: - Behavidence says passive digital biomarkers monitor trends over time instead of relying only on questionnaires or patient recall. - The approach is designed to give clinicians objective information between appointments without adding burden for patients. - The company says the method could help prioritize clinical resources by identifying patients whose behavioral patterns suggest worsening symptoms. - Behavidence also says the technology could support waiting patients with self-help resources, psychoeducation or digital interventions when those steps appear appropriate. - The company says objective longitudinal behavioral data can complement clinical interviews and patient-reported outcomes. - Behavidence says the technology may help detect deterioration earlier so care teams can intervene sooner. - Behavidence says multiple peer-reviewed studies have clinically validated its passive smartphone behavioral data for identifying patterns associated with depression and anxiety. - The company says its research has appeared in leading digital health journals and is expanding into additional mental health conditions and use cases. - Behavidence says it is working with the U.S. Department of Veterans Affairs on initiatives to improve mental healthcare for veterans through passive digital monitoring and early identification of behavioral changes. - The company was founded by neuroscientist Roy Cohen, who developed the idea while completing a master’s degree in Applied Neuroscience at King’s College London. - Cohen said passive digital biomarkers are not meant to replace clinicians or clinical judgment and should instead add another layer of objective information. - Behavidence’s technology is being evaluated and deployed across healthcare providers, researchers and government organizations, according to the company. - The company says its platform is used to identify behavioral patterns linked to depression, anxiety, stress and ADHD. - More information is available on Behavidence’s LinkedIn page.

Between the lines: - The pitch reflects a broader shift in mental healthcare toward continuous monitoring rather than episodic check-ins. - The timing matters because staff shortages and rising demand make it harder for clinicians to track deterioration using appointments alone. - The strongest use case appears to be triage and early warning, not replacing in-person assessment. - Privacy and consent are central to whether these tools can gain trust in real-world care settings.

What's next: - Behavidence says it will keep expanding research across more mental health conditions and clinical applications. - Wider adoption will likely depend on further validation, integration into care pathways and proof that the tools improve outcomes without adding complexity. - Health systems will keep testing AI-enabled monitoring models as they look for ways to manage demand with limited clinical capacity.