Problem
Moving from an analogue to digital system
Mental health services across the UK are under intense pressure. Over 500,000 children are waiting for care, and adult services face rising demand with vacancy rates exceeding 25%. With long waits and limited capacity, services urgently need scalable, digital solutions to improve access, consistency, and efficiency—especially as budgets tighten and expectations rise.
Workforce, productivity, and efficiency
Clinicians spend valuable time collecting basic patient information. Psyomics shifts this burden by enabling service users to share symptom, contextual, and social details at the point of referral. Patient-reported information, including validated measures and free-text responses, are captured upfront streamlining admin, reducing duplication, and allowing clinicians to focus on care.
Reduce repetition for the service user
Service users often feel frustrated by having to repeat their story. The Psyomics Platform captures their voice from the beginning—why they’re seeking help, in their own words. This not only enriches clinical understanding but can help people to prepare for face-to-face appointments. Many complete it at home, in their own time—25% overnight.
solutions
01
Reducing system inefficiencies
Psyomics enables clinicians to collect high-quality information directly from service users, whilst creating consistency across front doors.
Service users found the platform to be fairly or extremely relevant to them
02
Saving time, driving productivity
By automating early information capture and reducing pre-appointment admin, the platform cuts unnecessary steps for clinical teams.
Service users said it covered all or most of the things relevant to them
03
Engaging people through digital
A simple, accessible experience that helps people feel understood and prepared. Benefits including being relevant, easy to complete, and helping to prepare for appointments with a healthcare professional.
Psyomics has been researching and developing in mental health
testimonials
Upkar Jheeta
Midlands Partnership University NHS Foundation Trust
Jonathan Sweeney
Hertfordshire Partnership University NHS Foundation Trust
Hakan Akozek
Hertfordshire Partnership University NHS Foundation Trust
work with us
Step 1
Book a call with us
Step 2
Build your proposal and RoI calculation
Step 3
Implementation, EPR integration and 'go live'
publications
Translational PsychiatryA machine learning algorithm to differentiate bipolar disorder from major depressive disorder using an online mental health questionnaire and blood biomarker data
2021-01-12
Jakub Tomasik, Sung Yeon Sarah Han, Giles Barton-Owen, Dan-Mircea Mirea, Nayra A. Martin-Key, Nitin Rustogi, Santiago G. Lago, Tony Olmert, Jason D. Cooper, Sureyya Ozcan, Pawel Eljasz, Grégoire Thomas, Robin Tuytten, Tim Metcalfe, Thea S. Schei, Lynn P. Farrag, Lauren V. Friend, Emily Bell, Dan Cowell & Sabine Bahn
JMIR publicationsToward an Extended Definition of Major Depressive Disorder Symptomatology: Digital Assessment and Cross-validation Study
2021-02-15
Nayra A Martin-Key; Dan-Mircea Mirea; Tony Olmert; Jason Cooper; Sung Yeon Sarah Han; Giles Barton-Owen; Lynn Farrag5 ; Emily Bell5 ; Pawel Eljasz1 ; Daniel Cowell5, 6 ; Jakub Tomasik1 ; Sabine Bahn1, 5
JAMA PsychiatryMetabolomic Biomarker Signatures for Bipolar and Unipolar Depression
2023-10-25
Jakub Tomasik,Scott J. Harrison,Nitin Rustogi
Its time for mental health service transformation
Book a discovery call today to see if we can help with your key priorities.
