Klantcase

AI helps clinicians define concrete treatment goals

How GGz Centraal uses AI to translate abstract care needs into concrete, measurable treatment goals — helping clinicians have better conversations, make progress visible, and free up time for what really matters: the client..

Advisor and client in conversation, with a laptop showing progress charts and floating AI icons representing people, validation and results
Customer GGz Centraal
Sector Mental healthcare
Expertise AI & Applications
Solution AI Co-creation Sprint — treatment goals

The challenge

Mental healthcare organisations are under growing pressure to improve treatment quality, while clinicians simultaneously face heavy administrative burdens and limited time per client.

A key bottleneck is formulating and recording clear, measurable treatment goals. Care needs are often expressed in abstract terms, while treatment plans need to be concrete and testable — the heart of the challenge: turning an abstract care need into a concrete treatment outlook.

Woman at a desk looking at a progress line on paper with a missing link, symbolising the translation from an abstract care need into a concrete treatment goal
Our approach

AI Co-creation Sprint

  1. Care need

    One concrete care challenge as the starting point, with direct involvement from care professionals.

  2. Co-creation

    Close collaboration between care, data and IT to translate the care need into a concrete AI use case.

  3. AI prototype

    Full Orbit builds a working prototype around the chosen use case.

  4. Validation with professionals

    Care professionals assess and validate whether the solution genuinely adds value.

AI that helps make treatment goals concrete

The AI solution supports clients and clinicians in jointly formulating concrete treatment goals. Based on a general care need, the AI generates suggestions for personalised goals, including SMART criteria and next steps.

The clinician reviews and refines these suggestions — the AI does not make independent treatment decisions. Only after that human review is the SMART treatment goal recorded, after which progress can be tracked digitally.

Laptop showing the 'Health goals dashboard': an overview of personalised, SMART treatment goals
The core

Clear, measurable treatment goals with AI

The AI Co-creation Sprint combines care expertise, data and AI technology into a working prototype — with the clinician always in control.

Download the case study
Co-creation between care, data and IT Close collaboration with care professionals, from care need to AI use case.
AI-generated treatment goals Suggestions for SMART treatment goals based on the care need.
Review by the clinician The clinician checks and validates every proposed goal — the AI does not decide independently.

Result: a working prototype

The AI Co-creation Sprint led to a working prototype in a short space of time and shows that this approach can genuinely add value within mental healthcare.

Working prototype

A working AI solution for a concrete care need, delivered in a single short sprint.

More structure

Concrete, measurable goals provide more direction during the treatment process.

Less administrative burden

AI supports the formulation and recording of treatment goals, freeing up more time for the client.

The solution is currently in the pilot phase. The next step is measuring time savings and the impact on treatment quality.

Met AI kunnen we behandelaren ondersteunen en hen meer tijd geven voor écht contact met cliënten.

Matthijs Jantzen Clinical Informatics Specialist, GGz Centraal

Want to discover where AI can add real value?

With an AI Co-creation Sprint, we take a concrete use case to a working prototype in a short space of time.