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Our real-time visualisation capabilities brings patient data to life; providing clinicians with the tools necessary to implement Feedback-Informed Therapy processes into treatment, in turn, increasing patient engagement and improving treatment outcomes.
By combining the latest research with machine-learning models, Recovery Metrics automatically flags slow-or-no progress as well as high-risk responses; allowing practitioners to proactively intervene and prevent premature treatment dropouts as well as client deterioration and relapse.
By taking information from existing data sets to determine patterns and predict future outcomes and trends, providers can better determine which patients are best suited to which treatment types, which are at risk of drop out, which are likely to require a higher-level of care.
We acknowledge the traditional owners and custodians of the land on which we work as the first people of this country.
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