Mental Healthcare Analytics Platform Development
Challenge
Clinicians needed a single platform combining patient management with deep analytics of treatment outcomes across large, heterogeneous datasets. Existing tools required manual analysis of medication histories, crisis events, and therapy paths — making data-driven clinical decisions slow, inconsistent, and difficult to scale across multiple organisations.
Clinicians needed a single platform combining patient management with deep analytics of treatment outcomes across large, heterogeneous datasets. Existing tools required manual analysis of medication histories, crisis events, and therapy paths — making data-driven clinical decisions slow, inconsistent, and difficult to scale across multiple organisations.
Solution
We delivered full-cycle product engineering: a custom EMR tailored to mental healthcare workflows, a proprietary Sankey visualization built in D3 alongside 15+ supporting charts, and an AI engine recommending optimal treatment paths based on statistical comparison of outcomes. Multi-tenant access was implemented via AWS Cognito with role-based routing. The EMR and analytics layer were delivered as two interoperable products, connected by a shared data architecture that supports longitudinal views of medications, test results, and crisis events.
We delivered full-cycle product engineering: a custom EMR tailored to mental healthcare workflows, a proprietary Sankey visualization built in D3 alongside 15+ supporting charts, and an AI engine recommending optimal treatment paths based on statistical comparison of outcomes. Multi-tenant access was implemented via AWS Cognito with role-based routing. The EMR and analytics layer were delivered as two interoperable products, connected by a shared data architecture that supports longitudinal views of medications, test results, and crisis events.
Results
Two interoperable products — EMR and analytics platform — delivered and in active clinical use. AI-driven treatment recommendations replaced manual outcome analysis, giving clinicians statistical comparisons across patient cohorts. Custom crisis and medication timelines eliminated blind spots in long-term treatment tracking. Multi-tenant architecture enabled independent operation across multiple healthcare organisations on a single, maintainable codebase.
Two interoperable products — EMR and analytics platform — delivered and in active clinical use. AI-driven treatment recommendations replaced manual outcome analysis, giving clinicians statistical comparisons across patient cohorts. Custom crisis and medication timelines eliminated blind spots in long-term treatment tracking. Multi-tenant architecture enabled independent operation across multiple healthcare organisations on a single, maintainable codebase.