Maryland Health Performance & Forecasting Dashboard

Overview

The Maryland Health Performance & Forecasting Dashboard is a demo platform designed to showcase how a state can centralize, monitor, and forecast all public health and policy indicators within one intelligent ecosystem.
Built with synthetic and anonymized data, the system demonstrates how government agencies can manage statewide performance metrics using advanced analytics, AI forecasting, and simulation.

Integrating key data sources such as the Maryland Department of Health (MDH), the State Health Improvement Process (SHIP), and county-level submissions, the platform aligns progress with CDC and Healthy People 2030 goals.
It provides policymakers with a 360° real-time view across critical domains: Access to Care, Chronic Disease, Behavioral Health, Women’s Health, and Violence Prevention — empowering state leaders to make evidence-based, data-driven decisions.

Core Capabilities

The demo illustrates how a state health department can consolidate, forecast, and analyze hundreds of indicators in a single environment. It integrates over 60+ KPIs from counties and health agencies, providing unified dashboards for tracking, comparison, and accountability across all public health programs.

Machine learning models predict 12-month outcomes for key indicators — such as asthma ER visits, chronic disease prevalence, and access-to-care rates — allowing agencies to anticipate future trends and evaluate program impact.

Through its “What-If” simulation engine, users can test the effects of new policies or funding allocations, like expanding telehealth or preventive care initiatives, and immediately see their projected impact on statewide performance and forecasted improvement rates.

Built-in demographic filters for county, ethnicity, age group, and gender=reveal disparities in outcomes, while cross-domain integration links all health areas for a complete population-level analysis.

Impact & Value

• Provides a complete model for state performance management, enabling transparent tracking of all indicators.
• Demonstrates a 98.6% current statewide progress and 4.3% forecasted improvement, based on modeled data.
• Reduces reporting complexity by transforming static reports into real-time, interactive dashboards.
• Equips policymakers with tools to simulate outcomes, track program success, and evaluate equity across counties.
• Serves as a proof of concept for scalable, AI-driven government intelligence systems adaptable to any U.S. state.

Technology Stack

• Power BI Embedded for advanced visualization and interactive analytics.
• Python Machine Learning Models for predictive forecasting and scenario simulation.
• ETL pipelines replicating multi-agency data integration processes.
• Microsoft Azure & Dataverse ensuring scalability, security, and data governance.
• Smart Narratives & Natural Language Insights automatically summarize key findings and trends.

Our Difference

This demo exemplifies how Tsubaki Systems transforms government analytics—from fragmented reporting into predictive governance intelligence. The architecture mirrors real-world state analytics environments, demonstrating how any government can achieve data transparency, predictive forecasting, and unified indicator management under one intelligent platform.