Re-envisioning Housing Data: Usability, Integration, and Systems Alignment

Participated in a panel discussion at the 2025 Monarch Housing Associates Conference, “Housing as a Human Right: Driving Progress in Times of Uncertainty,” focusing on how data systems and predictive modeling are being used to address New Jersey’s housing crisis.

Conference Overview

The conference brought together housing advocates, policymakers, service providers, and data experts to discuss strategies for maintaining housing stability during a period of significant federal policy uncertainty and potential funding cuts.

Panel Participants

Tina McGill - Assistant Director, Office of Homelessness Prevention, NJ DCA

• Policy implementation and homelessness prevention strategies
• Coordination across state housing programs
• Community-based organization partnerships

Marlon Duprey - Community Consultant, Hudson County Advisory Board

• Community perspective on housing challenges
• Lived experience insights informing policy
• Grassroots advocacy and engagement

Gavin Rozzi - Director, DHCR Data Center, NJ DCA

• Technical infrastructure for housing data systems
• Building the Homelessness Entry Risk Framework (HERF)
• Data visualization and decision support tools

Dr. Dan Treglia - Rutgers Center for State Health Policy

• Research and evaluation of housing interventions
• Medicaid Section 1115 Demonstration Project evaluation
• Data linkage across multiple government systems

Key Discussion Topics

The Homelessness Entry Risk Framework (HERF)

Presented DHCR’s innovative predictive modeling system that:

• Forecasts homelessness vulnerability at the ZIP code level across New Jersey
• Integrates real-time economic indicators including eviction filings, rent burden, mortgage distress, and employment data
• Accounts for structural factors like racial inequity, historical patterns, and policy responsiveness
• Enables scenario modeling to predict impacts of federal budget cuts or policy changes
• Uses GPT interface for natural language queries and analysis

Federal Policy Shock Analysis

Demonstrated data-driven modeling of potential impacts from proposed federal cuts:

Scenario Analysis:

• 20% cut to Housing Choice Voucher program: 4,316 households affected
• 44% cut scenario: 9,496 total households (7,510 able-bodied adults; remainder elderly and disabled)
• Projected that 74-81% of terminated households would face homelessness within first year

Geographic and Racial Equity Impact:

• 6 out of 10 households cut in worst-case scenario would be households of color
• Created ZIP code-level risk maps showing disproportionate impact on communities of color
• Additive sheltering costs for top 14 communities alone: approximately $18M within 90 days

Systems Integration and Data Linkage

Dr. Treglia presented on the complexity of linking multiple data systems for comprehensive evaluation:

• Homeless Management Information System (HMIS) data
• Medicaid (MMIS) enrollment and claims data
• Managed Care Organization (MCO) program records
• Prison health records for justice-involved populations
• Eviction filing and judgment data from courts

Medicaid Tenancy and Housing Supports

Discussion of New Jersey’s innovative use of Medicaid funding for housing services:

• Pre-tenancy supports for housing searches
• Move-in assistance and household setup
• Tenancy sustaining services to prevent eviction
• Housing modification and remediation
• 40+ housing providers enrolled, 600+ successful claims filed

PowerBI Dashboards and Decision Tools

Demonstrated interactive data tools built for DCA leadership:

• Real-time HCV program monitoring across all public housing authorities
• Risk visualization by ZIP code using HERF modeling
• Scenario comparison tools for policy analysis
• Eviction tracking and prevention metrics
• Built with React, TypeScript, and modern web technologies

Policy Implications

The panel discussion highlighted critical challenges:

The Crisis Mathematics

Losing $440M in federal rent stabilization would cost New Jersey an estimated $1.76-$2.2 billion in downstream crisis response through:

• Emergency shelter system expansion
• Healthcare costs for unhoused populations
• Educational disruption for homeless children
• Criminal justice system interactions
• Lost economic productivity

Strategic Intervention Priorities

Given limited resources, the panel identified highest-impact interventions:

1. CEDD Expansion - Scale Comprehensive Eviction Defense & Diversion with triage at court entry
2. Lease-in-Place Stabilization - Subsidize at-risk tenancies using existing infrastructure
3. School-Linked Family Diversion - Deploy rapid stabilization teams via McKinney-Vento partnerships
4. Landlord Retention Incentives - Prevent landlord exits from affordable housing market
5. Senior Utility Backstop - Layer assistance to prevent elderly displacement

Protection Tiers

Developed risk-based framework for allocating scarce resources:

• Tier 1: Critical - Families with young children, seniors, disabled adults
• Tier 2: Stabilization - Recently employed workers, young adults aging out
• Tier 3: Intensive Support - Chronically homeless populations

Technical Innovation Highlights

The presentation showcased several technical achievements:

• Predictive modeling using machine learning to forecast homelessness risk
• Geographic information systems for spatial analysis of vulnerability
• Real-time data integration from multiple state agencies
• Interactive visualization tools making complex data accessible to policymakers
• Scenario modeling capabilities for policy impact analysis

Impact and Outcomes

The panel’s data-driven approach influenced state policy responses:

• Evidence-based advocacy for maintaining federal funding levels
• Strategic resource allocation to highest-risk communities
• Enhanced CBO capacity through improved data tools and technical assistance
• Improved coordination across housing, health, and social service systems
• Transparent communication of policy trade-offs to stakeholders

Looking Forward

The discussion emphasized the need for continued investment in data infrastructure:

• Strengthening DCA’s capacity to analyze and respond to housing crises
• Providing community-based organizations with better tools and data access
• Centralizing administrative processes to allow CBOs to focus on direct service
• Building predictive capabilities to enable preventive rather than reactive responses

The panel demonstrated how technical expertise, policy knowledge, community insights, and research rigor can combine to address complex social challenges with data-driven solutions that center equity and protect the most vulnerable populations.