Caption: A 2022 review of mental health-related calls for service (CFS) in a rural Virginia region, reveals a 10% increase in call volume over three years, with the sharpest growth (47.6%) in rural townships. The review highlights the need for comprehensive local data systems mapping, noting that over 30% of mental health crisis calls were not reported in call type search.
As community response programs transition from pilot initiatives to more sustained public investments, reliable data and evidence-based performance metrics are essential. A clear case for return on investment can help your program justify continued funding and long-term expansion.
Just a few months ago, a market leader in artificial intelligence for consumer use announced the release of a new AI chatbot solution for government. Unlike its consumer-facing counterpart, this product was developed with public sector compliance, data security, and regulations in mind. This reflects a growing demand for AI in government services, where agencies must balance innovation with strict standards for privacy, accountability, and security.
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When communities adopt a coordinated data collection plan across Sequential Intercepts, they gain essential insights on community need and service efficiency. Yet, many communities lack the data infrastructure needed to track progress, monitor implementation, and inform ongoing decision-making. Without dedicated data infrastructure, practitioners often find themselves asking a familiar question after the mapping process concludes: “What’s next?”
