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PHI researcher lays out four practical steps for prioritizing direct care workforce data
Summary
Stephen McCall of PHI presented a four‑step approach—identify partners, define the workforce, specify data needs, and explore data sources—illustrating how to turn policy questions (e.g., ARPA wage effects) into measurable analyses.
Stephen McCall, director of research at PHI, told participants that states should follow a sequential approach when designing workforce data work: identify and engage partners, define which workers to include, specify data needs (measures and time frames), and then explore data sources that meet those needs.
"Engaging partners early and strategically will help you build the essential buy in," McCall said, urging participants to include state program leadership, labor market experts, advocacy organizations and MCOs. He illustrated how to turn a general interest—"How did wage increases funded by ARPA affect home care workforce stability?"—into a concrete before‑and‑after analytic question (for example, quarterly turnover and retention from 2019 to 2025).
McCall described three data buckets—labor market data (BLS/OES), program/administrative data (FMS, EVV, worker registries, UI wage records), and primary data (surveys/interviews)—and noted tradeoffs in granularity, inclusivity and resource intensity for each source. He recommended being explicit about definitions and measures up front to maximize analytic usefulness.
