Data Quality, Equity, and Ethics in Outcome Assessment
Test inter-rater reliability, verify construct validity, and check whether measures detect meaningful change. Document protocols, train staff, and pilot tools to avoid false conclusions that misdirect resources and harm trust.
Data Quality, Equity, and Ethics in Outcome Assessment
Respect participants with clear consent, minimal data collection, and strong safeguards. Align with regulations and community expectations, and explain how outcome data will be used to improve care rather than surveil.