PACT-CARE™: A Human-in-the-Loop Framework for Responsible and Useful AI in Healthcare

PACT-CARE™ is a Human-in-the-Loop (HITL) framework to make AI in healthcare responsible, useful, and trusted. While many models excel in accuracy, they often fail in real-world care due to poor integration, lack of trust, or limited benefit. This 8-step loop—Patient & Problem, Action Policy, Capacity & Context, Thresholds & Trade-offs, Compliance, Adoption, Reliability & Recalibration, Equity & Economics—ensures AI is clinically relevant, safe, and equitable. It synthesizes global standards like FDA’s GMLP, ONC transparency rules, WHO ethics, and the EU AI Act. A toolkit (scorecard, canvas, transparency datasheet) operationalizes the framework. Case studies—AI triage for pneumothorax, preventive statin use, and no-show prediction—show improved outcomes: faster treatment, higher therapy adoption, reduced disparities, and positive ROI. PACT-CARE™ shifts the focus from model accuracy to real-world usefulness by embedding oversight, capacity checks, and continuous recalibration. Ultimately, it bridges the gap between promising algorithms and sustainable clinical adoption, enabling healthcare AI that earns trust, delivers measurable benefits, and aligns with ethical and regulatory norms