Patient Experience of Nursing Care Assessment

Identifies which character strengths employees draw on most, how often they get to use them day to day, and what gets in the way of strengths-based work. Built for HR, L&D, and coaching teams running strengths-based development programs — the AI follow-up interview digs into a specific recent moment someone used their top strength, turning self-report scores into concrete, usable examples.

Captures how patients experienced a recent visit — wait times, communication, staff respect, and overall likelihood to recommend — with a best-worst prioritization of improvement areas and an AI follow-up that digs into the specific moment behind their recommendation score. Built for clinics, hospitals, and practice managers tracking care quality.

Captures how residents and their families experience daily care, staff responsiveness, meals, activities, and communication in a nursing home or assisted living community. An AI follow-up interview digs into the story behind the lowest-rated experience so administrators know exactly what to fix first, not just where the score dropped.

Measures how patients experience physical therapy care — clarity of communication, pain management during exercises, and real functional progress — built for clinics, rehab practices, and outpatient PT groups. The AI follow-up interview digs past satisfaction scores to reconstruct what actually happened in sessions and why recovery felt fast, slow, or stalled.

Measures how a patient experienced a specific provider visit — getting the appointment, provider communication, staff courtesy, and an overall rating — modeled on the CAHPS Clinician & Group Visit 2.0 survey used across medical practices and health systems. An AI follow-up interview digs into the exact moment or interaction that drove the patient's overall rating, turning a single number into an actionable story.

Captures how clearly patients understood their discharge instructions, medications, and follow-up care after being released from a hospital, ER, or outpatient procedure. An AI follow-up interview digs into the specific point where instructions were unclear, so care teams can fix the discharge process before it causes a readmission or complication.