Quality & Patient Safety Nurse (AI Clinical Evaluation)

Gramian Consulting Group

21h•Remote

About The Position

Gramian Consultancy is seeking an experienced Quality & Patient Safety Nurse for a 12-week contractor assignment supporting an AI training and evaluation project. The project focuses on clinical quality, patient safety, documentation review, adverse-event analysis, and healthcare process improvement. The role is remote in the United States and may be part-time or full-time, with a commitment of 20–40 hours per week. The nurse will create and review complex quality and safety cases, longitudinal chart scenarios, gold-standard answers, and evaluation rubrics. They will assess AI-generated outputs for appropriate clinical judgment, patient-safety principles, regulatory expectations, documentation quality, and quality-improvement reasoning. Selection is based on an online questionnaire and review of the applicant’s resume, education, and certification. Active U.S. RN licensure and substantial recent quality or patient-safety experience are required.

Requirements

Active Registered Nurse (RN) license in the United States.
Approximately 8+ years of professional nursing experience.
Significant experience in quality improvement, patient safety, clinical risk, or healthcare quality operations.
Current or recent professional practice within the last 3 years.
Strong experience reviewing complex clinical documentation and identifying safety, quality, or process concerns.
Strong understanding of incident review, root-cause analysis, corrective actions, and quality-improvement methodologies.
Ability to interpret fragmented clinical information and produce clear, defensible conclusions.
Strong written English and ability to communicate quality and safety findings precisely.

Responsibilities

Develop high-difficulty clinical quality and patient-safety cases and benchmark tasks.
Review longitudinal medical records, incident reports, clinical documentation, and care-process data.
Identify patient-safety risks, documentation gaps, process failures, preventable harm, and quality concerns.
Evaluate AI-generated outputs for clinical accuracy, safety, regulatory alignment, and quality-improvement relevance.
Create gold-standard answers and clinically defensible reference solutions.
Review adverse events, near misses, escalation failures, handoff issues, and system-level safety concerns.
Assess quality-improvement recommendations, corrective actions, and process changes.
Apply structured rubrics to evaluate clinical reasoning, terminology, documentation quality, and patient-safety implications.
Participate in peer review, calibration, and resolution of complex quality or safety edge cases.
Support cross-functional review involving nursing, physicians, pharmacy, case management, infection prevention, and hospital operations.