Hybrid Medical Staff Quality & Data Analyst

Ampcus, Inc; Oakland (CA); Hybride; USD 90 000 - 120 000; Plein temps

Résumé du poste

Ampcus, Inc. is seeking a Medical Staff Quality Specialist in Oakland, CA. The role focuses on data analysis, reporting, and database management to support medical staff evaluation, credentialing, and peer review processes.

It emphasizes professional practice evaluation, confidentiality, and regulatory compliance. The position involves collaboration with medical staff leadership, data quality improvement, and participation in quality committees.

Qualifications

• Bachelor's degree required.
• Minimum 3 years of healthcare experience.
• Experience managing FPPE, OPPE, and professionalism cases.
• Strong data analysis and statistical reporting skills.
• Experience with database management and analyzing complex datasets.
• Proficiency with Word, Excel, PowerPoint, and Outlook.
• Excellent written and verbal communication; ability to present findings.

Responsabilités

• Collaborate with leadership to analyze OPPE and peer review data.
• Complete data collection, analysis, and reporting projects.
• Generate reports from peer review databases.
• Maintain data integrity and confidentiality; ensure timely, accurate data.
• Summarize OPPE and peer review findings for leadership.
• Improve data quality and audit data collection processes.
• Support quality initiatives and committees; monitor performance measures.
• Stay informed on regulatory and accreditation standards.

Connaissances

Data analysis

FPPE/OPPE

MS Office

Communication

Independent work

Organization

Formation

Bachelor's degree

Outils

Database management

Description du poste

Ampcus, Inc. is seeking a Medical Staff Quality Specialist in Oakland, CA. The role focuses on data analysis, reporting, and database management to support medical staff evaluation, credentialing, and peer review processes.

It emphasizes professional practice evaluation, confidentiality, and regulatory compliance. The position involves collaboration with medical staff leadership, data quality improvement, and participation in quality committees.