Healthcare Performance Data Analyst - Full Time

In this role you will:

• Performance Measures and Regulatory Analytics
  
  
  
  • Serve as IRMC’s analytics subject-matter expert for CMS Hospital IQR and OQR programs, CMS Overall Star Ratings, HCAHPS, AHRQ PSI, NHSN, and Leapfrog Hospital Safety Grade. Monitor specifications, tracking calendars, and method changes; translate technical updates into clear implications for leaders and front-line teams.
  
  
  • Build and maintain robust measure definitions, data dictionaries, and lineage documentation to ensure transparency and reproducibility of all performance metrics.
  
  
  • Produce recurring executive and service-line dashboards (monthly/quarterly) highlighting trends, benchmarks, control limits, variation, and prioritized opportunities, surface leading indicators and predicted performance risk against external public reporting cycles.
  
  
  • Support data for survey readiness and public reporting; validate measure logic and results; coordinate with abstractors, infection prevention, patient experience, and finance/decision support teams to reconcile discrepancies.
  
  


• Data Management and Integration
  
  
  
  • Design and implement end‑to‑end data collection and analysis plans for quality, safety, regulatory, and patient experience initiatives; establish sampling strategies, inclusion/exclusion criteria, and refresh schedules.
  
  
  • Integrate data from internal systems (electronic health record (HER), data warehouse, incident/event reporting, patient experience platforms, staffing/acuity, pharmacy/antimicrobial stewardship, throughput) and external sources (CMS Compare datasets, Leapfrog submissions/feedback, AHRQ PSI, NHSN, state reporting, payor portals).
  
  
  • Develop sustainable, automated data pipelines using SQL/ETL/Power Query (or equivalent) with version control, data quality checks, and audit trails.
  
  


• Analytics, Statistics, and Visualization
  
  
  
  • Apply descriptive and inferential statistics (e.g., rates, proportions, CIs, trend and SPC charts, risk adjustment concepts, stratification, small‑n techniques) to transform data into clear information and insight.
  
  
  • Build interactive dashboards and self‑service reports (e.g., Microsoft Power BI or Tableau) with drill‑downs from system level → service line → unit → provider, using color‑blind–safe palettes and clear annotation.
  
  
  • Partner with PI teams to quantify opportunity, model impact (e.g., baseline vs. target performance, avoidable events, financial implications), and support PDSA cycles with rapid feedback loops.
  
  


• Data Governance, Privacy, and Quality
  
  
  
  • Apply procedures for data and system management, including HIPAA compliance, minimum necessary, de‑identification where appropriate, access controls, user provisioning, and routine data quality monitoring (completeness, validity, timeliness, consistency).
  
  
  • Lead or support data validation sprints and crosswalks between source systems, extracts, and dashboards; document and remediate data issues.
  
  


• Stakeholder Engagement and Training
  
  
  
  • Translate complex methodology into practical “what it means/what to do” for leaders, clinicians, and front-line staff; create one‑page explainer visuals, metric fact sheets, and tip sheets.
  
  
  • Provide just‑in‑time education on measure specifications, SPC interpretation, and dashboard use; coach teams to use data in daily management and huddles.
  
  
  • Collaborate with Finance/Rev Cycle, Case Management, Infection Prevention, Patient Experience, and Nursing/Physician leadership to ensure alignment between clinical, operational, and financial targets.
  
  


• Continuous Improvement and Special Projects
  
  
  
  • Support/lead analytics for priority PI projects (e.g., HAIs, readmissions, LOS, ED throughput, mortality, harm events, adverse drug events, safety culture).
  
  
  • Evaluate and pilot advanced analytic approaches (e.g., risk stratification, segmentation, simple predictive models) in partnership with IRMC’s data engineering/IT teams.
  
  


• Other Core Competencies
  
  
  
  • Demonstrate understanding of 24/7 hospital operations in an acute care setting, including clinical knowledge.
  
  
  • Organize and prioritize work to meet multiple deadlines and adapt to frequent changes in priority.
  
  
  • Utilize excellent organizational and interpersonal communication skills.
  
  

OTHER DUTIES

Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.

QUALIFICATIONS

Required:

• EDUCATION:
  
  
  
  • Associate degree in Data Analytics, Health Informatics, Biostatistics, Public Health, Computer Science, or related field.
  
  
  • Bachelor’s or Master’s degree (MPH, MS, MHA with analytics focus) or graduate certificate in healthcare analytics desirable
  
  


• EXPERIENCE:
  
  
  
  • 3+ years of progressive analytics experience in a hospital or health system quality/safety environment.
  
  
  • Demonstrated expertise analyzing CMS IQR/OQR measures, CMS Star Ratings, HCAHPS, AHRQ PSI, NHSN, and Leapfrog Hospital Safety Grade (including measure definitions and specifications).
  
  
  • Track record building automated dashboards and producing executive‑ready insights that led to measurable quality/safety/experience improvements.
  
  
  • Experience partnering with abstractors and registries (e.g., core measures, stroke/ACS, sepsis) while personally focusing on analytics vs. chart abstraction.
  
  


• LICENSURE/CERTIFICATION:
  
  
  
  • Lean, Six Sigma, or combination, yellow belt desirable
  
  
  • Certified Professional in Healthcare Quality (CPHQ) desirable
  
  
  • Relevant analytics certifications (e.g. Microsoft Power BI Data Analyst Associate) desirable
  
  


• Skills:
  
  
  
  • Proficient with SQL (querying/joining/aggregations), Power BI (or Tableau), Excel (Power Query/Power Pivot), and statistical/visual methods (including SPC).
  
  
  • Familiarity with EHR data models (e.g., Epic Clarity/Caboodle or Meditech/other), data warehousing concepts, and API/flat‑file data exchange.
  
  
  • Solid understanding of risk adjustment concepts, case‑mix normalization, reliability, small‑numbers handling, and suppression rules in public reporting.