Clinical Analytics & Performance Leader

University Health; San Antonio (TX); On-site; USD 90,000 - 140,000; Full time

Job summary

University Health seeks a Sr. Data Analyst leader to provide analysis of clinical, quality, utilization, throughput and financial data; manages Sr. Data Analysts; develops data validation procedures; creates reports to improve patient services and health outcomes.

Collaborates with departments, develops visualization methods, supports decision-making, trains staff on data systems, and leads special projects and process improvement efforts.

Qualifications

• Bachelor’s degree required with extensive experience in data management and analysis.
• Master’s degree in health-related field preferred.
• Five or more years of relevant experience in large health care systems.
• Knowledge of Microsoft Office Suite, decision support systems, and data visualization preferred.
• Excellent writing and oral skills, organization and data presentation skills.

Responsibilities

• Analyze clinical, quality, utilization, throughput, and financial data.
• Develop procedures for monitoring, validating, and reconciling data for accuracy.
• Create reports and presentations to improve patient services and health outcomes.
• Collaborate with departments and project managers on analytical and data visualization methods.
• Lead training for health care providers and staff on data systems; present results.

Skills

Data analysis

Data management

Health care analytics

Training and presentations

Education

Bachelor’s degree in health-related field

Master’s degree in health-related field (preferred)

Tools

Microsoft Office Suite

Decision support systems

Data visualization tools

Job description

University Health seeks a Sr. Data Analyst leader to provide analysis of clinical, quality, utilization, throughput and financial data; manages Sr. Data Analysts; develops data validation procedures; creates reports to improve patient services and health outcomes.

Collaborates with departments, develops visualization methods, supports decision-making, trains staff on data systems, and leads special projects and process improvement efforts.