Job Description
Job Summary The Chief Quality Data Officer serves as a strategic analytics leader for Baptist Memorial Health Care Corporation,
focused on improving patient care quality through advanced analytics while optimizing revenue through quality-based
payment programs. This role identifies quality improvement opportunities by analyzing both clinical care delivery and
administrative data to ensure BMHCC receives appropriate recognition for the high-quality care provided to patients.
This position combines deep analytical expertise with healthcare domain knowledge to predict performance in quality
rating methodologies, identify improvement opportunities, and translate complex data into actionable insights for
leadership and clinical teams. The ideal candidate is a data storyteller who can extract meaningful patterns from
complex healthcare data sets, develop predictive models for quality outcomes, and effectively communicate findings
to drive organizational change. This role requires someone who not only understands the data but can craft compelling
narratives that make complex analytics accessible and actionable for diverse stakeholders across the organization.
This position will work collaboratively across multiple departments including quality, coding, CDI, finance, and IT to
integrate data sources, create analytics frameworks, and implement data-driven strategies that maximize BMHCC's
performance in public quality rating programs and value-based payment models. The Quality Data Scientist will be
adept at using large data sets to find opportunities for clinical quality optimization, testing different courses of action,
and developing algorithms to monitor performance, serving as a bridge between technical and clinical domains to help
BMHCC capture earned revenue by getting full credit for the quality care already being delivered.
Job Responsibilities - Quality Performance Improvement Leadership
- Analytics and Modeling
- Data Visualization and Communication
- Collaboration and Team Development
- Process Improvement
Requirements Technical Skills: Proficiency with data analysis platforms, ability to work with large complex datasets, experience with programming languages, and SQL query development. Experience with healthcare information systems. Demonstrated ability to use programming languages (SAS, R, Python) to manipulate datasets, conduct what-if scenarios, and implement predictive models based on quality program methodologies. Proficiency with one data analysis platform Experience with SAS, R, or Python; Advanced SQL skills; Experience with Epic systems
Healthcare Knowledge: Understanding of healthcare quality measures, terminology (including DRGs, ICD-10 codes, HCCs), clinical documentation requirements, and public reporting methodologies. Basic understanding Comprehensive knowledge
Data Storytelling: Ability to communicate complex data insights to diverse audiences in a clear, compelling, and actionable manner. Experience developing executive-level presentations and strategic recommendations based on data analysis. Demonstrated ability Advanced skills with proven track record
Critical Thinking: Ability to identify patterns and insights in complex data, approach problems from multiple perspectives, and develop innovative analytical solutions. Demonstrated ability Advanced skills with proven examples
Personal Characteristics: Curiosity, adaptability to new information and methodologies, tenacity, and resilience when working through complex analytical challenges. Demonstrated traits Proven track record of applying these traits to drive organizational change
Leadership Skills: Ability to mentor others, lead cross-functional initiatives, and potentially build and supervise a team of analysts as the program grows. Basic leadership skills Proven experience building and developing teams
Experience Healthcare Analytics Experience: Professional experience analyzing healthcare data to identify quality improvement opportunities and revenue optimization strategies. Experience working with quality metrics, public reporting programs (CMS Stars, Leapfrog, Vizient, US News), and value-based payment programs (HVBP, HRRP, HACRP). 7-years required 8-years desired
Data Analysis Experience: Experience with descriptive statistical methods and data exploration techniques. Expertise in analyzing complex data sets, identifying patterns and trends, and extracting actionable insights. Demonstrated ability to integrate multiple data sources and develop comprehensive analytics solutions that combine clinical and financial data elements. 7-years required 8-years desired
Collaborative Experience: Experience working collaboratively with multidisciplinary teams including quality, CDI, coding, finance, and IT. Experience presenting to and working with healthcare leadership teams on strategic initiatives. 4 years required 5 years desired
Data Visualization Experience: Experience creating dashboards and visualization tools that clearly communicate quality performance metrics to various stakeholders. 3 years required 4 years desired
Data Modeling Experience: Experience developing and implementing predictive analytics models, statistical analyses, and forecasting methodologies to anticipate performance outcomes with sufficient lead time for intervention. Demonstrated ability to translate complex healthcare quality methodologies into practical analytical frameworks that can guide organizational decision-making and improvement strategies. 3 years required 4 years desired
Leadership Experience: Experience mentoring other analysts and leading improvement initiatives. Experience building and supervising analytics teams preferred. 2 years required 3 years desired
Education Degree in data science, analytics, statistics, public health, business analytics, engineering or related field demonstrating strong analytical foundation and quantitative skills. Master’s degree PhD/Doctorate preferred
Certifications in healthcare analytics, quality improvement, or Epic systems demonstrating specialized knowledge in healthcare data analysis. None Epic’s Clarity & Cogito Certifications
Training Healthcare Training: Training in healthcare delivery systems, quality measures, and methodologies. Understanding of healthcare terminology, clinical documentation requirements, and quality-based reimbursement structures. Basic Understanding Advanced Training
Statistical Methods: Training in statistical analysis, predictive analytics, modeling, and performance evaluation methodologies. Intermediate Level Advanced Level
Process Improvement: Training in data-driven improvement processes and methodologies to evaluate the effectiveness of quality improvement initiatives. Basic Understanding Formal Certification (Lean, Six Sigma, etc.)
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