Healthcare Data Analyst

At Community Hospice and Palliative Care, the Healthcare Data Analyst, Quality and Compliance supports mission-critical analytics that strengthen performance, quality measurement, and regulatory readiness. In this onsite role in Jacksonville, you will turn clinical, quality, operational, and compliance data into actionable insights used by quality and compliance leadership, QAPI, and survey readiness activities.

The role reports to the Chief Compliance and Quality Officer and acts as the primary analytics resource for QAPI
, compliance monitoring, regulatory reporting, and survey readiness. You will build repeatable measurement, automate reporting workflows, and support executive-level communication of quality and compliance performance.

• Partner with clinical and compliance leaders to define, calculate, and maintain certified quality and compliance KPIs
  , including documented definitions, data sources, and calculation logic in the enterprise KPI registry.
• Monitor quality indicators, clinical outcomes, and performance trends across hospice, home health, palliative care, and PACE
  ; identify variation by team, setting, and market, and explain root causes.
• Analyze CAHPS data, including response trends, patient feedback themes, and demographic patterns, and support quality improvement initiatives through detailed reporting.
• Work with BI Engineers and technical partners to build and maintain automated quality dashboards and scorecards, reducing manual data pulls and static spreadsheets.
• Conduct conversion validation and reconciliation testing for Databricks platform and EMR transitions; document defects and confirm converted data matches source systems and certified definitions.
• Provide baseline data, statistical process control, and results tracking for PIPs and QAPI performance improvement projects.
• Develop predictive and early-warning analytics with clinical leaders, such as live discharge risk, length-of-stay outliers, and CAHPS decline.
• Use approved AI tools (example:
  Claude
  , Microsoft Copilot
  , Databricks Genie
  ) to speed analysis, comment coding, documentation, and report drafting, while verifying all AI output against source data before use.
• Follow Alivia Care AI governance
  , HIPAA, and data privacy standards; use only approved tools with protected health information, and submit new AI use cases for governance review.
• Identify manual quality and compliance processes that can be automated or AI-assisted, partnering with operations, technology, and analytics teams to prioritize and implement solutions.
• Provide data and analysis for survey readiness, accreditation reviews, and compliance audits as requested by the Chief Compliance Officer.
• Prepare and present executive, committee, and Board-level reports translating quality and compliance data into actionable information.
• Develop executive-level dashboards, scorecards, and analytical summaries for strategic decision-making, regulatory readiness, and performance improvement.
• Serve as a data resource for quality committees, the Hospice Experience Committee, and interdisciplinary meetings.
• Train clinical and quality staff to read dashboards and apply data to improvement work.
• Other duties as assigned.

• Bachelor’s degree in health informatics, healthcare administration, statistics, data analytics, nursing, public health, or related field (required).
• 3 to 5 years of healthcare data analysis experience, including quality measurement or clinical outcomes reporting.
• Hospice or home health experience strongly preferred, including HOPE
  , CAHPS Hospice
  , or OASIS
  .
• Demonstrated experience writing SQL and building dashboards in Power BI or a comparable BI tool.
• Certification such as CPHQ
  , CHDA
  , Microsoft Power BI Data Analyst
  , or Databricks (preferred).
• Proficiency in SQL and advanced Excel, including Power Query and pivot tables.
• Proficiency in Power BI (or comparable BI tool), including data modeling and basic DAX
  .
• Working knowledge of Python or R (preferred).
• Familiarity with cloud data platforms such as Databricks
  .
• Knowledge of data quality practices: validation, reconciliation, data lineage, and documentation.
• Applied statistics including rates, basic risk adjustment, significance testing, and statistical process control.
• Understands generative AI and predictive model limits, including inaccurate output and bias; writes effective prompts and verifies AI output against source data.
• Knowledge of responsible AI use in healthcare, including HIPAA, protected health information…