Data Analyst, Clinical Data Effectiveness

As a Data Analyst, you will:

• Proactively identify and monitor which healthcare facilities consistently generate high-quality, usable clinical documents (e.g., EHRs, discharge summaries, procedure notes) to precisely locate and quantify data gaps.
• Conduct deep-dive analyses by mapping and correlating facility-specific data across disparate sources like structured claims, clinical care summaries (CCDAs), and ADT messages to uncover systematic patterns of missingness, latency, or incongruence in clinical records.
• Establish and maintain clear, transparent reporting on ADT coverage across key geographic, organizational, and technological dimensions (e.g., by county, facility, and underlying EMR system).
• Based on rigorous analysis of data flow and quality, recommend and guide the implementation of optimal technical configurations for existing data vendors (e.g., Bamboo Health, PCC, Experian, HSX).
• Conduct comprehensive evaluations and proof-of-concepts for potential new data integration technologies (e.g., Kno2 vs. Particle Health) to assess viability, quality improvements, and strategic fit.
• Systematically determine the existence and completeness of documentation associated with specific patient visits or encounters.
• Develop a data-driven framework for prioritizing facility targets for direct data acquisition, assessing impact, cost-effectiveness, and technical feasibility.
• Inform and guide vendor strategy around national initiatives such as TEFCA and QHIN adoption, ensuring Counterpart Health is positioned for compliant, high-quality data exchange.
• Partner cross-functionally with Product Managers to define data requirements, Engineers to implement reliable pipelines, and Clinical teams to validate data quality and clinical utility.
• Act as a critical liaison to identify and remove operational and technical bottlenecks, ensuring a predictable, scalable, and reliable clinical data flow across all customer markets.

You should get in touch if you have:

• 2+ years of hands-on data analytics experience, with direct exposure to healthcare data interoperability
• Experience with TEFCA/QHIN frameworks and evolving national interoperability standards.
• Familiarity with vendor-specific data exchange platforms (e.g., Bamboo Health, HSX, Particle Health, Kno2).
• Background in value-based care, population health, or clinical data operations.
• Experience with claims-clinical data reconciliation (e.g., matching EOBs to clinical encounter records).
• Comfort working with Python or similar tools for data manipulation and automation.