Data Analyst, Clinical Data Effectiveness
New
C
Counterpart HealthHealth Tech
Remote-first cultureFull-TimeMiddle
Salary$77,000—$100,000 USD
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Job Details
- Experience
- 2+ years
- Required Skills
- PythonSQLData visualizationData analytics
Requirements
- 2+ years of hands-on data analytics experience with exposure to healthcare data interoperability.
- Strong hands-on experience with healthcare data standards: HL7, CCDA, and ADT messages.
- Proficiency in SQL and experience working with large, complex datasets like claims, clinical logs, and interoperability data.
- Background in analyzing interoperability networks such as Carequality, CommonWell, or eHealthExchange.
- Experience with HIE integrations.
- Strong data visualization skills and the ability to communicate with technical and non-technical stakeholders.
- Investigative mindset to resolve data discrepancies.
- Self-directed project management capabilities.
- Experience with TEFCA/QHIN frameworks (preferred).
- Familiarity with vendor-specific data exchange platforms such as Bamboo Health, HSX, Particle Health, or Kno2 (preferred).
- Background in value-based care, population health, or clinical data operations (preferred).
- Experience with claims-clinical data reconciliation (preferred).
- Comfort working with Python for data manipulation and automation (preferred).
Responsibilities
- Identify and monitor healthcare facilities to quantify data gaps in EHRs, discharge summaries, and procedure notes.
- Perform deep-dive analyses to uncover patterns of missingness or latency in clinical data across claims, CCDAs, and ADT messages.
- Establish and maintain reporting on ADT coverage across geographic and organizational dimensions.
- Recommend and implement optimal technical configurations for existing data vendors.
- Conduct evaluations and proof-of-concepts for new data integration technologies to assess strategic fit.
- Develop a framework for prioritizing facility targets for direct data acquisition.
- Inform and guide vendor strategy regarding TEFCA and QHIN adoption.
- Partner with Product, Engineering, and Clinical teams to define data requirements and validate clinical utility.
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