Data Analyst, Clinical Data Effectiveness
New
C
Counterpart HealthHealthcare data
Remote - USAFull-TimeMiddle
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Experience
- 5+ years of hands-on data analytics experience, with direct exposure to healthcare data interoperability
- Required Skills
- PythonSQLData visualization
Requirements
- Bring 5+ years of hands-on data analytics experience with direct exposure to healthcare data interoperability.
- Have strong hands-on experience with HL7, CCDA, and ADT messages.
- Be proficient in SQL and comfortable working with large, complex datasets, including claims, clinical logs, and interoperability data.
- Have a background analyzing interoperability networks such as Carequality, CommonWell, or eHealthExchange, or HIE integrations.
- Be skilled in data visualization and able to present complex findings to technical and non-technical stakeholders.
- Be able to investigate causes of missing data and diverging metrics.
- Manage multiple analytical projects independently.
- Experience with TEFCA/QHIN frameworks and national interoperability standards is preferred.
- Familiarity with vendor-specific data exchange platforms such as Bamboo Health, HSX, Particle Health, or Kno2 is preferred.
- Experience in value-based care, population health, or clinical data operations is preferred.
- Experience with claims-clinical data reconciliation is preferred.
- Comfort with Python or similar tools for data manipulation and automation is preferred.
Responsibilities
- Identify and monitor facilities that generate high-quality, usable clinical documents, and quantify data gaps.
- Map and correlate facility-specific data across claims, clinical care summaries (CCDAs), and ADT messages to uncover missingness, latency, and incongruence.
- Report ADT coverage across geographic, organizational, and technological dimensions, including county, facility, and EMR system.
- Recommend technical configurations for existing data vendors based on data flow and quality analysis.
- Evaluate potential data integration technologies through comprehensive assessments and proof-of-concepts.
- Determine the existence and completeness of documentation associated with patient visits or encounters.
- Develop a data-driven framework for prioritizing facilities for direct data acquisition.
- Guide vendor strategy for initiatives such as TEFCA and QHIN adoption.
- Partner with Product Managers, Engineers, and Clinical teams to define data requirements, implement pipelines, and validate data quality and clinical utility.
- Identify and remove operational and technical bottlenecks in clinical data flow.
View Full Description & ApplyYou'll be redirected to the employer's site
