Appalachian Regional Healthcare Inc.
Clinical Quality Data Abstractor II
Appalachian Regional Healthcare Inc., Lexington, Kentucky, us, 40598
Overview
The Clinical Quality Data Abstractor is responsible for the accurate, timely, and complete abstraction of complex clinical quality measures from the electronic health record and other data sources. This role supports regulatory reporting to CMS, deemed status Accrediting Organizations (TJC, DNV), and state-directed payment programs such as KY HRIP and WV DPP, ensuring data integrity and compliance with all data abstraction specifications. Responsibilities
High Complexity Clinical Data Abstraction: Use EHR, data abstraction platform and abstraction specifications manuals from various entities (e.g., CMS, DNV, TJC, State DPP Programs) to accurately abstract data for measures of varying degrees of complexity, including highly complex measures. Documentation Validation Across Multiple Systems: Utilize documentation from multiple systems (e.g., Meditech, scanned records, ED logs etc.) to ensure completeness and accuracy of abstracted data elements. Apply Measure Logic: Use abstraction manual, abstraction platform resources, quality program data dictionaries and encyclopedias of measures to apply measure logic and inclusion/exclusion criteria with precision, escalate ambiguous cases for second level review. IRR Participation: Participate in inter-rater-reliability (IRR) audits and maintain a ≥95% agreement rate. Training & Development: Maintain up-to-date knowledge of abstraction specifications and regulatory changes through continuing education, support onboarding and peer mentoring of new abstractors as needed. Stakeholder Engagement: Collaborate with clinical teams to clarify documentation, provide fall out trend insights, and support abstraction enhancing workflows. Qualifications
Education Associate’s degree in clinical field or HIM required Clinical licensure (RN, PharmD, RT, PT, LCSW etc.) required unless HIM professional certification Minimum Work Experience Minimum 1 year in bedside nursing or front-line clinical role in a hospital setting required Minimum 2 years complex clinical data abstraction (e.g., Sepsis, PC measures, Stroke) Familiarity with CMS data specifications, IRR audits and abstraction platforms Demonstrated participation in IRR audits with ≥95% agreement (internal candidates only) Licensures and Certifications Licensure in a clinical field required Certified Professional in Healthcare Quality - preferred Certified Health Data Analyst - preferred Required Skills, Knowledge, and Abilities Demonstrated proficiency in abstracting CMS and regulatory core measures including Sep-1, PC Measures, OP-18 and OP-23 Strong understanding of clinical workflows, medical terminology and documentation standards Ability to interpret complex clinical situations and apply abstraction logic and specifications accurately Experience with electronic health records (EHR) systems, preferably Meditech, abstraction platforms and secure remote access tools High attention to detail and commitment to data integrity over speed Strong written and verbal communication skills, able to document rationale for abstraction decisions
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The Clinical Quality Data Abstractor is responsible for the accurate, timely, and complete abstraction of complex clinical quality measures from the electronic health record and other data sources. This role supports regulatory reporting to CMS, deemed status Accrediting Organizations (TJC, DNV), and state-directed payment programs such as KY HRIP and WV DPP, ensuring data integrity and compliance with all data abstraction specifications. Responsibilities
High Complexity Clinical Data Abstraction: Use EHR, data abstraction platform and abstraction specifications manuals from various entities (e.g., CMS, DNV, TJC, State DPP Programs) to accurately abstract data for measures of varying degrees of complexity, including highly complex measures. Documentation Validation Across Multiple Systems: Utilize documentation from multiple systems (e.g., Meditech, scanned records, ED logs etc.) to ensure completeness and accuracy of abstracted data elements. Apply Measure Logic: Use abstraction manual, abstraction platform resources, quality program data dictionaries and encyclopedias of measures to apply measure logic and inclusion/exclusion criteria with precision, escalate ambiguous cases for second level review. IRR Participation: Participate in inter-rater-reliability (IRR) audits and maintain a ≥95% agreement rate. Training & Development: Maintain up-to-date knowledge of abstraction specifications and regulatory changes through continuing education, support onboarding and peer mentoring of new abstractors as needed. Stakeholder Engagement: Collaborate with clinical teams to clarify documentation, provide fall out trend insights, and support abstraction enhancing workflows. Qualifications
Education Associate’s degree in clinical field or HIM required Clinical licensure (RN, PharmD, RT, PT, LCSW etc.) required unless HIM professional certification Minimum Work Experience Minimum 1 year in bedside nursing or front-line clinical role in a hospital setting required Minimum 2 years complex clinical data abstraction (e.g., Sepsis, PC measures, Stroke) Familiarity with CMS data specifications, IRR audits and abstraction platforms Demonstrated participation in IRR audits with ≥95% agreement (internal candidates only) Licensures and Certifications Licensure in a clinical field required Certified Professional in Healthcare Quality - preferred Certified Health Data Analyst - preferred Required Skills, Knowledge, and Abilities Demonstrated proficiency in abstracting CMS and regulatory core measures including Sep-1, PC Measures, OP-18 and OP-23 Strong understanding of clinical workflows, medical terminology and documentation standards Ability to interpret complex clinical situations and apply abstraction logic and specifications accurately Experience with electronic health records (EHR) systems, preferably Meditech, abstraction platforms and secure remote access tools High attention to detail and commitment to data integrity over speed Strong written and verbal communication skills, able to document rationale for abstraction decisions
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