Lead Clinical Quality Consultant
The ideal candidate will have 15 to 20+ years of experience in hospital quality and clinical data roles, with deep hands-on grounding in clinical data abstraction for national quality registries (stroke, cardiac, heart failure, resuscitation, or similar) and a track record of leading quality improvement with hospital quality departments. The position requires a candidate who has mastered chart abstraction and registry reporting end to end, who can work with hospital quality departments as a trusted senior advisor and improve the quality of care, and who will lead the development of the organisation's clinical AI-based data abstraction — defining abstraction standards, owning the accuracy benchmark, and building the clinical team beneath them.
Job Responsibilities:
1. Partner with hospital quality departments to assess current registry workflows — case identification, chart abstraction, data entry, and submission — and identify gaps in accuracy, completeness, timeliness, and staffing effort.
2. Analyze measure performance with hospital quality teams, identify root causes of fallouts, and drive practical improvement plans through to measurable results.
3. Identify documentation problems in patient records, feed them back to clinical teams, and hold feedback and education sessions with staff on registry definitions and measure requirements.
4. Support hospitals in achieving national quality recognition and in preparing registry data for certification and accreditation reviews, including survey preparation and follow-up.
5. Lead the clinical side of client engagements and pilots end to end: scoping, success metrics, on-site or remote working sessions, and results readouts to hospital leadership.
6. Liaise with EHR and IT teams and external vendors on documentation capture, data crosswalks and uploads, and troubleshoot data-quality issues between systems.
7. Lead the development of the organisation's clinical AI-based data abstraction capability — defining abstraction standards and coding-instruction rules, abstracting and adjudicating the gold-standard reference cases used to measure the accuracy of automated registry data extraction, and signing off the accuracy figures the organisation stands behind.
Qualifications:
1. 15 to 20+ years in United States hospital quality, clinical data or registry roles, including substantial hands-on abstraction experience with one or more national quality registries; multi-registry experience is an advantage.
2. Bachelor's or Master's degree in Nursing, Health Information Management, Allied Health, Clinical Sciences or a related healthcare discipline; an active RN licence is strongly preferred.
3. Demonstrated experience creating actionable data and implementing interventions that improved quality measures, with results the candidate can speak to.
4. Demonstrated accuracy track record in abstraction — sustained performance in inter-rater reliability reviews, QA programs or registry audits — and experience running such reviews for others.
5. Experience with automated, AI-based clinical data abstraction — having used, evaluated or helped implement systems that extract and structure information from EHRs and clinical documents — or demonstrably strong working knowledge of such systems, with the ability to clinically evaluate, guide and improve them.
6. Hands-on fluency with registry data-entry platforms (national registry patient management tools or certified vendor entry tools), including embedded coding instructions and edit checks, and with ICD-10-CM codes as used for case identification.
7. Experience across multiple EHR systems (for example Epic or Cerner) and clinical record types, with proficiency in data tools such as Excel or Tableau.
8. Expertise in health information management, including data analysis, clinician education and leading process improvement; strong root-cause-analysis and critical-thinking skills.
9. Executive-level communication: the credibility to advise quality directors and medical leadership, teach clinical staff, and present findings to executive audiences.
10. Ability to document clinical rules clearly for technical teams without requiring software development expertise, and to manage multiple concurrent engagements independently.
11. Understanding of HIPAA and the secure handling of Protected Health Information.
Preferred Qualifications:
1. CPHQ or equivalent healthcare quality certification; RN, LPN, RHIA or RHIT credentials; specialty certifications such as SCRN (stroke) or CHFN (heart failure).
2. Experience with certification programs involving registry data (for example Joint Commission or DNV stroke or cardiac certification), including on-site survey support.
3. Experience across multiple national quality registries; resuscitation registry experience is especially valued.
4. Lean, Six Sigma or equivalent structured process-improvement training.
5. Familiarity with clinical terminology standards beyond ICD-10-CM (SNOMED CT, LOINC, RxNorm, CPT/HCPCS) and with HL7/FHIR interoperability concepts.
6. Prior consulting, advisory or practice-building experience with healthcare technology or services organisations, including collaboration on automated abstraction or clinical AI solutions.
