In-patient hospitalist with CDI/coding background (Train AI Models Part Time!)
• hackajob
is collaborating with
• *Mercor**
to connect them with exceptional professionals for this role.*
## About the Role Mercor is seeking *In-Patient Hospitalists with Clinical Documentation Improvement (CDI) and medical coding expertise on behalf of a healthcare AI partner building advanced clinical decision-support tools. We onboard multiple experts for this role on a rolling basis. In this role, you will leverage both your clinical and coding expertise to review, annotate, and validate complex medical data.
Your work will directly support the development of accurate, compliant, and explainable healthcare AI systems, particularly in areas involving documentation integrity, coding accuracy, and reimbursement logic. ## Key Responsibilities ### Clinical Data Annotation - Review and label in-patient clinical documentation*, including EHR data, discharge summaries, and case notes.
• Identify and validate *diagnoses, comorbidities, complications (CC/MCC), procedures, and treatment pathways.
• Apply knowledge of ICD-10-CM/PCS coding standards and DRG grouping logic during annotation. ### Quality Review & Validation - Audit annotated datasets for clinical accuracy, documentation completeness, and coding integrity.
• Ensure alignment between clinical documentation and coded data (ICD-10, DRGs, billing elements).
• Validate AI-generated outputs for both clinical correctness and reimbursement compliance. ### Knowledge Contribution - Provide expert input on CDI best practices, coding guidelines, and documentation standards.
• Help define annotation frameworks incorporating ICD-10 classifications, MS-DRG grouping, and payer requirements.
• Collaborate with data scientists to improve AI understanding of clinical nuance and coding dependencies. ### Model Evaluation & Feedback - Evaluate AI-generated clinical summaries, coding suggestions, and documentation outputs.
• Flag inaccuracies related to under/over-coding, missing specificity, or documentation gaps.
• Provide structured feedback to improve model performance in clinical reasoning and coding alignment. ### Documentation & Training Support - Contribute to clinical documentation and coding standards for AI training workflows.
• Assist in developing onboarding materials for clinicians and annotators, particularly around CDI and coding accuracy. ## Requirements - *MD or DO degree (Internal Medicine strongly preferred).
• Board-certified or board-eligible in Internal Medicine.
• Active medical license in good standing.
• 2+ years of in-patient / hospitalist experience.
• Demonstrated experience in Clinical Documentation Improvement (CDI) and/or medical coding.
• Relevant certifications preferred: CCS, CDIP, CCDS, or similar.
• Strong working knowledge of:
• ICD-10-CM/PCS coding systems - MS-DRG grouping and reimbursement logic - Insurance billing workflows and documentation requirements - Experience in academic or large hospital systems* preferred.
Apply tot his job
Apply To this Job
is collaborating with
• *Mercor**
to connect them with exceptional professionals for this role.*
## About the Role Mercor is seeking *In-Patient Hospitalists with Clinical Documentation Improvement (CDI) and medical coding expertise on behalf of a healthcare AI partner building advanced clinical decision-support tools. We onboard multiple experts for this role on a rolling basis. In this role, you will leverage both your clinical and coding expertise to review, annotate, and validate complex medical data.
Your work will directly support the development of accurate, compliant, and explainable healthcare AI systems, particularly in areas involving documentation integrity, coding accuracy, and reimbursement logic. ## Key Responsibilities ### Clinical Data Annotation - Review and label in-patient clinical documentation*, including EHR data, discharge summaries, and case notes.
• Identify and validate *diagnoses, comorbidities, complications (CC/MCC), procedures, and treatment pathways.
• Apply knowledge of ICD-10-CM/PCS coding standards and DRG grouping logic during annotation. ### Quality Review & Validation - Audit annotated datasets for clinical accuracy, documentation completeness, and coding integrity.
• Ensure alignment between clinical documentation and coded data (ICD-10, DRGs, billing elements).
• Validate AI-generated outputs for both clinical correctness and reimbursement compliance. ### Knowledge Contribution - Provide expert input on CDI best practices, coding guidelines, and documentation standards.
• Help define annotation frameworks incorporating ICD-10 classifications, MS-DRG grouping, and payer requirements.
• Collaborate with data scientists to improve AI understanding of clinical nuance and coding dependencies. ### Model Evaluation & Feedback - Evaluate AI-generated clinical summaries, coding suggestions, and documentation outputs.
• Flag inaccuracies related to under/over-coding, missing specificity, or documentation gaps.
• Provide structured feedback to improve model performance in clinical reasoning and coding alignment. ### Documentation & Training Support - Contribute to clinical documentation and coding standards for AI training workflows.
• Assist in developing onboarding materials for clinicians and annotators, particularly around CDI and coding accuracy. ## Requirements - *MD or DO degree (Internal Medicine strongly preferred).
• Board-certified or board-eligible in Internal Medicine.
• Active medical license in good standing.
• 2+ years of in-patient / hospitalist experience.
• Demonstrated experience in Clinical Documentation Improvement (CDI) and/or medical coding.
• Relevant certifications preferred: CCS, CDIP, CCDS, or similar.
• Strong working knowledge of:
• ICD-10-CM/PCS coding systems - MS-DRG grouping and reimbursement logic - Insurance billing workflows and documentation requirements - Experience in academic or large hospital systems* preferred.
Apply tot his job
Apply To this Job