Remote | Internal Medicine Hospitalist — $80–$115/hour

24-Mag•New York, NY

12h•Remote

About The Position

24-MAG LLC is recruiting experienced Internal Medicine Hospitalists and physicians for a fully remote freelance/contract consulting opportunity supporting advanced AI training and evaluation. The work applies adult inpatient medicine expertise to reviewing medical records, evaluating clinical documentation, assessing medication management, and checking the accuracy and consistency of medical information used in AI training. Assignments may include reviewing HPI and PMH, medication records, clinical assessments, treatment plans, admission and progress notes, transitions of care, and discharge documentation. Deliverables include structured clinical reviews, medical accuracy assessments, and actionable written feedback to improve AI model performance and medical data quality. Compensation is $80–$115 per hour, and 50 openings are available. Previous AI training project experience is not required.

Requirements

MD or DO qualification with Internal Medicine board certification is preferred; physicians with a Hospital Medicine-focused practice designation are also identified as preferred.
At least 5 years of professional hospitalist experience is preferred.
Current or recent inpatient hospitalist experience, ideally within the past 2 years, is preferred.
Strong expertise in adult inpatient medicine and hospital-based patient management.
Understanding of hospital admission procedures and inpatient clinical evaluations.
Experience reviewing daily progress notes, clinical assessments, treatment plans, and discharge summaries.
Knowledge of HPI, PMH, and social history documentation.
Practical experience with medication reconciliation and inpatient medication management.
Understanding of renal and hepatic dose adjustments and clinically relevant medication interactions.
Ability to identify inaccurate, incomplete, or inconsistent information in medical records.
Familiarity with electronic health records and structured clinical data; comfort reviewing FHIR resources or comparable raw healthcare record information.
Strong understanding of hospital workflows, transitions of care, and clinical documentation standards.
Ability to determine whether medical statements are supported by the underlying patient record.
Strong clinical reasoning, analytical problem-solving, and professional judgment.
Excellent attention to detail and ability to follow structured evaluation guidelines consistently.
Clear written communication skills for explaining clinical findings and documentation discrepancies.
Ability to work independently on complex medical record evaluation assignments.

Nice To Haves

Experience with clinical documentation improvement (CDI).
Familiarity with chart review, utilisation review, medical coding, or clinical quality assurance.
Prior experience with AI model training or evaluation projects is not required.

Responsibilities

Review medical records, clinical notes, and structured healthcare data, including FHIR resources.
Determine whether documented clinical statements and conclusions are supported by the underlying medical record.
Assess the accuracy, completeness, and consistency of patient information across records and identify discrepancies between structured data and narrative notes.
Review adult inpatient documentation, including HPI, PMH, admission records, daily progress notes, transitions of care, and discharge documentation.
Evaluate clinical assessments, treatment plans, and documented medical reasoning.
Assess social history, patient characteristics, and continuity-of-care information; identify missing, inaccurate, or inconsistent documentation.
Evaluate medication reconciliation records for accuracy, completeness, and consistency.
Review clinically relevant medication interactions and dosing considerations, including renal- and hepatic-adjusted dosing.
Assess medication management and clinical decision-making in light of documented patient information and characteristics.
Evaluate medical information used to train and assess AI systems, identifying unsupported conclusions, omissions, and dataset inconsistencies.
Apply review guidelines consistently and assess whether clinical information accurately reflects patient circumstances and inpatient care practices.
Provide structured expert feedback to improve AI model performance and medical data quality.
Review records for completeness, internal consistency, and alignment with documented care; identify opportunities to improve documentation accuracy and clarity.
Document findings in clear, structured written evaluations and explain errors and clinically appropriate corrections.