Internal Medicine Documentation Reviewer

OpenTrain AI, Inc.; Northern (KY); À distance; USD 110 000 - 172 000; Temps partiel

Résumé du poste

OpenTrain AI, Inc. seeks experienced healthcare professionals to assist AI training by reviewing inpatient adult medicine records, including structured FHIR data and clinical notes.

You will verify that clinical claims are supported, identify missing or inconsistent details, and provide feedback to improve documentation quality and model performance.

Part-time contract work with hourly pay; MD/DO in Internal Medicine, 5+ years of hospitalist experience, and fluent English are required.

Qualifications

• MD or DO with board certification in Internal Medicine.
• Minimum of five years of hospitalist experience.
• Current or recent inpatient hospitalist practice within the past two years.
• Professional fluency in English.

Responsabilités

• Review histories of present illness, past medical histories, medication reconciliations, social histories, assessments, and care plans.
• Evaluate admission, daily progress, transitions of care, and discharge documentation.
• Review renal- and hepatic-adjusted dosing, medication interactions, and age-appropriate clinical details.
• Apply review guidelines consistently and provide feedback that improves model performance and data quality.

Connaissances

Professional fluency in English

Formation

MD or DO degree with board certification in Internal Medicine

At least five years hospitalist experience

Description du poste

The Work

You will review inpatient adult medicine records used for AI training. Your work will combine hospitalist judgment with structured review of FHIR data and clinical notes.

You will assess whether clinical claims are supported by the medical record and identify missing, incorrect, or inconsistent details. You will also provide feedback on documentation quality, consistency, and clinical accuracy.

• Review histories of present illness, past medical histories, medication reconciliations, social histories, assessments, and care plans.
• Evaluate admission, daily progress, transitions-of-care, and discharge documentation.
• Review renal- and hepatic-adjusted dosing, medication interactions, and age-appropriate clinical details.
• Apply review guidelines consistently and provide feedback that improves model performance and data quality.

What It Pays And Takes

This is part-time contract work. Candidates must be able to review clinical notes and raw medical-record data with careful, consistent judgment.

• Pay: $80 to $125 per hour equivalent, paid per task that meets the project specifications.
• Open to candidates in the United Arab Emirates, Argentina, Austria, Bangladesh, Belgium, Bahrain, Brazil, Canada, Switzerland, Chile, Colombia, Germany, Denmark, Algeria, Egypt, Spain, Ethiopia, France, the United Kingdom, Ghana, Greece, Indonesia, India, Italy, Jordan, Japan, Kenya, Kyrgyzstan, Kuwait, Kazakhstan, Lebanon, Sri Lanka, Morocco, Mexico, Malaysia, Nigeria, the Netherlands, Oman, Peru, the Philippines, Pakistan, Palestine, Portugal, Qatar, Saudi Arabia, Singapore, Thailand, Tunisia, Taiwan, the United States, Uzbekistan, Vietnam, and South Africa.
• Professional fluency in English is required.
• MD or DO degree with board certification in Internal Medicine.
• At least five years of hospitalist experience.
• Current or recent inpatient hospitalist practice within the past two years.
• Strong understanding of clinical documentation and comfort reviewing medical records.
• Helpful experience includes chart review, clinical documentation improvement, utilization review, medical coding, or medical quality assurance.

About AI Training Work

AI training is the human work behind systems that learn from examples, including reviewing records and rating whether model outputs are accurate and well supported. OpenTrain helps people find AI training and data‑labeling roles, build a profile, and apply in one place. Experienced professionals are needed for specialized work where sound medical judgment improves the quality of training data.