Locum Tenens Hospitalist

Locum Tenens Hospitalist

Micro1 is engaging with Locum Tenens Hospitalist to contribute their medical expertise to a customer project focused on inpatient care and documentation standards. In this role, you'll apply your adult inpatient clinical training to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.

Scope of Work

• Review medical records, including FHIR data and clinical notes, for AI training.
• Check whether clinical information and claims are supported by the medical record.
• Review inpatient adult medicine documentation, including HPI, PMH, medication reconciliation, social history, assessments, and plans.
• Follow clear guidelines and apply the same standards consistently.
• Identify missing, incorrect, or inconsistent information in medical records, including renal- and hepatic-adjusted dosing, medication interactions, and age-appropriate clinical details.
• Share feedback to help improve AI models and data quality.

Preferred Qualifications

• At least 5 years of hospitalist experience.
• MD or DO, board certified in Internal Medicine (or Internal Medicine with a Hospital Medicine focused practice designation).
• Current or recent inpatient hospitalist experience (within the last 2 years).
• Strong understanding of inpatient documentation and hospital workflows, including admission, daily progress notes, transitions of care, and discharge.
• Comfortable reviewing clinical notes and raw medical record data.
• Strong attention to detail and ability to follow clear guidelines consistently.
• Experience with chart review, clinical documentation improvement, utilization review, or medical coding/QA is a plus.

Compensation Structure

• Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert's experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.