Micro1 review · AI Training & Data Labeling
Pediatric Hospitalist — Inpatient Documentation AI Training (micro1)
What the work involves
micro1 is engaging Pediatric Hospitalist Physicians to review inpatient pediatric documentation for a customer project focused on inpatient care and documentation standards. Working from medical records including FHIR data and clinical notes, you'll check whether clinical information and claims are supported by the record, review inpatient documentation such as HPI, PMH, birth and developmental history, immunization status, assessments and plans, and identify missing, incorrect or inconsistent information — including weight-based dosing and age-appropriate clinical details.
You'll follow clear guidelines consistently and share feedback that improves AI models and data quality. No prior AI experience is required — your pediatric inpatient expertise is what matters.
What you'll do
- 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 pediatric documentation, including HPI, PMH, birth and developmental history, immunization status, assessments and plans
- Follow clear guidelines and apply the same standards consistently
- Identify missing, incorrect or inconsistent information, including weight-based dosing and age-appropriate clinical details
- Share feedback to help improve AI models and data quality
Requirements & eligibility
- At least 5 years of hospitalist experience
- MD or DO, board certified in Pediatrics (or Pediatrics with a Pediatric Hospital Medicine subspecialty certification)
- Current or recent inpatient pediatric 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
How to apply
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