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How to fill out the Mini-Sentinel Common Data Model V4.0 online
Filling out the Mini-Sentinel Common Data Model (MSCDM) V4.0 online is crucial for maintaining accurate data in public health surveillance. This guide provides clear steps to ensure that you complete the form efficiently and correctly.
Follow the steps to complete the Mini-Sentinel Common Data Model V4.0 online.
- Press the ‘Get Form’ button to access the Mini-Sentinel Common Data Model V4.0 and open it in your online document management system.
- Begin by entering the unique member identifier (PatID). This is crucial for linking records across tables. Each member should retain the same PatID across all their records.
- Input the enrollment start date (Enr_Start) and end date (Enr_End). Use the first day of the month if the exact date is unknown. Ensure that Enr_End is not earlier than Enr_Start.
- Indicate if the health plan covers medical and/or drug care for the enrollment period by marking 'Y' for yes or 'N' for no in the MedCov and DrugCov fields.
- Complete the demographic information for the member, including birth date, sex, race, and ZIP code. Ensure that you only input the most recent information.
- Fill out the tables such as Dispensing, Encounter, Diagnosis, and Procedure according to the guidelines provided. Each table must have a consistent format and data integrity.
- Review all data entries for accuracy before saving. Use the opportunity to cross-check against available data resources.
- Once completed, ensure you save your changes, and consider downloading or printing the document for your records.
- In case of issues or uncertainties, refer to the documentation or reach out to the support contact provided for assistance.
Start filling out the Mini-Sentinel Common Data Model V4.0 online today to contribute to vital health data management!
The Sentinel Operations Center (SOC) coordinates the network of Sentinel Data Partners and leads development of the Sentinel Common Data Model (SCDM), a standard data structure that allows Data Partners to quickly execute distributed programs against local data.
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