Practical Tips to Improve Measure Performance for Depression Screening and Follow up Quality Measure
December 4, 2025
The Design Studios for Data Exchange, hosted by EPT Data SME Connecting for Better Health, have helped EPT practices develop workflows, overcome challenges, and develop a more automated data approach to improve performance on key quality measures.
Resources
User Stories
- Jordan Gomez
- This document outlines the user story for Jordan Gomez (fictitious persona), a non-binary, native Spanish-speaking teen on Medi-Cal, focusing on the workflow when the initial depression screening (PHQ-2) is positive and the same day follow up depression screening (PHQ-9) is negative.
- Albert Hughes
- This document details the Depression Screening and Follow-up (DSF-E) User Story for Albert Hughes (fictitious persona), a 65-year-old patient, that tracks his care journey from a positive depression screen to a behavioral health case management encounter, grief counseling, and eventual closure of the HEDIS quality measure gap.
- This quick reference guide outlines the process for healthcare providers to submit standard supplemental data to specifically report the Depression Screening and Follow-Up (DSF-E) measure assessments completed. This workflow automates the current manual entry of this data into population health management tools.
- This playbook translates Design Studio insights into practical guidance that organizations can use to improve data accuracy and completeness, streamline workflows, reduce manual burden, and increase DSF-E measure performance.
Sponsored by:
