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A clinical classification framework for identifying persons with high social and medical needs: The COMPLEXedex-social determinants of health (SDH)

  • SUNY Buffalo

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Background: First-generation algorithms resulted in high-cost features as a representation of need but unintentionally introduced systemic bias based on prior ability to access care. Improved precision health approaches are needed to reduce bias and improve health equity. Purpose: To integrate nursing expertise into a clinical definition of high-need cases and develop a clinical classification algorithm for implementing nursing interventions. Methods: Two-phase retrospective, descriptive cohort study using 2019 data to build the algorithm (n = 19,20,848) and 2021 data to test it in adults ≥18 years old (n = 15,99,176). Discussion: The COMPLEXedex-SDH algorithm identified the following populations: cross-cohort needs (10.9%); high-need persons (cross-cohort needs and other social determinants) (17.7%); suboptimal health care utilization for persons with medical complexity (13.8%); high need persons with suboptimal health care utilization (6.2%). Conclusion: The COMPLEXedex-SDH enables the identification of high-need cases and value-based utilization into actionable cohorts to prioritize outreach calls to improve health equity and outcomes.

Original languageEnglish
Article number102044
JournalNursing Outlook
Volume71
Issue number5
DOIs
StatePublished - Sep 1 2023

Keywords

  • Care coordination
  • Provider–provider communication
  • Social determinants of health
  • Social need

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