Fisher Digital Publications

Title

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

Authors

Suzanne S. Sullivan, SUNY University at Buffalo
Kathryn M. Ledwin, St. John Fisher UniversityFollow
Sharon Hewner, SUNY University at Buffalo

Document Type

Article

Publication Date

9-2023

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.

DOI

https://doi.org/10.1016/j.outlook.2023.102044

Comments

Article originally published in Nursing Outlook, V. 71, Iss. 5 (Set.-Oct. 2023).

https://www.sciencedirect.com/science/article/pii/S0029655423001495?via%3Dihub

Publication Information

Sullivan, Suzanne S.; Ledwin, Kathryn M.; and Hewner, Sharon (2023). "A clinical classification framework for identifying persons with high social and medical needs: The COMPLEXedex-social determinants of health (SDH)." Nursing Outlook 71.5.

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Creative Commons License

This work is licensed under a Creative Commons Attribution-No Derivative Works 4.0 International License.