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A clinical classification framework for identifying persons with high social and medical needs: The COMPLEXedex-SDH
Suzanne S Sullivan1, Kathryn M Ledwin1, Sharon Hewner1
1Department of Nursing, University at Buffalo, State University of New York, Buffalo, NY.
Nursing Outlook
|September 20, 2023
Summary
This study developed the COMPLEXedex-SDH algorithm, integrating nursing expertise to identify high-need patients and improve health equity. The algorithm effectively classifies populations for targeted interventions, reducing bias in healthcare access.
Area of Science:
- Health Services Research
- Nursing Informatics
- Precision Health
Background:
- First-generation algorithms for identifying patient needs created bias due to unequal access to care.
- Precision health strategies are essential to mitigate bias and advance health equity.
Purpose of the Study:
- To incorporate nursing expertise into defining high-need patients.
- To create a clinical classification algorithm for targeted nursing interventions.
Main Methods:
- A two-phase retrospective, descriptive cohort study was conducted.
- The algorithm was built using 2019 data (19,20,848 adults) and validated with 2021 data (15,99,176 adults).
Main Results:
- The COMPLEXedex-SDH algorithm identified distinct patient populations: cross-cohort needs (10.9%), high-need individuals (17.7%), those with suboptimal healthcare utilization (13.8%), and high-need individuals with suboptimal utilization (6.2%).
Conclusions:
- The COMPLEXedex-SDH algorithm facilitates the identification of high-need patients and optimizes value-based care.
- It enables the creation of actionable cohorts for prioritized outreach, aiming to enhance health equity and patient outcomes.
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