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A Diabetes Prevention Cascade Model for Healthcare Organizations: Results From a Pilot for Disproportionately
Tamkeen Khan1, Alejandro Hughes2, Madeline Brady1
1American Medical Association, Chicago, Illinois.
Introduction:
A conceptual cascade model was developed to track diabetes prevention efforts in the process for managing patients with prediabetes and compared with observed data from healthcare organizations.
Methods:
The cascade tracked patients eligible for diabetes prevention at each level of the cascade derived from multiple data sources. This was aligned with eligible (aggregated) data from 3 pilot healthcare organizations (n=70,911), including disproportionately affected population of both Black and Hispanic women (n=18,079).
Results:
Healthcare organizations had higher screening eligibility than expected (43% vs 35%). Laboratory tests ordered were lower than expected for the total population (42% vs 60%) and aligned well for the disproportionately affected population (57% vs 60%). Ranges for prediabetes laboratory tests were close to expected for the total (38% vs 35%) and disproportionately affected population (39% vs 35%). Referral rates were higher (assuming awareness of the condition) in the total (188% vs 25%) and disproportionately affected population (264% vs 25%). Conversion rates from referral to enrollment were lower than expected in the total (14% vs 25%) and disproportionately affected population (13% vs 25%).
Conclusions:
Despite increased referral rates, there is still a need to improve the enrollment conversion rate. Feedback from the conceptual model to observed data can provide critical findings to facilitate diabetes prevention efforts.
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