A Diabetes Prevention Cascade Model for Healthcare Organizations: Results From a Pilot for Disproportionately Affected Populations

Abstract

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.