Increasing Referrals to a YMCA-Based Diabetes Prevention Program: Effects of Electronic Referral System Modification and Provider Education in Federally Qualified Health Centers.

INTRODUCTION: The Diabetes Prevention Program has been translated to community settings with varying success. Although primary care referrals are used for identifying and enrolling eligible patients in the Diabetes Prevention Program, little is known about the effects of strategies to facilitate and sustain eligible patient referrals using electronic health record systems. METHODS: To facilitate and sustain patient referrals, a modification to the electronic health record system was made and combined with provider education in 6 federally qualified health centers in the Bronx, New York. Referral data from April 2012 through November 2014 were analyzed using segmented regression analysis. RESULTS: Patient referrals increased significantly after the modification of the electronic health record system and implementation of the provider education intervention. Before the electronic system modification, 0 to 2 patients were referred per month. During the following year (September 2013 through August 2014), which included the provider education intervention, referrals increased to 1 to 9 per month and continued to increase to 5 to 11 per month from September through November 2014. CONCLUSIONS: Modification of an electronic health record system coupled with a provider education intervention shows promise as a strategy to identify and refer eligible patients to community-based Diabetes Prevention Programs. Further refinement of the electronic system for facilitating referrals and follow-up of eligible patients should be explored.

Combining clinical and population-level data to understand the health of neighborhoods.

From February through December 2012, we examined responses to health behavior questions integrated into the electronic medical record of primary care centers in the Bronx, New York in the context of New York City Community Health Survey data. We saw a higher proportion of unhealthy behaviors among patients than among the neighborhood population. Analyzing clinical data in the neighborhood context can better target at-risk populations.