Using a Prediction Model to Identify Patients Who Can Benefit from Diabetes Prevention

This implementation project is complete.

PCORI implementation projects promote the use of findings from PCORI-funded studies in real-world healthcare and other settings. These projects build toward broad use of evidence to inform healthcare decisions.

	This PCORI-funded implementation project used a risk prediction tool—shown to identify patients at high risk for developing diabetes—to help patients and their doctors make decisions about preventive treatment.
One in three adults in the United States are at risk for diabetes. Effective treatments are available to prevent diabetes, including medicine and lifestyle changes. But not all patients require treatment. Identifying which patients would benefit most from treatment may help patients and clinicians, such as doctors or nurses, prevent diabetes among patients at greatest risk.

What was the goal of this implementation project?

In a completed PCORI-funded pilot project, researchers looked at data from a landmark clinical trial and other studies to see how well treatment prevented diabetes in different groups of patients. They found that patients at highest risk for diabetes benefited most from preventive treatment. Patients at lower risk got much less or no benefit. Researchers used these findings to create a prediction tool that estimates patients’ risk for diabetes over three years as well as potential benefits from treatment. Patients and clinicians can use this information to help decide together on ways to prevent diabetes, either metformin or a lifestyle program called the Diabetes Prevention Program, or DPP.

This project worked with two health systems, Premier Medical Associates in Pennsylvania, and Mercy in Missouri, to make the prediction tool available at 52 primary care clinics.

What did this project do?

The project team adapted the prediction tool to work with different electronic health record, or EHR, systems. At Premier, a calculator drew from data in the Allscripts EHR to estimate risk. The calculator did not require staff to enter any data. At Mercy, a SMART on FHIR app linked to Epic EHR data to provide the risk estimates.

Clinicians could access the risk prediction information during the patient visit and produce a report. The report included information on each patient’s risk for developing diabetes and how well treatment was likely to work to reduce risk for each patient.

To support the use of the prediction tool, the project team:

• Developed resources on how to use the tool, including a site-specific short video
• Trained clinicians on how to use the tool and discuss results with patients
• Provided sites with technical assistance
• Identified and trained a site champion to promote the use of the tool, fix issues, and work with clinicians who weren’t using the tool to understand their concerns
• Provided feedback reports to clinician champions on clinicians’ use of the tool

What was the impact of this project?

During the project, a total of 96 clinicians used the prediction tool with more than 2,500 patients.

At Premier, clinicians used the tool with 79% of their patients with prediabetes over a 31-month period. The prediction tool identified about half of these patients as having high risk for diabetes. Prescriptions for metformin increased fourfold among these patients. Clinicians also referred 490 patients at high risk to the DPP. Of these, 124 patients followed up; 64 enrolled and met the program’s targeted level of weight loss.

Clinicians at Premier reported that the tool was useful in helping to predict patient risk of diabetes. Patients reported feeling more confident in making decisions once they understood their risk of diabetes. The availability of the prediction tool also facilitated screening for diabetes at Premier. With the increased screening that took place during the project, 148 patients learned they had diabetes.

At Mercy, clinicians piloted the prediction tool with manual data entry. During the pilot, clinicians used it with 58% of their patients with prediabetes. Referral to the DPP increased from 0% to 13% among patients with prediabetes. Metformin prescriptions increased from 3% to 17%.

Completion of the project using the EHR at Mercy was halted by the COVID-19 pandemic. However, the project team did test the EHR-based approach. During testing, clinicians accessed the method with nearly 1,000 patients. The SMART on FHIR app used at Mercy is now available for use with Epic or other EHR systems.

More about this implementation project: