Automated Telephone Outreach With Speech Recognition to Improve Diabetes Care: A Randomized Controlled Study

Randomly allocate a total of 1200 health plan members with diabetes to automated telephone outreach with speech recognition (ATO-SR; N = 600) or usual care (N = 600). The intervention is a series of three calls, using automated calls, originating from the health plan, using interactive speech recognition technology, spaced approximately 4-6 weeks apart, to encourage participants to fulfill the recommended testing (dilated eye examinations, glycated hemoglobin, LDL-cholesterol, microalbumin) that had not been performed received in the preceding year.

Inclusion criteria

• Age 18 years or older
• Diabetes, defined as either 1) filled a prescription for insulin or an oral hypoglycemic agent; or, 2) had two outpatient or one inpatient or two outpatients encounter claims with an ICD9-CM or CPT code indicating diabetes.
• Gap in a key diabetes management metric as evidenced by no claim for a dilated eye examination in the prior 15 months and no claim for one or more of the following tests: glycated hemoglobin, LDL-cholesterol, or microalbumin. (Individuals with evidence of having received ACE-inhibitors or angiotensin receptor blockers were considered to have had a microalbumin test.)

Exclusion criteria

• No primary care clinician in the data base
• Those who had previously asked the health plan to exclude them from research or quality improvement
• Women whose claim records contained diagnoses suggesting gestational diabetes