Automated Telephone Outreach With Speech Recognition to Improve Diabetes Care: A Randomized Controlled Study
Automated Telephone Outreach With Speech Recognition to Improve Diabetes Care: A Randomized Controlled Study
The purpose of this study is to evaluate the effectiveness of automated telephone outreach
 with speech recognition to improve diabetes care.
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