Automated messaging to improve compliance with diabetes test monitoring.
OBJECTIVE
To evaluate the use of automated systems to prompt patients with diabetes mellitus to obtain overdue laboratory tests for its effectiveness in promoting test compliance and to compare letters, telephone messages, and combinations.


METHODS
Randomized controlled trial.


METHODS
All subjects (N = 13,057) were adult members of Southern California Kaiser Permanente with diabetes and with no record of glycosylated hemoglobin, low-density lipoprotein cholesterol, and urinary microalbumin tests in more than 1 year. The effectiveness of automated telephone calls and letters was compared versus a no-contact control group using the following 5 intervention groups: letter, call, letter that is followed by a call 4 weeks later, call that is followed by a letter 4 weeks later, and letter-call-letter combination. Messages were in English and in Spanish. Adherence to all testing was compared at 8 weeks and 12 weeks after initial contact using chi(2) test and logistic regression analysis.


RESULTS
The proportions of each study group compliant with all tests were 18% to 19% among controls, 21% for a letter or a call, 25% for a letter-call or call-letter, and 26% for a letter-call-letter; letter-call and call-letter were significantly different versus controls (P <.001), and letter-call-letter was not significantly different versus letter-call. Older age was associated with compliance (P <.001).


CONCLUSIONS
The pairing of automated letters and telephone calls in any order was more effective than any single intervention in promoting compliance with diabetes monitoring tests. The relative cost of the letter-call and call-letter approaches to outreach should be considered to determine which is preferred in any given situation.
Derose
Stephen F
SF
Department of Research and Evaluation (SFD), Southern California Kaiser Permanente, Pasadena, CA 91101, USA. stephen.f.derose@kp.org
Nakahiro
Randall K
RK
Ziel
Frederick H
FH
D015190:Blood Glucose Self-Monitoring; D016001:Confidence Intervals; D003920:Diabetes Mellitus / Q000175:diagnosis* / Q000628:therapy; D019468:Disease Management; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D016017:Odds Ratio; D010349:Patient Compliance / Q000706:statistics & numerical data*; D017010:Reminder Systems / Q000706:statistics & numerical data*