Evaluation of a diabetes education call center intervention

Suzanne Austin Boren, Gianluca De Leo, F. Fungai Chanetsa, Joe Donaldson, Santosh Krishna, E. Andrew Balas

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Patients require education and information as they engage in self-help, self-care, and disease management activities. The purpose of this study was to determine how effective voice technologies are in diabetes patient education. A pretest-posttest study was conducted to evaluate the effectiveness of prerecorded educational messages delivered via the telephone to participants with diabetes. The intervention, consisted of 24 four-minute messages on the topics of knowledge and prevention, glucose level, diet and activity, and management and coping. Eighteen persons with diabetes participated in the pretest-posttest trial. A total of 324 educational messages were listened to over a 12-week intervention period. The pretest-posttest trial demonstrated that a brief telephone-based diabetes education intervention can have a significant impact on increasing frequency of checking blood for glucose (p = 0.017), improving general diabetes knowledge (p = 0.048), and improving insulin-specific knowledge (p = 0.020). Automated educational interventions should be based on scientifically sound evidence and can be effectively delivered by telephone. Automated telephone-based diabetes education may be used alone or as a supplement to existing diabetes education. Automated education is a viable solution when healthcare organizations and regions that as a result of a lack of human and financial resources cannot afford a diabetes educator.

Original languageEnglish (US)
Pages (from-to)457-465
Number of pages9
JournalTelemedicine and e-Health
Volume12
Issue number4
DOIs
StatePublished - Aug 2006
Externally publishedYes

ASJC Scopus subject areas

  • Health Informatics
  • Health Information Management

Fingerprint

Dive into the research topics of 'Evaluation of a diabetes education call center intervention'. Together they form a unique fingerprint.

Cite this