Developing an automated speech-recognition telephone diabetes intervention

Int J Qual Health Care. 2008 Aug;20(4):264-70. doi: 10.1093/intqhc/mzn021. Epub 2008 May 20.


Objective: Many patients do not receive guideline-recommended care for diabetes and other chronic conditions. Automated speech-recognition telephone outreach to supplement in-person physician-patient communication may enhance patient care for chronic illness. We conducted this study to inform the development of an automated telephone outreach intervention for improving diabetes care among members of a large, not-for-profit health plan.

Design: In-depth telephone interviews with qualitative analysis.

Setting: participants Individuals with diabetes (n=36) enrolled in a large regional health plan in the USA. Main outcome measure Patients' opinions about automated speech-recognition telephone technology.

Results: Patients who were recently diagnosed with diabetes and some with diabetes for a decade or more expressed basic informational needs. While most would prefer to speak with a live person rather than a computer-recorded voice, many felt that the automated system could successfully supplement the information they receive from their physicians and could serve as an integral part of their care. Patients suggested that such a system could provide specific dietary advice, information about diabetes and its self-care, a call-in menu of information topics, reminders about laboratory test results and appointments, tracking of personal laboratory results and feedback about their self-monitoring.

Conclusions: While some patients expressed negative attitudes toward automated speech recognition telephone systems generally, most felt that a variety of functions of such a system could be beneficial to their diabetes care. In-depth interviews resulted in substantive input from health plan members for the design of an automated telephone outreach system to supplement in-person physician-patient communication in this population.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Automation
  • Diabetes Mellitus / therapy*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Patient Education as Topic / methods*
  • Patient Satisfaction
  • Remote Consultation / methods*
  • Self Care / methods
  • Speech
  • Telephone*
  • User-Computer Interface*
  • Young Adult