Automated screening for at-risk drinking in a primary care office using interactive voice response

J Stud Alcohol Drugs. 2010 Sep;71(5):734-8. doi: 10.15288/jsad.2010.71.734.


Objective: Screening for alcohol misuse in primary care settings is strongly recommended but grossly underused. Using interactive voice response (IVR), we developed an automated screening tool (IVR Screen) for identifying alcohol misuse in outpatient primary care offices and evaluated its use rate and acceptability for both patients and providers.

Method: Patients (N = 101) presenting to a primary care clinic for scheduled, nonemergent health care visits called the IVR Screen by using a dedicated telephone in the waiting room and answered five questions about their health. Results were printed immediately for patient and provider to review during the visit. Medical assistants interviewed patients about the IVR Screen in the examination room.

Results: Ninety-six percent of patients who were invited to participate in the study consented to do so. Of those, 26% met criteria for alcohol misuse. Feedback from patients and providers was positive and included constructive suggestions for revisions to the IVR Screen for future use.

Conclusions: IVR-based screening for at-risk drinking was feasible and did not interfere with the provider-patient interaction. The proportion of heavy drinkers identified by the IVR Screen was comparable to that of published reports of screening with written questionnaires. Implications for behavioral health screening, treatment, and clinical research are considerable because IVR-based screening assessments can be customized and targeted to different populations. Results suggest that continued development of IVR as a tool for health and alcohol screening in primary care settings is warranted.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Alcoholism / diagnosis*
  • Alcoholism / psychology
  • Ambulatory Care / methods*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Primary Health Care / methods*
  • Risk Factors
  • Substance Abuse Detection / methods*
  • User-Computer Interface*
  • Voice*