• John D Piette, Milton O Mendoza-Avelares, Martha Ganser, Muhima Mohamed, Nicolle Marinec, and Sheila Krishnan.
• Ann Arbor VA Healthcare System, University of Michigan, Ann Arbor, MI 48113, USA. jpiette@umich.edu
• Am J Prev Med. 2011 Jun 1; 40 (6): 629632629-32.

BackgroundAlthough interactive voice response (IVR) calls can be an effective tool for chronic disease management, many regions of the world lack the infrastructure to provide these services.PurposeThis study evaluated the feasibility and potential impact of an IVR program using a cloud-computing model to improve diabetes management in Honduras.MethodsA single-group, pre-post study was conducted between June and August 2010. The telecommunications infrastructure was maintained on a U.S. server, and calls were directed to patients' cell phones using VoIP. Eighty-five diabetes patients in Honduras received weekly IVR disease management calls for 6 weeks, with automated follow-up e-mails to clinicians, and voicemail reports to family caregivers. Patients completed interviews at enrollment and a 6-week follow-up. Other measures included patients' glycemic control (HbA1c) and data from the IVR calling system.ResultsA total of 53% of participants completed at least half of their IVR calls and 23% of participants completed 80% or more. Higher baseline blood pressures, greater diabetes burden, greater distance from the clinic, and better medication adherence were related to higher call completion rates. Nearly all participants (98%) reported that because of the program, they improved in aspects of diabetes management such as glycemic control (56%) or foot care (89%). Mean HbA1c's decreased from 10.0% at baseline to 8.9% at follow-up (p<0.01). Most participants (92%) said that if the service were available in their clinic they would use it again.ConclusionsCloud computing is a feasible strategy for providing IVR services globally. IVR self-care support may improve self-care and glycemic control for patients in underdeveloped countries.Published by Elsevier Inc.

23 keywords...

hide…