Impact and Feasibility of Personalized Decision Support for Older Patients with Diabetes: A Pilot Randomized Trial. (July 2017)

• Record Type: Journal Article
• Authors: Huang, Elbert S.; Nathan, Aviva G.; Cooper, Jennifer M.; Lee, Sang Mee; Shin, Na; John, Priya M.; Dale, William; Col, Nananda F.; Meltzer, David O.; Chin, Marshall H.
• Is Part Of: Medical decision making. Volume 37:Number 5(2017)
• Page Start: 611
• Page End: 617
• Publication Date: 2017-07
• Subjects: type 2 diabetes -- aging -- personalized medicine -- decision aids -- decision support -- chronic disease modeling -- randomized trial; Medical policy -- Periodicals; Clinical medicine -- Decision making -- Periodicals; Medicine -- Periodicals; Médecine clinique -- Prise de décision -- Périodiques; 362.1
• DOI: 10.1177/0272989X16654142
• Languages: English
• ISSNs: 0272-989X

Abstract

Background. Diabetes guidelines recommend individualizing glycemic goals (A1C) for older patients. The aim of this study was to assess a personalized Web-based decision support tool.Methods. We randomized physicians and their patients with type 2 diabetes (≥65 years of age) to a support tool or educational pamphlet (75:25 patients). Prior to a visit, intervention patients interacted with the tool, which provided personalized risk predictions and elicited treatment preferences. Main outcomes included 1) patient-doctor communication, 2) decisional conflict, 3) changes in goals, and 4) intervention acceptability.Results. We did not find significant differences in proportions of patients who had an A1C discussion (91% intervention v. 76% control; P = 0.19). Intervention patients had larger declines in the informed subscale of decisional conflict (–20 v. 0, respectively; P = 0.04). There were no significant differences in proportions of patients with changes in goals (49% v. 28%, respectively; P = 0.08). Most intervention patients reported that the tool was easy to use (91%) and helped them to communicate (84%). A limitation was that this was a pilot trial at one academic institution.Conclusions. Web-based decision support tools may be a practical approach to facilitating the personalization of goals for chronic conditions. Trial registration: NCT02169999 (https://clinicaltrials.gov/show/NCT02169999 ).