Eliciting patient treatment preferences using a clinical decision support system [abstract 1252-P] Abstract uri icon
Overview
abstract
  • CV Wizard is a web-based EHR-integrated point-of-care clinical decision support (CDS) system that presents personalized cardiovascular (CV) risk information to primary care providers (PCP) and patients in both a low numeracy and high numeracy format. Here we report PCP perspectives on how this CDS system affected shared decision making and patient-centered care. Twenty clinics were randomized to either usual care (UC) or use of the CDS system with diabetes or high reversible cardiovascular risk adults. The CDS system targeted 20% of office visits, and was used at 70-80% of targeted visits over a 2-year period. Consented providers (n=102) were surveyed at baseline and 18 months after implementation. Corrected survey response rates were 90% at baseline and 82% at follow-up. Generalized linear mixed models were used to compare UC and CDS responses to common questions at baseline and follow-up, and CDS users were queried on their perceptions of the CDS system at follow-up only. Compared to UC, PCPs in the CDS group reported increased follow-up rates of CV risk calculations while seeing patients (73% vs. 28%, p=.006), being better prepared to discuss CV risk reduction priorities with patients (98% vs. 78%, p=.03), providing accurate advice on aspirin for primary prevention (75% vs. 48%, p=.02), and more often discussing CV risk reduction (60% vs. 30%, p=.06). PCP users reported that the CDS system improved CV risk factor control (98%), saved time talking to patients about CV risk reduction (93%), efficiently elicited patient treatment preferences (90%), was useful for shared decision making (95%), influenced treatment recommendations (89%),and helped initiate CV risk discussions (94%); 85% of PCPs reported that their patients liked CV Wizard. The CV Wizard CDS system was successfully integrated into the workflow of primary care visits with high sustained use rates, high PCP satisfaction, high patient satisfaction, and positive impacts on shared decision making and patient-centered care.

  • publication date
  • 2016
  • published in
  • Diabetes  Journal
  • Research
    keywords
  • Cardiovascular Diseases
  • Clinical Decision Support Systems
  • Decision Making
  • Diabetes
  • Economics
  • Patient Satisfaction
  • Randomized Controlled Trials=
  • Additional Document Info
    volume
  • 65
  • issue
  • Suppl 1