Abstract
Background: Clinical decision aids may support shared decision-making for screening mammography. To inform shared decision-making between patients and their providers, this study examines how patterns of using an EHR-integrated decision aid and accompanying verbal patient-provider communication predict decision-making satisfaction. Methods: For 51 patient visits during which a mammography decision aid was used, linguistic characteristics of patient-provider verbal communication were extracted from transcribed audio recordings and system logs automatically captured uses of the decision aid. Surveys assessed patients’ post-visit decisional satisfaction and its subcomponents. Linear mixed effects models assessed how patients’ satisfaction with decision making was related to patterns of verbal communication and navigation of the decision aid. Results: The results indicate that providers’ use of quantitative language during the encounter was positively associated with patients’ overall satisfaction, feeling informed, and values clarity. Patients’ question-asking was negatively associated with overall satisfaction, values clarity, and certainty perception. Where system use data indicated the dyad had cycled through the decision-making process more than once (“looping” back through pages of the decision aid), patients reported improved satisfaction with shared decision making and all subcomponents. Overall satisfaction, perceived support, certainty, and perceived effectiveness of decision-making were lowest when a high number of navigating clicks occurred absent “looping.” Conclusions: Linguistic features of patient-provider communication and system use data of a decision aid predict patients’ satisfaction with shared decision making. Our findings have implications for the design of decision aid tools and clinician training to support more effective shared decision-making for screening mammography.
| Original language | English (US) |
|---|---|
| Article number | 323 |
| Journal | BMC Medical Informatics and Decision Making |
| Volume | 22 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 2022 |
Funding
This work was supported by the Community-Academic Partnerships core of the University of Wisconsin Institute for Clinical and Translational Research (UW ICTR) (to EB), grant 9 U54 TR000021 from the National Center for Advancing Translational Sciences (to EB), the National Institutes of Health, National Cancer Institute, grant K24 CA194251 (to EB and DS), the University of Wisconsin Carbone Cancer Center, support grant P30 CA014520 (to EB and DS), the Ministry of Education of the People’s Republic of China, grant 19YJC860029 (to YL), Shanghai Pujiang Program 2020PJC056 (to YL). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or other funders.
Keywords
- Breast cancer screening
- Clinical decision support tool
- Computational text analysis
- Decisional satisfaction
- Shared decision-making
ASJC Scopus subject areas
- Health Policy
- Health Informatics
- Computer Science Applications
