Document Type
Article
Publication Date
11-27-2019
Abstract
Background: According to the September 2015 Institute of Medicine report, Improving Diagnosis in Health Care, each of us is likely to experience one diagnostic error in our lifetime, often with devastating consequences. Traditionally, diagnostic decision making has been the sole responsibility of an individual clinician. However, diagnosis involves an interaction among interprofessional team members with different training, skills, cultures, knowledge, and backgrounds. Moreover, diagnostic error is prevalent in the interruption-prone environment, such as the emergency department, where the loss of information may hinder a correct diagnosis.
Objective: The overall purpose of this protocol is to improve team-based diagnostic decision making by focusing on data analytics and informatics tools that improve collective information management.
Methods: To achieve this goal, we will identify the factors contributing to failures in team-based diagnostic decision making (aim 1), understand the barriers of using current health information technology tools for team collaboration (aim 2), and develop and evaluate a collaborative decision-making prototype that can improve team-based diagnostic decision making (aim 3).
Results: Between 2019 to 2020, we are collecting data for this study. The results are anticipated to be published between 2020 and 2021.
Conclusions: The results from this study can shed light on improving diagnostic decision making by incorporating diagnostics rationale from team members. We believe a positive direction to move forward in solving diagnostic errors is by incorporating all team members, and using informatics.
Recommended Citation
Roosan D, Law AV, Karim M, Roosan M. Improving team-based decision making using data analytics and informatics: Protocol for a collaborative decision support design. JMIR Res Protoc. 2019;8(11):e16047. https://doi.org/10.2196/16047
Copyright
The authors
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Comments
This article was originally published in JMIR Research Protocols, volume 8, issue 11, in 2019. https://doi.org/10.2196/16047