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Project Details - Ended
- Grant Number:R36 HS023349
- Funding Mechanism:
- AHRQ Funded Amount:$21,160
- Principal Investigator:
- Organization:
- Location:
- Project Dates:7/1/2014 to 8/31/2015
Project Categories
- Technology:
- Care Setting:
- Medical Condition:
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Summary:
Clinical Decision Support Systems (CDSS) has been shown to improve the quality, safety, and value of health care. However, most of the studies demonstrating the benefits of CDSS were conducted in health care organizations that built their own electronic health record (EHR) systems and advanced CDSS capabilities. Conversely, typical commercial EHR systems have only basic CDSS, such as drug-drug interaction alerts and preventive reminders. This kind of decision support fails to account for factors that complicate decisionmaking tasks, resulting in widely reported issues such as alert fatigue and lack of usage uptake. Despite substantial prior research on task complexity in other domains that has shown the potential to improve the quality of decisionmaking by incorporating decision task complexity in the system design, less is known about complexity in the context of clinical decisionmaking.
The purpose of this study is to improve the understanding of complexity in clinical decision tasks, including decisionmaking patterns and the factors that contribute to decision task complexity. A theoretical framework of task complexity developed in other successful fields will guide the research. The framework conceptualizes task complexity into 10 dimensions including size, ambiguity, novelty, temporal demand, and action complexity.
The specific aims of the project are to:
- Characterize leverage points of complex clinical decision tasks.
- Identify factors that contribute to complex decision tasks.
- Design and evaluate a prototypical CDSS that supports high-level reasoning for decision tasks.
The team aims to contribute new findings to existing research through the application of a complex-decisionmaking framework in the health care domain; a more comprehensive understanding of factors that contribute to the complexity of decision tasks and how complexity factors evolve over time with case progression and the impact on decision tasks; and an improved understanding of clinicians’ information needs when facing complex decision. Through the study of these areas, the project team anticipates gaining an enhanced understanding of task complexity in clinical decisions that will improve the design of future innovative CDSS interventions.
