Project Details - Ongoing
- Grant Number:R01 HS023708
- Funding Mechanism:
- AHRQ Funded Amount:$980,821
- Principal Investigator:
- Project Dates:7/1/2015 to 4/30/2020
- Health Care Theme:
Optimal design of electronic health records (EHRs) has proven difficult because of the complexity and high-stakes collaborative nature of health care. A 2011 report from the Institute of Medicine identified design limitations of human-computer interaction (HCI) pose a risk to patient safety. One limitation, fragmented displays, occurs when information that should be viewed together is located on different screens requiring providers to mentally integrate the information. Another is lack of fit to task. Providers’ information needs vary widely by specialty and individual patient and can change during the course of diagnosis and treatment. Current systems design may not adequately fit all tasks that the clinician needs to perform. Additionally, current interface designs may not provide cognitive support for clinical reasoning. These system limitations impose high cognitive load, or high mental effort, which itself is a threat to safety and can contribute to errors.
This project will build knowledge about how providers’ interactions and cognition are affected by system design and determine how design can be improved to ensure safe systems. It will also clarify the differing information needs and interaction requirements for medical specialties and clinical roles. The resulting information will be used to develop system specifications and design patterns to improve EHRs.
The specific aims of the project are as follows:
- Understand the effect of the fragmentation problem on cognitive load and its effect on provider performance in locating, understanding, and using information in EHRs in typical tasks.
- Understand provider information needs and use patterns in a variety of specialties and clinical roles as well as information transfer among these clinicians.
- Understand approaches to clinical reasoning and errors in high-stress scenarios with multiple patients and nonlinear workflow.
The study team will use a mixed method approach that incorporates established methods such as usability testing, think-aloud protocols, and novel methods, including pupillometry, to assess cognitive load during EHR use. Additionally, a novel system that allows rapid prototyping and testing of new configurations will be used to conduct controlled experiments of conventional and new approaches to system design.