Cognitive Engineering for Complex Decision-Making and Problem-Solving in Acute Care | MedStar Health

Cognitive Engineering for Complex Decision-Making and Problem-Solving in Acute Care

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Health information systems are rapidly being implemented in a variety of healthcare contexts, including Emergency Departments (EDs). These systems offer promising solutions to challenges related to cost, efficiency, patient safety, and medical errors.


New technologies are often designed with only a limited understanding of the nature of cognition, tasks, and workflow in the setting in which they will be used. Without a careful understanding of how new technologies will be used in practice, unanticipated or undesirable consequences can arise. From increased workload to “workarounds,” patient and provider safety can be compromised if systems and tasks are bypassed, abandoned, or interrupted.


To address these deficits, MedStar Health National Center for Human Factors in Healthcare and MedStar Emergency Physicians recognized an opportunity to leverage their partnership—one of the few existing collaborations between human factors scientists, informaticians, and clinicians. They partnered with the University at Buffalo’s Department of Industrial Engineering to use cognitive systems engineering (CSE) methods to design and test prototype ED information systems. Together, they worked to understand how new technologies will be used in practice, the cognitive work technologies support, and how technologies’ design can be optimized for this support. While there have been applications of cognitive engineering to medical environments, none have provided a comprehensive understanding of the nature of cognitive clinical work and activities across an acute care environment. The research supported by this partnership has continued to grow and has received R01 grant funding since 2014 (R01HS022542; Fairbanks/Hettinger).


Our goal is to provide a fundamental and comprehensive picture of the difficult sensemaking, decision-making, and planning/replanning tasks in the ED, along with the individual and team expertise required to meet those challenges.

The research uses the ED as a "field laboratory" for two reasons. First, the ED is home to some of the most challenging conditions for cognitive work—high risk, time pressure, and uncertainty—and therefore provides a strong opportunity to generalize findings to other complex healthcare environments. Second, the ED can clearly benefit from the decision aids, visualizations, and other supportive technologies that can result from cognitive engineering analyses.

Additionally, the research will develop and evaluate exemplar solutions for a targeted set of needs that will be identified through the cognitive engineering analysis, thus providing a methodological example and "proof-of-concept" for translating cognitive engineering analyses into designs.


Three main prototypes have been iteratively developed and evaluated leveraging usability methods.

Workload Display: Embedded in the electronic health record (EHR), this tool visually quantifies the individual work associated with given patients while monitoring the distribution of work across clinicians in real-time. Key display features include patients represented by a bar with a length relative to the workload of the given patient and color-coded by their current phase of care, as well as the ability for staff to assess workload at a glance and decide which provider has the capacity to take on more patients. The tool and algorithm have undergone usability and usefulness analysis and the algorithm has been continually refined for improved accuracy until completion of the research grant. Research findings demonstrate the feasibility of incorporating design prototypes into the EHR using real-time, dynamic patient data, and utilizing such prototypes for in situ studies. This can potentially aid in the management of clinician workload by supporting the decision of assigning new patients.
Patient-Centered Display: Issues have arisen from the transition from manual to electronic patient status boards. The patient information display, which includes distinct sections of information, was developed to improve information accessibility for nurses and physicians. Feedback from the usability evaluation has been shared with existing EHR vendors to improve health IT design in the ED on a broader scale.
Clinical Event Timeliner: This tool, also embedded in the EHR, can be used in real-time and aggregates all of a patient’s clinical events (labs, imaging, medications, and documentation) into a timeline-based view in order to improve the post-encounter event review process. Users of this tool can identify relationships between data elements based on the time of order and time of result. It is currently being used by MedStar Health safety and clinical personnel to perform chart reviews and day-to-day clinical tasks with the goal to roll it out systemwide.

July 2021 Update

Funding for this grant concluded as of September 29, 2020. The research team’s final manuscripts summarizing the last phases of this research are currently under review with peer-reviewed journals. The descriptions provided for the prototypes listed above have been updated to reflect progress since this case study was first written as well. The AHRQ Project Final Report (available here) summarizes the work, publications, and products funded by this research grant in more detail. The health IT vendor community, healthcare organizations, emergency medicine frontline staff, and healthcare researchers can all benefit from these findings.


We would like to thank our internal research team, MedStar Health collaborators, and partners from the Department of Industrial Engineering at the University at Buffalo State University of New York, Roth Cognitive Engineering, and Department of Emergency Medicine at the University of Florida for their support, dedication, and teamwork in completing this research in an exemplary fashion.

Key team members include: Aaron (Zach) Hettinger (Principal Investigator), Rollin (Terry) Fairbanks, Ann Bisantz, Emilie Roth, Shawna Perry, Robert Wears, Tracy Kim, Joseph Blumenthal, Sonita Bennett, Shrey Mathur, Xiaomei Wang, Sudeep Hegde, Daniel Hoffman, Natalie Benda, Rebecca Berg, David LaVergne, Lindsey Clarke, Nicolette McGeorge, and Jessica Arora.


Key Publications:
Additional Publications and Presentations:

Please note: Images on this page contain fictitious patient data or are otherwise altered for confidentiality.

The overview above reflects work completed while the MedStar Health National Center for Human Factors in Healthcare was part of the MedStar Institute for Innovation. In July 2020, the Human Factors Center transitioned to its new organizational home, MedStar Health Research Institute, and still remains a key collaborator of MI2. Visit the Human Factors Center website for the latest information on its work.


Cognitive systems engineering methods can be used to design Emergency Department information systems.


MedStar Health National Center for Human Factors in Healthcare



Page last updated: 7/1/21
Page first published: 10/9/19