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Cognitive Engineering for Complex Decisionmaking & Problem Solving in Acute Care

Project Final Report (PDF, 366.73 KB) Disclaimer

The use of cognitive engineering systems methodology helps to better understand the interactions of the cognitive and workflow processes of frontline emergency medicine providers by affording new strategies for the design of health information technology (IT) solutions. These strategies not only strive to improve the effectiveness of clinical work in high-intensity medical environments, but also provide a guide to improve health IT implementations in the future.

Project Details -
Completed

Healthcare is a complex, high-risk, sociotechnical work environment. As complexity increases and technology advances, there is an increasing need for “intelligent” design of health information technology (IT) to better support the work of healthcare providers. An improved understanding of how to effectively integrate these systems into the workflow of clinical providers and non-clinical staff is critical to fully utilize health IT’s potential. Future designs for health IT systems must support healthcare providers’ cognitive work, workflow, and decision-making needs, rather than requiring them to adapt their cognitive work and workflow to meet the requirements of the system.

The key to successful use of health IT is presenting the right information at the right time, visualized in a format that facilitates insight into patterns and management strategies that will help the user carry out work effectively and safely. This study applied cognitive systems engineering (CSE) to understand and support complex cognition and work activities in the emergency department (ED). The ED was an ideal setting for this research because it has some of the most challenging conditions for cognitive work—including high risk, time pressure, and uncertainty—and, therefore, provided findings that can be generalized to other complex healthcare environments.

The specific aims of this study were as follows:

  • Perform a cognitive engineering analysis of emergency medicine across diverse healthcare environments, including rural, inner-city, teaching, and community healthcare settings. 
  • Define design guidance and solutions based on identified needs, and develop testable prototypes that integrate these design criteria. 
  • Evaluate prototypes with usability methods and realistic simulated tasks set in a clinical simulation center. 
  • Disseminate results to health IT developers, researchers, and scientists to allow integration of the findings into future designs of technology solutions. 

The research team used a mixed methods approach, including focus groups, interviews, observations, and electronic health record data analysis to develop a deep understanding of the cognitive needs of emergency medicine staff. These findings were used to iteratively develop tools and models based on those needs. The research team not only identified gaps and challenges related to existing health IT but also strategies for improving the methods used for the development and testing before implementation. As such, the results from this research provide solutions to guide future innovations in health IT. The research also produced strategies and prototypes that advanced the understanding of the time-sensitive and high-acuity environment of the ED. These findings and prototype interfaces represent a step forward in using CSE to support the needs of frontline ED providers with a goal of reducing burden and increasing safety.

Designing Intelligent Systems to Support Cognitive Work of Clinical Providers in Emergency Departments

Designing Intelligent Systems to Support Cognitive Work of Clinical Providers in Emergency Departments

The use of cognitive engineering systems methodology helps to better understand the interactions of the cognitive and workflow processes of frontline emergency medicine providers. Its use also can inform the design of health IT solutions to improve effectiveness of clinical work in high-intensity healthcare environments.

Principal Investigator: Hettinger, Aaron Zachary
Organization: MedStar Health Research Institute
Research Profile: Cognitive Engineering for Complex Decisionmaking & Problem Solving in Acute Care
Funded Amount: $2,491,816

Emergency departments are complex environments with a high potential for error

Emergency departments (EDs) in hospitals are complex environments and home to some of the most challenging cognitive work conditions for providers: high risk, time pressure, and uncertainty. These environments always have many people moving around and working within time-sensitive and demanding situations. With multiple physicians, advance practice providers, nurses, and other staff attempting to coordinate and provide appropriate care quickly, there is a greater risk for errors, inefficiencies, and suboptimal workflow.

As complexity increases and technology advances, the value of “intelligent” design of health information technology (IT) to better support the work of emergency medicine (EM) providers is more apparent. An improved understanding of how to effectively integrate systems into the workflow of EM providers and nonclinical staff is critical to fully utilize the potential of technology, while also keeping patients safe. Health IT systems should support providers’ cognitive work, workflow, and decision making needs. In contrast, when providers find themselves adapting their cognitive work and workflow to meet the system’s requirements, mistakes and errors in patient care occur.

I need to be able to quickly assess what's going on at any time. If the cognitive tasks aren't supported by the workflow and the health IT systems, then there's going to either be misses or delays in care because we're spending so much time trying to access information. But if there can be [the necessary well-placed information in a] color-coded dashboard, I can quickly say, ‘These are my three patients that are ready for me to make a decision’ and I can quickly get them discharged home or admitted to the hospital or see them right away. With proper workflow and systems, these tasks can be accomplished in a matter of seconds, instead of [the provider] accessing each individual chart on 30 patients that could take 30 minutes alone. And if [the proper data is] up on the board, I can see whose status is changing without having to dive into each individual chart, which is crucial if you're trying to care for this many patients at the same time.”
–Dr. Hettinger

Understanding cognitive needs of ED providers to improve workflow and health IT systems design

To address these issues, Dr. Aaron (Zach) Hettinger and team from the MedStar Health Research Institute, in association with the University at Buffalo-State University of New York and other collaborators, used cognitive systems engineering (CSE) approaches to understand and support complex cognition and work activities in the ED. They also developed models and solutions to some of the biggest challenges in practicing medicine in this complex environment. They knew the ED could benefit from decision aids, visualizations, and other supportive tools and approached the addition of these tools from the perspective of joint cognitive systems, distributed across people, roles, and time.

The team used a mixed methods approach, including focus groups, interviews, observations, and electronic health record (EHR) data analysis to develop a deep understanding of the cognitive needs of emergency medicine staff, which informed the development of several tools and prototypes. These included a Workload Monitoring Prototype—an embedded workload display tool in the EHR that visually quantifies the individual work associated with a patient while monitoring the distribution of work across providers; a Patient-Centered Display interface, used to incorporate information needs and communication strategies across physicians and nurses to facilitate a holistic view of the patient and communication between these providers; and a Clinical Timeline Chart Review Tool—a timeline-based platform to review the events of an individual’s patient care.

The workload monitoring tool was born out of the standard approach of the triage nurse assigning a patient to alternating teams in the ED, which rotates assigning patients between the teams to be equitable. But this [model] doesn’t take into account how sick patients are. Sometimes the first patient that comes in is really sick. The second patient is not that sick. And then the third patient that comes in is really sick and needs a higher level of resources. And so instead of just assigning the patient based on an alternating pattern, the nurse has to have a sense of what's going on with the teams and their patients, and they might assign the patient to a specific team based on the current workload of each team.”
–Dr. Hettinger

Supporting providers’ needs to reduce burden and increase patient safety

The research team stresses that successful use of health IT is presenting the right information at the right time visualized in a format that facilitates insight into patterns and management strategies; this clearly-presented information will help providers carry out work effectively and safely. This study’s findings and prototype interfaces represent a step forward in using CSE to support the needs of frontline EM providers with a goal of reducing burden and increasing safety. The ED was an ideal setting for this research because it has some of the most challenging conditions for cognitive work—including high risk, time pressure, and uncertainty—and, therefore, provided findings that can be generalized to other complex healthcare environments.