Emergency Departments (ED) in hospitals are high workload, information intensive, time sensitive, interruption- laden, multitasking, error-prone, and life-critical environments. Managing information needs and supporting clinical decision making is of great consequence for patient safety and healthcare quality. The broad, long- term objective of our project is to study information management and decision making in the ED and develop interventions to reduce cognitive burden, improve communication, and reduce error. In the proposed project, we will focus on opportunistic decision making, which is an unplanned switching in the middle of a task or across multiple tasks. In high risk settings such as the ED, i can lead to suboptimal performance and medical errors. This project targets Area 1 (clinical work) and Area 3 (visualization) in the Program Announcement.
Aim 1 : Develop and validate the Work Domain Ontology (WDO) of the emergency department (ED). The WDO composed of clinical goals, information objects, and clinical operations required for the care of patients, provides an implementation-independent description of the work domain. It is also information needs analysis as well as a coding system for data collection. A validated WDO composed of clinical goals, information objects, and clinical operations in the ED will be implemented in an ontology development tool.
Aim 2 : Identify the information needs and understand the mechanisms and impacts of opportunistic decision making in the ED. We will conduct an extensive empirical study to explore the mechanisms of decision making for task transitions, the associated information needs, and information seeking behaviors, and assess the impact of decision making on care delivery. An integrated set of data from ethnographic studies, records from EHR, and human movement patterns from Radio ID Tags will be generated, and patterns, mechanisms, outcomes of opportunistic decision making will be analyzed.
Aim 3 : Develop visualizations for increasing situation awareness and supporting decision making. Visualizations designed from human-centered principles can provide better situation awareness of the ED at various levels (e.g., patient-centered, provider-centered, and department-centered). Utilizing the information needs identified in Aim 2, we will develop a 3-level visualization system that matches the corresponding operations in the WDO to support better decision making. ? Aim 4: Evaluate the impact of the visualizations as cognitive interventions. Visualizations are based on pattern recognition, parallel processing, and external memory. They support better detection, interpretation, understanding, and evaluation of information for decision making.
This aim will evaluate the impacts of the visualization tools on individual performance, team communication, and a set of clinical outcome measures important to patient safety and care quality. Comprehensive comparisons between outcomes with interventions (Aim 3) and without interventions (Aim 2) will be generated.

Public Health Relevance

Emergency Departments (ED) in hospitals are high workload, information intensive, time sensitive, interruption-laden, error-prone, and life-critical environments. Managing information needs and supporting clinical decision making is of paramount importance for patient safety and healthcare quality. Our project will study information management and decision making in the ED and develop cognitive interventions to reduce cognitive burden, improve communication, and reduce error.

Agency
National Institute of Health (NIH)
Institute
Agency for Healthcare Research and Quality (AHRQ)
Type
Research Project (R01)
Project #
5R01HS021236-03
Application #
8735080
Study Section
Health Care Technology and Decision Science (HTDS)
Program Officer
Zayas-Caban, Teresa
Project Start
2012-09-30
Project End
2016-07-31
Budget Start
2014-08-01
Budget End
2015-07-31
Support Year
3
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of Texas Health Science Center Houston
Department
Type
Schools of Allied Health Profes
DUNS #
800771594
City
Houston
State
TX
Country
United States
Zip Code
77225
Nguyen, Vickie; Okafor, Nnaemeka; Zhang, Jiajie et al. (2014) Using TURF to understand the functions of interruptions. AMIA Annu Symp Proc 2014:917-23