Ayse P. Gurses, Ph.D. - US grants

? DESCRIPTION (provided by applicant): Ensuring safety and quality of care as well as improving patient and family experiences have been strong drivers for health information technology (HIT) deployment. When designed and implemented well, HIT can revolutionize and improve the way clinicians and families work together. However, currently available HIT applications have made healthcare more fragmented, making it harder to coordinate care among various care team members and families; thus introducing new risks to patient safety. Our long-term goal is to develop innovative and effective concepts and techniques for the next generation of HIT-supported work systems that provide integrated, seamless, safe, and patient and family-centered care based on scientific evidence. Trauma is the leading cause of death and permanent paralysis among the pediatric population. Care transitions of critically ill patients such as trauma patients, to and from the pediatric intensive care unit (PICU) require effective teamwork among the PICU team, other teams and services (e.g., emergency department), as well as the family members. We propose to use a sociotechnical systems approach to the design of HIT that supports pediatric trauma care transitions. We will use the SEIPS 2.0, a sociotechnical systems model for healthcare, complemented by the well-known team processes framework, to ensure that our HIT design supports the cognitive work of the various trauma care team members and families. Nested within the SEIPS 2.0, we will use contextual design methodology, a six-step user-centered design process, to guide our overall design process. Our first specific aim is to describe cognitive teamwork involved in care transitions of pediatric trauma patients. We will focus on three types of care transitions: admission to PICU from emergency department, transfer from PICU to inpatient pediatric general care unit, and hospital discharge directly from PICU. The second specific aim is to develop and test design requirements for future HIT, referred to as the team-centric information technology (TACIT), that supports cognitive teamwork for enhancing safety, quality, and family-centeredness of care. The study will be conducted in three Level I pediatric trauma centers: Johns Hopkins Children's Hospital, UWHealth-American Family Children's Hospital, and the All Children's Hospital. Methods for analyzing cognitive teamwork will be diverse (i.e. contextual inquiry, interviews, focus groups) (Aim 1) and will produce a range of outputs (e.g., process maps, information flow diagrams, artifact analysis, collaboration tables, decision wheels, role network analysis) that wil be used to define the TACIT design requirements (Aim 2). Using a collaborative process among researchers and the various other stakeholders, we will develop preliminary design requirements for the TACIT mock-up and evaluate its usability. This study uses an iterative design approach; Aim 2 results will help to define additional data collection and analysis needs under Aim 1. When all Aim 1 data have been collected and analyzed, the TACIT design requirements will be finalized (Aim 2).

Diagnostic errors are common, deadly, and costly. Twelve million Americans annually experience diagnostic error in ambulatory care, including in Emergency Department (EDs), over half of these with potential for harm. ED clinical practice is especially prone to diagnostic error as a sociotechnical work system that is fast-paced, high-stakes, highly adaptive and complex. The 2016 National Academy of Medicine (NAM) report was an urgent call for more research regarding diagnostic safety, making particular reference to the ED. ED diagnosis is cognitively-intense work, distributed across team members who may or may not be co-located. There is very limited understanding of the salient `real-time' details of the ED diagnostic process and associated performance shaping factors on the work system. Without structured in-depth analysis of ED diagnosis occurring as part of `real-time ED work,' that is ?work-as-done,? we will continue the struggle with the design of effective, sustainable interventions to improve diagnostic safety. Accordingly, we are proposing a 3-year, multi- site, multi-method field study in the ED based on a sociotechnical systems approach and a macrocognition framework, which is the study of cognitive tasks that characterize how people think in natural settings. We have 3 specific aims: (1) AIM 1. To understand provider (physician and advanced practice provider) work involved in ED diagnosis and identify associated performance shaping factors. (2) AIM 2. To understand collaborative (team-oriented) work involved in ED diagnosis and identify associated performance shaping factors. (3) AIM 3. To conduct a proactive risk assessment of the diagnostic process in the ED. AIM 1 and AIM 2 will be achieved by conducting in-depth qualitative studies using a variety of data collection methods (observations, interviews) and cognitive task analyses techniques. Data analysis will produce a range of outputs such as process maps, macrocognitive and procedural tasks involved in diagnosis, information flow diagrams, role network graphs, among others. AIM 3 will use two complementary proactive risk assessment methods to assess failure modes and performance shaping factors and to identify possible interventions to improve ED diagnostic safety: (1) Health Care Failure Mode and Effect Analysis (HFMEA); (2) Functional Resonance Analysis Method (FRAM) Based ?What-if? Risk Analysis. Additionally, we will develop a research methods compendium/guide for those interested in conducting similar research on diagnostic safety. The study will be conducted in 3 different EDs (urban, suburban, rural) that serve patients from 6 AHRQ priority population groups. The research team is interdisciplinary, composed of internationally known experts in patient safety, human factors, systems engineering, cognitive psychology, communication, emergency medicine, and nursing. The study is innovative due to its lens on ED diagnostic process as a whole, its use of human factors- based conceptual approaches, its investigation of the ED team's role in the diagnosis, and its use of a variety of cognitive task analysis techniques and proactive risk assessment methods.