|
| Simulation-Based Training to Improve Communication and Teamwork and Reduce Medical Errors |
| Monday, May 26, 2008 |
| 3:00 PM–4:20 PM |
| Boulevard A |
| Area: CBM/OBM; Domain: Service Delivery |
| Chair: R. Wayne Fuqua (Western Michigan University) |
| Discussant: Terry E. McSween (Quality Safety Edge) |
| CE Instructor: R. Wayne Fuqua, Ph.D. |
| Abstract: Errors in the delivery of health care services are estimated to account for 90,000 deaths per year in the United States. Many of these deaths are traceable to failures in team coordination and communication among health care workers. Other high risk industries, such as aviation, have greatly reduced error rates through comprehensive simulation-based skill assessment and training programs. We suggest that many of the simulation-based training and quality control strategies developed in aviation can be extrapolated to health care, if, and only if, a number of modifications are made to reflect unique aspects of health care (non-standardized work environments, rotating team composition, poorly delineated roles and chains of command, absence of systematic training in key skills). We describe the preliminary stages of the development of a simulation-based assessment and training system for heath care workers, known as in-situ simulation. The features of this model include the development of scenarios composed of a number of event sets designed to challenge critical health care skills (e.g., problem solving, team coordination, error detection and correction). Simulations are orchestrated in the health care setting in an effort to increase the fidelity of the surrounding environment and to sample the real-world interface between health care workers and support services (e.g., lab and blood services). We describe the development and validation of a taxonomy of health care skills that can be used to evaluate the performance of health care teams. We also describe a facilitated debriefing strategy that is used to promote self- evaluation of critical communication, problem solving and error detection skills by health care workers who have completed an in-situ simulation. |
| |
| Reducing Medical Errors: In Situ Simulation to Assess and Train Team Management Skills in Health Care Settings. |
| R. WAYNE FUQUA (Western Michigan University), William Hamman (Western Michigan University), Jeff Beaubien (Aptima, Inc.), Amy M. Gullickson (Western Michigan University), Rick Lammers (Michigan State University/Kalamazoo Center for Medical Studies ), Beth Seiler (Western Michigan University ) |
| Abstract: Errors in the delivery of health care services are estimated to account for 90,000 deaths per year in the United States. Many of these deaths are traceable to failures in team coordination and communication among health care workers. Other high-risk industries, such as aviation, have greatly reduced error rates through comprehensive simulation-based skill assessment and training programs. We suggest that many of the simulation-based training and quality control strategies developed in aviation can be extrapolated to health care, if, and only if, a number of modifications are made to reflect unique aspects of health care (non-standardized work environments, rotating team composition, poorly delineated roles and chains of command, absence of systematic training in key skills). We describe the preliminary stages of the development of a simulation-based assessment and training system for heath care workers, known as “in-situ simulation.” Thefeatures of this model include the development of scenarios composed of a number of event sets designed to challenge critical health care skills (e.g., problem solving, team coordination, error detection and correction). Simulations are orchestrated in the health care setting in an effort to increase the fidelity of the surrounding environment and to sample the real-world interface between health care workers and support services (e.g., lab and blood services). We describe the development and validation of a taxonomy of health care skills that can be used to evaluate the performance of health care teams. We also describe a facilitated debriefing strategy that is used to promote self-evaluation of critical communication, problem solving and error detection skills by health care workers who have completed an in-situ simulation. |
| |
| Designing Simulation-Based Assessment and Training: Behavioral Principles and Applications. |
| AMY GROSS (Western Michigan University), R. Wayne Fuqua (Western Michigan University) |
| Abstract: Behavior analysis researchers have used a range of simulations including those with low fidelity to those with very high fidelity. In this context, “fidelity” refers to the correspondence between the critical stimulus features of the “real world” situation in which a target behavior occurs and the corresponding features of the simulation. Examples at the lower end of the fidelity continuum include, actor-based role plays used to assess and train social skills, to polymer breast models that approximate the density of human breast tissue and the size and location of embedded lumps used to train breast self-exam skills. Simulations have long been used in behavior analysis research to (a) assess behavior, (b) to train behavior and (c) to identify causal variables for a problem behavior. We then discussed the application of behavior analysis principles to the design of high-fidelity simulations for research, assessment and training purposes. We suggest that the design of high-fidelity simulations can be guided by consideration of contextual, physiological and historical variables that have been identified by learning theory and behavior analysis researchers as important determinants of behavior. We identified and gave examples of a range of variables that should be considered in designing high-fidelity simulations including the stimulus events that define a response opportunity, more distal setting events, historical events, emotional and physiological variables, distracting events that control competing behavior, and the naturalistic and programmed consequences (e.g., reinforcers and punishers) for behavior being sampled in the simulation. We also discussed the range of response dimensions that might be considered in efforts to obtain an accurate assessment of a behavior, including response topography, magnitude, frequency, latency, sequence and duration. We then reviewed factors that influence generalization and maintenance for simulation-based training. Finally, we discussed strategies to assess social validity, or consumer satisfaction with simulation-based assessment and training. |
| |
| Training and Assessing Team Skills: A Review and Synopsis of the Empirical Literature. |
| KRYSTYNA A. ORIZONDO-KOROTKO (Western Michigan University), Amy M. Gullickson (Western Michigan University), R. Wayne Fuqua (Western Michigan University) |
| Abstract: This presentation identified a range of team skills and discussed strategies for the assessment and training of skills that are related to health care safety issues. There are different ways that teams are formed, and in order to determine which team skills are necessary, it is first essential to identify the various models of team organization and functioning. Among the variables that merit consideration are whether teams are intact and stable or fluid, whether teams are organized around a flat vs. hierarchical structure, and finally the extent to which team members have common skills or unique, not overlapping skill sets. Observationof team performance in health care settings reveals that most hospital-based health care teams have a fluid structure (the membership of the team varies across time), with some hierarchical elements (one or more designated or implicit leaders) and specialized skill sets for each team member. Knowing the most common team structure in health care, we were then able to determine what skill sets (called domains) were most relevant to effective team performance. An important prerequisite to implementing any team skill training intervention is developing an adequate assessment procedure, collecting baseline performance data and identifying the team skills that characterize exemplary team performance (and presumably improve the health care outcomes produced by a given team). We then described the manner in which a matrix of team skills was developed, refined and validated for this particular project. Finally, we previewed the three different methods of training team skills that will be tested in this project: (1) information-based, including role clarification; (2) demonstration-based; and (3) practice- and feedback-based. Different tools will also be used during training: classroom instruction, the use of simulations, and the postsimulation debrief. |
|
| |