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Simulation-based clinical systems testing for healthcare spaces: from intake through implementation.

ABSTRACT: Healthcare systems are urged to build facilities that support safe and efficient delivery of care. Literature demonstrates that the built environment impacts patient safety. Design decisions made early in the planning process may introduce flaws into the system, known as latent safety threats (LSTs). Simulation-based clinical systems testing (SbCST) has successfully been incorporated in the post-construction evaluation process in order to identify LSTs prior to patient exposure and promote preparedness, easing the transition into newly built facilities. As the application of simulation in healthcare extends into the realm of process and systems testing, there is a need for a standardized approach by which to conduct SbCST in order to effectively evaluate newly built healthcare facilities. This paper describes a systemic approach by which to conduct SbCST and provides documentation and evaluation tools in order to develop, implement, and evaluate a newly built environment to identify LSTs and system inefficiencies prior to patient exposure.

SUBMITTER: Colman N

PROVIDER: S-EPMC6676572 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Simulation-based clinical systems testing for healthcare spaces: from intake through implementation.

Colman Nora N Doughty Cara C Arnold Jennifer J Stone Kimberly K Reid Jennifer J Dalpiaz Ashley A Hebbar Kiran B KB

Advances in simulation (London, England) 20190802

Healthcare systems are urged to build facilities that support safe and efficient delivery of care. Literature demonstrates that the built environment impacts patient safety. Design decisions made early in the planning process may introduce flaws into the system, known as latent safety threats (LSTs). Simulation-based clinical systems testing (SbCST) has successfully been incorporated in the post-construction evaluation process in order to identify LSTs prior to patient exposure and promote prepa ...[more]

PMID: 31388455

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Project description:BackgroundClinical alarm system safety is a national patient safety goal in the United States. Physiologic monitors are associated with the highest number of device alarms and alarm-related deaths. However, research involving nurses' use of physiologic monitors is rare. Hence, the identification of critical usability issues for monitors, especially those related to patient safety, is a nursing imperative.ObjectiveThis study examined nurses' usability of physiologic monitors in intensive care units with respect to the effectiveness and efficiency of monitor use.MethodsIn total, 30 nurses from 4 adult intensive care units completed 40 tasks in a simulation environment. The tasks were common monitoring tasks that were crucial for appropriate monitoring and safe alarm management across four categories of competencies: admitting, transferring, and discharging patients using the monitors (7 tasks); managing measurements and monitor settings (23 tasks); performing electrocardiogram (ECG) analysis (7 tasks); and troubleshooting alarm conditions (3 tasks). The nurse-monitor interaction was video-recorded. The principal investigator and two expert intensive care units nurse educators identified, classified, and validated task success (effectiveness) and the time of task completion (efficiency).ResultsAmong the 40 tasks, only 2 (5%) were successfully completed by all the nurses. At least 1-27 (3%-90%) nurses abandoned or did not correctly perform 38 tasks. The task with the shortest completion time was "take monitor out of standby" (mean 0:02, SD 0:01 min:s), whereas the task "record a 25 mm/s ECG strip of any of the ECG leads" had the longest completion time (mean 1:14, SD 0:32 min:s). The total time to complete 37 navigation-related tasks ranged from a minimum of 3 min 57 s to a maximum of 32 min 42 s. Regression analysis showed that it took 6 s per click or step to successfully complete a task. To understand the nurses' thought processes during monitor navigation, the authors analyzed the paths of the 2 tasks with the lowest successful completion rates, where only 13% (4/30) of the nurses correctly completed these 2 tasks. Although 30% (9/30) of the nurses accessed the correct screen first for task 1 and task 2, they could not find their way easily from there to successfully complete the 2 tasks.ConclusionsUsability testing of physiologic monitors revealed major ineffectiveness and inefficiencies in the current nurse-monitor interactions. The results indicate the potential for safety and productivity issues in completing routine tasks. Training on monitor use should include critical monitoring functions that are necessary for safe, effective, efficient, and appropriate monitoring to include knowledge of the shortest navigation path. It is imperative that vendors' future monitor designs mimic clinicians' thought processes for successful, safe, and efficient monitor navigation.

Project description:Implementation is a crucial component for the success of interventions in health service systems, as failure to implement well can have detrimental impacts on the effectiveness of evidence-based practices. Therefore, evaluations conducted in real-world contexts should consider how interventions are implemented and sustained. However, the complexity of healthcare environments poses considerable challenges to the evaluation of interventions and the impact of implementation efforts on the effectiveness of evidence-based practices. In consequence, implementation and intervention effectiveness are often assessed separately in health services research, which prevents the direct investigation of the relationships of implementation components and effectiveness of the intervention. This article describes multilevel decision juncture models based on advances in implementation research and causal inference to study implementation in health service systems. The multilevel decision juncture model is a theory-driven systems approach that integrates structural causal models with frameworks for implementation. This integration enables investigation of interventions and their implementation within a single model that considers the causal links between levels of the system. Using a hypothetical youth mental health intervention inspired by published studies from the health service research and implementation literature, we demonstrate that such theory-based systems models enable investigations of the causal pathways between the implementation outcomes as well as their links to patient outcomes. Results from Monte Carlo simulations also highlight the benefits of structural causal models for covariate selection as consistent estimation requires only the inclusion of a minimal set of covariates. Such models are applicable to real-world context using different study designs, including longitudinal analyses which facilitates the investigation of sustainment of interventions.

Dataset Information

Simulation-based clinical systems testing for healthcare spaces: from intake through implementation.

Publications

Simulation-based clinical systems testing for healthcare spaces: from intake through implementation.

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