Presentation
PS8 - Hierarchical and Cognitive Task Analysis for Delivery Room Resuscitations of Neonates with Congenital Anomalies
DescriptionBackground
Congenital anomalies are the second leading cause of neonatal death in the United States after prematurity, yet neonates with congenital anomalies are an understudied population, especially in the delivery room. Newborns with congenital anomalies are a unique population that add complexity to the usual transition of most newborns from in utero to ex utero life. Given this, multidisciplinary interprofessional teams and specific resuscitation interventions are needed to ensure optimal patient care. The Children’s Hospital of Philadelphia (CHOP) has a delivery room, the Special Delivery Unit (SDU), dedicated solely to the resuscitation of neonates with congenital anomalies. The SDU is the largest unit of its kind, performing more than 500 resuscitations per year. Within such a complex environment, it is paramount to understand all the roles and responsibilities, as well as the interactions that occur between team members, and the way information flows. Task analyses enable an in-depth understanding of all system elements and interactions within a complex system. Task analyses can be divided into several types, including hierarchical and cognitive. A hierarchical task analysis (HTA) breaks down each different task into subtasks, whereas a cognitive task analysis (CTA) examines the thought process of the person performing the task. HTA enables the understanding of the tasks necessary to accomplish a specific goal, providing a detailed breakdown of the tasks, subtasks, and order in which these tasks must be performed. CTA instead focuses on assessment and decision making.
The purpose of this project was to describe all tasks necessary for resuscitation of neonates with congenital anomalies, illuminating the complexity of these resuscitations and highlighting areas of variability. To complete the task analysis, we utilized several diverse sources including the Neonatal Resuscitation Program (NRP) algorithm for neonatal resuscitation, locally followed optimal care guidelines for the SDU, live and video recorded delivery room observations, and interviews with subject matter experts and SDU providers. The combination of all these data sources provides a novel approach to creating and developing task analyses.
The project began as an HTA, but the complexity of the tasks necessitated a combined HTA-CTA to understand decision points where patient assessment dictated task choice and performance. Incorporating the CTA into the HTA also allows insight into which tasks may present higher workload levels.
As an initial step, we developed an HTA-CTA of the NRP algorithm. We then focused on developing an HTA-CTA for the SDU. To ensure capture of the complexity of the system and the environment, initial task analysis data collection began through direct in person observations of delivery room resuscitations in the SDU. These observations were augmented through asking providers clarifying questions as the resuscitation allowed. The next step focused on video review of delivery room resuscitations which enabled in-depth review of specific tasks. For specific tasks, especially those involving preparation of equipment and medications, subject matter experts from the respiratory and nursing departments were interviewed.. A neonatologist with expertise in neonatal resuscitation and human factors provided oversight to the developing models. The current task analysis consists of 19 tasks, and over 262 subtasks.
Future work will analyze the variability within specific tasks and will explore how this may be related to different congenital anomalies Additionally, the variability within the steps will be investigated to propose human factors quality improvement projects to standardize and improve team performance and patient care. Video review and timestamps will be used to measure variability both qualitatively and quantitatively.
The task analysis is part of a larger body of work performing a work system analysis (WSA) within the SDU. Future work will incorporate the Systems Engineering Initiative for Patient Safety (SEIPS) to better understand the interactions and emerging properties that occur between the providers and other systems elements such as technology, task, or the environment.
Application
The combined HTA and CTA can be used within complex settings, such as healthcare, to gain better understanding of task and cognitive load, w and to delineate which roles are responsible for assessment and decision making. This work demonstrates how multiple data sources, including subject-matter expert interviews, observations, video review, and algorithms, can be used to developed robust system models, not just in healthcare, but in other industries as well.
The resulting task analysis has several potential applications, including assessing situation awareness and interruptions, flow disruptions, and to optimize workflows. From a systems perspective, the task analysis can also be used to compare the “work as done” vs “work as imagined,” where the tasks are reviewed by subject matter experts and then compared against real life scenarios.
Understanding all the tasks, the roles involved, and the interactions can produce a systems view that outlines emergent properties of the system. Thus, the task analysis could also be used as a proactive safety tool by identifying potential failure modes and corrective actions to reduce safety concerns.
Overview of Presentation
This poster will describe the integration of a hierarchical task analysis and a cognitive task analysis into a single task analysis and describe its application to a novel environment, a delivery room dedicated to neonates with congenital anomalies. Furthermore, the posted will demonstrate how diverse data sources can be combined to create a robust task analysis.
Congenital anomalies are the second leading cause of neonatal death in the United States after prematurity, yet neonates with congenital anomalies are an understudied population, especially in the delivery room. Newborns with congenital anomalies are a unique population that add complexity to the usual transition of most newborns from in utero to ex utero life. Given this, multidisciplinary interprofessional teams and specific resuscitation interventions are needed to ensure optimal patient care. The Children’s Hospital of Philadelphia (CHOP) has a delivery room, the Special Delivery Unit (SDU), dedicated solely to the resuscitation of neonates with congenital anomalies. The SDU is the largest unit of its kind, performing more than 500 resuscitations per year. Within such a complex environment, it is paramount to understand all the roles and responsibilities, as well as the interactions that occur between team members, and the way information flows. Task analyses enable an in-depth understanding of all system elements and interactions within a complex system. Task analyses can be divided into several types, including hierarchical and cognitive. A hierarchical task analysis (HTA) breaks down each different task into subtasks, whereas a cognitive task analysis (CTA) examines the thought process of the person performing the task. HTA enables the understanding of the tasks necessary to accomplish a specific goal, providing a detailed breakdown of the tasks, subtasks, and order in which these tasks must be performed. CTA instead focuses on assessment and decision making.
The purpose of this project was to describe all tasks necessary for resuscitation of neonates with congenital anomalies, illuminating the complexity of these resuscitations and highlighting areas of variability. To complete the task analysis, we utilized several diverse sources including the Neonatal Resuscitation Program (NRP) algorithm for neonatal resuscitation, locally followed optimal care guidelines for the SDU, live and video recorded delivery room observations, and interviews with subject matter experts and SDU providers. The combination of all these data sources provides a novel approach to creating and developing task analyses.
The project began as an HTA, but the complexity of the tasks necessitated a combined HTA-CTA to understand decision points where patient assessment dictated task choice and performance. Incorporating the CTA into the HTA also allows insight into which tasks may present higher workload levels.
As an initial step, we developed an HTA-CTA of the NRP algorithm. We then focused on developing an HTA-CTA for the SDU. To ensure capture of the complexity of the system and the environment, initial task analysis data collection began through direct in person observations of delivery room resuscitations in the SDU. These observations were augmented through asking providers clarifying questions as the resuscitation allowed. The next step focused on video review of delivery room resuscitations which enabled in-depth review of specific tasks. For specific tasks, especially those involving preparation of equipment and medications, subject matter experts from the respiratory and nursing departments were interviewed.. A neonatologist with expertise in neonatal resuscitation and human factors provided oversight to the developing models. The current task analysis consists of 19 tasks, and over 262 subtasks.
Future work will analyze the variability within specific tasks and will explore how this may be related to different congenital anomalies Additionally, the variability within the steps will be investigated to propose human factors quality improvement projects to standardize and improve team performance and patient care. Video review and timestamps will be used to measure variability both qualitatively and quantitatively.
The task analysis is part of a larger body of work performing a work system analysis (WSA) within the SDU. Future work will incorporate the Systems Engineering Initiative for Patient Safety (SEIPS) to better understand the interactions and emerging properties that occur between the providers and other systems elements such as technology, task, or the environment.
Application
The combined HTA and CTA can be used within complex settings, such as healthcare, to gain better understanding of task and cognitive load, w and to delineate which roles are responsible for assessment and decision making. This work demonstrates how multiple data sources, including subject-matter expert interviews, observations, video review, and algorithms, can be used to developed robust system models, not just in healthcare, but in other industries as well.
The resulting task analysis has several potential applications, including assessing situation awareness and interruptions, flow disruptions, and to optimize workflows. From a systems perspective, the task analysis can also be used to compare the “work as done” vs “work as imagined,” where the tasks are reviewed by subject matter experts and then compared against real life scenarios.
Understanding all the tasks, the roles involved, and the interactions can produce a systems view that outlines emergent properties of the system. Thus, the task analysis could also be used as a proactive safety tool by identifying potential failure modes and corrective actions to reduce safety concerns.
Overview of Presentation
This poster will describe the integration of a hierarchical task analysis and a cognitive task analysis into a single task analysis and describe its application to a novel environment, a delivery room dedicated to neonates with congenital anomalies. Furthermore, the posted will demonstrate how diverse data sources can be combined to create a robust task analysis.
Event Type
Poster Presentation
TimeMonday, March 254:45pm - 6:15pm CDT
LocationSalon C
Digital Health
Simulation and Education
Hospital Environments
Medical and Drug Delivery Devices
Patient Safety Research and Initiatives