Stopping incidents in their tracks: identifying weak signals for error prevention in healthcare

In order to adjust performance to ensure the success of a task and prevent error, it is necessary to anticipate, identify and respond to signals indicating changes in the system. The objectives of this study were to investigate weak signals within two different healthcare case studies by identifying key elements and behaviours of these tasks. This study investigated both Safety-I and Safety-II elements with four expert groups, two from the field of patient handling and two from the field of patient discharge. The Safety-I and Safety-II elements explored included potential errors, influencing factors, weak signals and learning opportunities arising from the investigated situations. The errors identified by the focus groups were related to skill, knowledge, inappropriate equipment, equipment misuse, lack of communication, missing or incomplete information, incorrect technique, and preconditions not being fulfilled. The influencing factors identified by the two case studies included patient-related factors, time and space-related factors as well as organizational and managerial factors such as available resources and safety culture. The weak signals identified in both case studies were analysed using the SEIPS 2.0 model. The sources of the signals were identified as originating from the work system elements “person”, “tasks”, “organization” and “internal environment”. The manifestation forms of the weak signals included the different sensory signals as well as the experience of intuition or “hunches”. Potential learning opportunities to improve signal recognition were identified and included the need for reflection and empowerment, continuous assessment and the sharing of information between the involved systems. The proposed framework and method provide a preliminary basis for the investigation of weak signals and assists in highlighting the role that the weak signals can play in safety behaviour

Development of a framework for the analysis of weak signals within a healthcare environment

Weak signals provide an opportunity for pro-activeness that can assist in improving safety. Through a review of literature and evaluated with three different case studies, this study proposed a framework for the analysis of weak signals in the healthcare environment

Unpacking Safety-II in action: weak signals of potential error in patient handling tasks

As a result of a new definition of safety, whereby the focus on the ability to succeed under varying conditions is emphasised, new opportunities for assessing and improving safety are being developed. This study investigated both Safety-I and Safety-II elements using a focus group method with two expert groups in patient handling. The Safety-I and Safety-II elements investigated included potential errors, weak signals and learning opportunities arising from these situations. The weak signals that were identified were classified as originating from either an external or internal source. Potential learning opportunities to improve signal recognition were identified

Sepsis: A work systems analysis of 30 survivor and tribute stories

Often reported incidents involving sepsis state opportunities were missed. This raises the question of where in the system these opportunities are present. Through a qualitative document analysis of tribute and survivor stories, work system elements that may provide an opportunity for the successful treatment or those that may hinder effective treatment of sepsis were identified

Weak signals in healthcare: A case study on community-based patient discharge

To adjust performance to ensure the success of a task and prevent error, it is necessary to anticipate, identify and respond to variations in the work system. The objectives of this study were to develop a framework for the analysis of signals, which provide an indication of variations in the system, in the healthcare environment and qualitatively investigate signals in the context of community-based patient discharge. In addition to the signals, both traditional (Safety-I) and proactive safety (SafetyII) elements were investigated with six expert groups, from the field of community-based patient discharge. The signals identified and the safety elements were analysed using the SEIPS 2.0 model. The sources of the signals were identified as originating from work system elements. The proposed framework and method provide a preliminary basis for the investigation of signals and assists in highlighting the role that these can play in safety behaviour

Factors contributing to task success: Safety II in the context of community-based patient discharge

This explorative study investigated Safety-I and Safety-II elements in six focus groups with experienced staff involved in the patient discharge process from a community perspective. The elements explored included defining a good discharge, potential errors, influencing factors, weak signals, learning opportunities, and elements that assisted in achieving a successful task outcome. Key findings included identifying person-, task-, and organization related examples that promote a good discharge. The weak signals and elements aiding success were categorised using the SEIPS 2.0 model

Stopping incidents in their tracks: identifying weak signals for error prevention in healthcare

In order to adjust performance to ensure the success of a task and prevent error, it is necessary to anticipate, identify and respond to signals indicating changes in the system. The objectives of this study were to investigate weak signals within two different healthcare case studies by identifying key elements and behaviours of these tasks. This study investigated both Safety-I and Safety-II elements with four expert groups, two from the field of patient handling and two from the field of patient discharge. The Safety-I and Safety-II elements explored included potential errors, influencing factors, weak signals and learning opportunities arising from the investigated situations. The errors identified by the focus groups were related to skill, knowledge, inappropriate equipment, equipment misuse, lack of communication, missing or incomplete information, incorrect technique, and preconditions not being fulfilled. The influencing factors identified by the two case studies included patient-related factors, time and space-related factors as well as organizational and managerial factors such as available resources and safety culture. The weak signals identified in both case studies were analysed using the SEIPS 2.0 model. The sources of the signals were identified as originating from the work system elements “person”, “tasks”, “organization” and “internal environment”. The manifestation forms of the weak signals included the different sensory signals as well as the experience of intuition or “hunches”. Potential learning opportunities to improve signal recognition were identified and included the need for reflection and empowerment, continuous assessment and the sharing of information between the involved systems. The proposed framework and method provide a preliminary basis for the investigation of weak signals and assists in highlighting the role that the weak signals can play in safety behaviour

Development of a framework for the analysis of weak signals within a healthcare environment

Weak signals provide an opportunity for pro-activeness that can assist in improving safety. Through a review of literature and evaluated with three different case studies, this study proposed a framework for the analysis of weak signals in the healthcare environment

Weak signals in healthcare: A case study on community-based patient discharge

To adjust performance to ensure the success of a task and prevent error, it is necessary to anticipate, identify and respond to variations in the work system. The objectives of this study were to develop a framework for the analysis of signals, which provide an indication of variations in the system, in the healthcare environment and qualitatively investigate signals in the context of community-based patient discharge. In addition to the signals, both traditional (Safety-I) and proactive safety (SafetyII) elements were investigated with six expert groups, from the field of community-based patient discharge. The signals identified and the safety elements were analysed using the SEIPS 2.0 model. The sources of the signals were identified as originating from work system elements. The proposed framework and method provide a preliminary basis for the investigation of signals and assists in highlighting the role that these can play in safety behaviour

Unpacking Safety-II in action: weak signals of potential error in patient handling tasks

As a result of a new definition of safety, whereby the focus on the ability to succeed under varying conditions is emphasised, new opportunities for assessing and improving safety are being developed. This study investigated both Safety-I and Safety-II elements using a focus group method with two expert groups in patient handling. The Safety-I and Safety-II elements investigated included potential errors, weak signals and learning opportunities arising from these situations. The weak signals that were identified were classified as originating from either an external or internal source. Potential learning opportunities to improve signal recognition were identified