Presentation
Systems Safety Engineering: Testing the feasibility of having healthcare workers perform a Causal Analysis using Systems Theory (CAST) and comparing this method to the standard approach
DescriptionSystems approaches to safer care have been promoted for nearly 25 years, yet still remain underutilized, with arguably only moderate progress away from blame-and-retrain methods. Most solutions are still focused on behavioral change. Promoting systems safety tools and providing training and coaching to deploy them may be one way to achieve richer, more systems-based adverse event analyses. This may be starting to change with the rising awareness of human factors engineering, the spread of embedded human factors engineers in healthcare systems, and the Institute of Healthcare Improvement’s recent Human Factors in Healthcare certification. In the UK, for example, the Patient Safety Incident Response Framework (PSIRF), which is based on Systems Engineering Initiative for Patient Safety (SEIPS), appears to demonstrate considerable success. Systems safety engineering is another engineering discipline that has been studied in only limited ways in healthcare. In this study, we explored the implementation of a set of systems safety engineering tools – the Systems-Theoretic Accident Model and Process (STAMP), developed by Prof Nancy Leveson – to explore specimen handling in the operating room (OR), from removal from the patient to arrival in the pathology lab.
Specimen-related adverse events are common, occurring in approximately 1% of collected specimens, leading to specimen loss, mislabeling, and mishandling, with an estimated 160,000 adverse events in the US annually due to specimen misidentification alone. Specimen failures, in turn, lead to patient diagnostic failures, disability, death, mental distress, and repeat procedures, with healthcare providers suffering moral injury, and healthcare institutions facing financial, med-legal, and reputational risks. Estimates suggest that the average compensation for medical malpractice for all specimen failures is $12,500 while the average compensation for high-risk specimen failures is $500,000. Despite considerable efforts from the Joint Commission and safety organizations, and mandated reporting requirements in many states, solutions remain elusive. Most studies focus on the categorization and frequency of specimen error types, and on traditional, person-centered approaches to reduce them (e.g., teaching, policy change), which say little about why specimen errors occur or how to circumvent them in the long run. Few studies address specimen errors systemically to identify the underlying hazards or complex interactions between departments, processes, technologies, and people that lead to error. This project uses a systems engineering approach to provide new perspectives on the problem to yield an array of potential interventions.
STAMP is a systems engineering approach that has been enormously successful and well-studied in other industries for over 30 years (e.g., NASA Columbia Shuttle, Deepwater Horizon). While its spread into healthcare is limited, it has been used in radiation oncology, anesthesiology, and interventional radiology. Based on Systems Theory, it frames systems as a set of human and computer “controllers” and treats safety as a system control problem. Adverse events occur when there are uncontrolled hazards in a control loop, such as inadequate feedback. For example, a surgical specimen can be lost (adverse event) when the scrub technician (controller) cannot distinguish tissue to be thrown out from tissue specimens that go to the laboratory (hazard due to lack of feedback to the scrub technician). STAMP comprehensively and systematically identifies and addresses all hazards.
To study the implementation and value of utilizing STAMP, we introduced the analysis technique to 12 healthcare workers -- including 8 who regularly perform adverse event investigations and analyses -- within a large West Coast health system. We focused on the use of Causal Analysis using Systems Theory (CAST), an arm of STAMP focused on the analysis of events after they have occurred. Our aim was to learn about the challenges for healthcare workers trying to use these tools and use this feedback to iteratively teach healthcare staff to think like an engineer (enough to be able to use the tool), and then to compare the STAMP findings with the current analysis methods. Here, we present early interim results of our findings.
Our preliminary data suggest that the results from using STAMP generate solutions that are stronger, with more breadth (e.g., focusing not just on the people but also on the environment, tools, and processes), and, if implemented, are more likely to be effective when compared with our standard approach. We have also found that changing the mental
Specimen-related adverse events are common, occurring in approximately 1% of collected specimens, leading to specimen loss, mislabeling, and mishandling, with an estimated 160,000 adverse events in the US annually due to specimen misidentification alone. Specimen failures, in turn, lead to patient diagnostic failures, disability, death, mental distress, and repeat procedures, with healthcare providers suffering moral injury, and healthcare institutions facing financial, med-legal, and reputational risks. Estimates suggest that the average compensation for medical malpractice for all specimen failures is $12,500 while the average compensation for high-risk specimen failures is $500,000. Despite considerable efforts from the Joint Commission and safety organizations, and mandated reporting requirements in many states, solutions remain elusive. Most studies focus on the categorization and frequency of specimen error types, and on traditional, person-centered approaches to reduce them (e.g., teaching, policy change), which say little about why specimen errors occur or how to circumvent them in the long run. Few studies address specimen errors systemically to identify the underlying hazards or complex interactions between departments, processes, technologies, and people that lead to error. This project uses a systems engineering approach to provide new perspectives on the problem to yield an array of potential interventions.
STAMP is a systems engineering approach that has been enormously successful and well-studied in other industries for over 30 years (e.g., NASA Columbia Shuttle, Deepwater Horizon). While its spread into healthcare is limited, it has been used in radiation oncology, anesthesiology, and interventional radiology. Based on Systems Theory, it frames systems as a set of human and computer “controllers” and treats safety as a system control problem. Adverse events occur when there are uncontrolled hazards in a control loop, such as inadequate feedback. For example, a surgical specimen can be lost (adverse event) when the scrub technician (controller) cannot distinguish tissue to be thrown out from tissue specimens that go to the laboratory (hazard due to lack of feedback to the scrub technician). STAMP comprehensively and systematically identifies and addresses all hazards.
To study the implementation and value of utilizing STAMP, we introduced the analysis technique to 12 healthcare workers -- including 8 who regularly perform adverse event investigations and analyses -- within a large West Coast health system. We focused on the use of Causal Analysis using Systems Theory (CAST), an arm of STAMP focused on the analysis of events after they have occurred. Our aim was to learn about the challenges for healthcare workers trying to use these tools and use this feedback to iteratively teach healthcare staff to think like an engineer (enough to be able to use the tool), and then to compare the STAMP findings with the current analysis methods. Here, we present early interim results of our findings.
Our preliminary data suggest that the results from using STAMP generate solutions that are stronger, with more breadth (e.g., focusing not just on the people but also on the environment, tools, and processes), and, if implemented, are more likely to be effective when compared with our standard approach. We have also found that changing the mental
Event Type
Oral Presentations
TimeWednesday, March 259:15am - 9:37am EDT
LocationMurray Hill East
Patient Safety Research and Initiatives