The use of “safety triggers,” or clues, to identify adverse events (AEs) is an effective method for measuring the overall level of harm from workplace events or company organization that don’t follow safety. Traditional efforts to detect AEs have focused on voluntary reporting and tracking of errors or lead and lag issues. Workplaces and employers need a more effective way to identify events that do cause harm to workers, in order to select and test changes to reduce harm.
When you think about safety triggers at work have you thought about using FMEA or SWIFT principles in solving the key issues?
Workplace Safety is NO DIFFERENT than daily life!
General Categories of Triggers:
· Emotional State (e.g., angry, depressed, happy, sad) u Physical State (e.g., relaxed, tense, tired, aroused)
· Presence of Others (e.g., when the behavior occurs are certain people present?)
· Physical Setting (e.g., work, party, ex-spouse’s house)
· Social Pressure (e.g., are you forced or coerced into doing things you don’t want to?)
· Activities (e.g., work, working at home, playing sports, watching TV, playing cards)
· Thoughts (e.g., remember times you engaged in the behavior)
Considerable effort has been devoted to optimizing methods of detecting errors and safety hazards, with the goal of prospectively identifying hazards before workers are harmed and analyzing events that have already occurred to identify and address underlying systems flaws. Despite much effort, health care institutions are still searching for optimal methods to identify underlying system defects before workers are harmed and, when errors do occur, methods to recognize them as rapidly as possible to prevent further harm.
Failure mode and effect analysis (FMEA) is a common approach to prospectively determine error risk within a particular process. FMEA begins by identifying all the steps that must be taken for a given process to occur (“process mapping”) and then how each step can go wrong (i.e., failure modes), the probability that each error will be detected before causing harm, and the impact of the error if it actually occurs. The estimated likelihood of a particular process failure, the chance of detecting such failure, and its impact are combined numerically to produce a criticality index, which provides a rough estimate of the magnitude of hazard posed by each step in a high-risk process. Steps ranked at the top (those with the highest criticality indices) should be prioritized for error proofing.
Regarding safety-related behavior, our challenge becomes one of defining what situations, including interpersonal interactions, activate at-risk behavior. But this “if-then behavioral signature” likely varies across individuals.
FMEA (or similar techniques) has been used in other high-risk industries and offers a reasonable framework for prospective safety analysis. Another, more qualitative approach termed SWIFT (“structured what-if technique”) can be used either as an adjunct to FMEA or as a stand-alone technique.
Human factors engineers often lead safety efforts in other high-risk industries, and recent commentaries have called for greater integration of human factors principles into health care and worker safety.
Other methods to prospectively uncover safety hazards rely on qualitative approaches that emphasize the views of frontline providers
Techniques to retrospectively identify safety hazards can be loosely classified into two groups: those used to screen larger datasets for evidence of preventable adverse events that merit further investigation and those that analyze individual cases of adverse events (or where an adverse event is strongly suspected). The former include trigger tools and methods of screening administrative datasets, while the latter include root cause analysis, mortality reviews, and related methods of in-depth investigation into specific workers.
Consider how different situations influence how you think, feel and act. And most importantly, value your perceptive and discriminative ability to alter your personality and your actions according to ever-changing circumstances.