Designing stronger interventions to improve patient safety

Avoidable patient harm is among the leading causes of morbidity and mortality in the US. In hospitals alone it accounts for 400,000 deaths per year. And the scant evidence available for other components of the healthcare system (e.g., ambulatory care, long-term care, home healthcare, etc.) suggests that they are no safer.

To address this pandemic of patient harm, healthcare organizations have adopted risk management tools from other industries, including: root cause analysis (RCA), a retrospective risk assessment technique that aims to uncover the underlying problems that led to an instance of harm; and failure mode and effects analysis (FMEA), a prospective risk assessment technique that aims to uncover hazards before they cause harm. While there is some evidence that these tools improve the quality and quantity of hazards identified, they have not reduced the overall rate of patient harm.

One reason for this: These tools focus solely on problem exploration. They provide no direct support for designing solutions. And in the absence of such support, healthcare organizations overwhelmingly fall back on administrative risk control interventions such as policies and training. These are among the least robust interventions available.

This presentation will introduce the three-tiered hierarchy of risk control for assessing the robustness of interventions to improve patient safety. It will then present the Active Risk Control (ARC) Toolkit, a structured approach to designing stronger risk control interventions (analogous to the use of RCA or FMEA for risk assessment).

Key research findings related to the ARC Toolkit and its components will also be presented. Evidence to date suggests that the Toolkit successfully improves the robustness of risk control recommendations and enables participants to better plan for the full lifecycle of an improvement intervention. Use of the toolkit also increases users’ confidence in the risk management process.