How to Improve Apparent Cause Analyses and Reduce Error Recurrence

How to Improve Apparent Cause Analyses and Reduce Error Recurrence 150 150 Brianne Moore

A quality improvement team embarks on a project focused on the accuracy of future quality improvement initiatives.

An apparent cause analysis (ACA) is a process used to investigate the cause or causes of a medium or low-risk safety event. Designed as a quality improvement measure, ACAs are used to explain in detail why an issue or near miss occurs and then to correct the issue and prevent its recurrence by making an action plan. Ideally, an ACA should serve as a learning tool that allows the institution at large to improve practice and reduce error recurrence, leading to safer patient care.

A recent quality improvement initiative published in Pediatric Quality and Safety paves the way for other institutions to reduce preventable harm by improving ACAs.

ACAs are only as helpful as they’re constructed to be, so when a single institution found that its ACA reliability was only 86.4 percent, it was clear that changes needed to be made.

“As the new director of patient safety, I reviewed the prior year’s completed ACAs and found that the analysis and action plans weren’t constructed well. This led to gaps in learning, frustration from faculty and error recurrence, which all contributed to relatively low reliability,” says Kristen Crandall, MSN, RN, CPN, director of patient safety at Children’s National Health System in Washington, D.C., and lead author of the study. “Seeing a low reliability score drove us to develop a project to increase ACA reliability.”

The team utilized the model for improvement and engaged experts to identify potential weaknesses in the current ACA structure. From there, they developed interventions to implement. Following the implementation of the interventions, all ACAs were a minimum of 95 percent reliable and were turned around nearly five days earlier. Stakeholders also showed a significant increase in satisfaction with the new ACAs they were utilizing.

“The high reliability toolkit we created, which links every action item or intervention to a calculable percentage of reliability, was the most impactful part of the intervention,” adds Crandall. “It gave us an objective scoring system and shifted the focus of our organization’s safety culture to quality and reliability.”

Having improved the reliability of a key quality improvement measure, the team plans to administer and review a safety culture survey to determine the effect of this reliability increase on the safety culture at their institution.

“While we’re not currently able to measure effectiveness in terms of outcome, utilizing this toolkit and strengthening action plan development should decrease error recurrence and improve patient, family and staff safety,” says Crandall. “In the future, we need a multi-center study of ACA effectiveness and quality to continue reducing repeat safety events. The peer-reviewed literature on this topic is lacking, and patients’ safety should come first.”



Crandall KM, Sten, MB, Almuhanna, A, Fahey, L, Shah, RK. Improving apparent cause analysis reliability: A quality improvement initiativePediatric Quality and Safety. 2017 May/June;2(3):e025.

About the author

Brianne is interning as a science writer and editor for Clinical & Research Communications at Nationwide Children's Hospital. She contributes to a variety of publications, including Pediatrics Nationwide and PediatricsOnline.