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Root Cause Analysis

September 7, 2019


Root cause analysis (RCA) is a structured method used to analyze serious adverse events. Initially developed to analyze industrial accidents, RCA is now widely deployed as an error analysis tool in health care. A central tenet of RCA is to identify underlying problems that increase the likelihood of errors while avoiding the trap of focusing on mistakes by individuals. RCA thus uses the systems approach to identify both active errors (errors occurring at the point of interface between humans and a complex system) and latent errors (the hidden problems within health care systems that contribute to adverse events). It is one of the most widely used retrospective methods for detecting safety hazards.

RCAs should generally follow a prespecified protocol that begins with data collection and reconstruction of the event in question through record review and participant interviews. A multidisciplinary team should then analyze the sequence of events leading to the error, with the goals of identifying how the event occurred (through identification of active errors) and why the event occurred (through systematic identification and analysis of latent errors) (Table). The ultimate goal of RCA, of course, is to prevent future harm by eliminating the latent errors that so often underlie adverse events.

Table. Factors That May Lead to Latent Errors

Type of Factor



A patient on anticoagulants received an intramuscular pneumococcal vaccination, resulting in a hematoma and prolonged hospitalization. The hospital was under regulatory pressure to improve its pneumococcal vaccination rates.


A nurse detected a medication error, but the physician discouraged her from reporting it.

Work environment

Lacking the appropriate equipment to perform hysteroscopy, operating room staff improvised using equipment from other sets. During the procedure, the patient suffered an air embolism.

Team environment

A surgeon completed an operation despite being informed by a nurse and the anesthesiologist that the suction catheter tip was missing. The tip was subsequently found inside the patient, requiring reoperation.


An overworked nurse mistakenly administered insulin instead of an antinausea medication, resulting in hypoglycemic coma.


An intern incorrectly calculated the equivalent dose of long-acting MS Contin for a patient who had been receiving Vicodin. The patient experienced an opiate overdose and aspiration pneumonia, resulting in a prolonged ICU course.

Patient characteristics

The parents of a young boy misread the instructions on a bottle of acetaminophen, causing their child to experience liver damage.

As an example, a classic paper described a patient who underwent a cardiac procedure intended for another, similarly named patient. A traditional analysis might have focused on assigning individual blame, perhaps to the nurse who sent the patient for the procedure despite the lack of a consent form. However, the subsequent RCA revealed 17 distinct errors ranging from organizational factors (the cardiology department used a homegrown, error-prone scheduling system that identified patients by name rather than by medical record number) to work environment factors (a neurosurgery resident who suspected the mistake did not challenge the cardiologists because the procedure was at a technically delicate juncture). This led the hospital to implement a series of systematic changes to reduce the likelihood of a similar error in the future.

RCA is a widely used term, but many find it misleading. As illustrated by the Swiss cheese model, multiple errors and system flaws often must intersect for a critical incident to reach the patient. Labeling one or even several of these factors as "causes" may place undue emphasis on specific "holes in the cheese" and obscure the overall relationships between different layers and other aspects of system design. Accordingly, some have suggested replacing the term "root cause analysis" with "systems analysis."

Effectiveness of Root Cause Analysis

Root cause analysis is one of the most widely used approaches to improving patient safety, but its effectiveness has been called into question. Studies have shown that RCAs often fail to result in the implementation of sustainable systems-level solutions. A 2017 commentary identified eight common reasons for ineffectiveness of the RCA process, including overreliance on weak solutions (such as educational interventions and enforcing existing policies), failure to aggregate data across institutions, and failure to incorporate principles of human factors engineering and safety science into error analysis and improvement efforts. The National Patient Safety Foundation has proposed renaming the process root cause analysis and action (RCA2)—emphasizing that a well-done RCA should yield robust corrective actions and risk reduction. As detailed in a 2016 Annual Perspective, safety experts agree that effective error analysis requires the active involvement of organizational leadership, training of specialized teams with expertise in safety science, focusing on stronger systems-level solutions, and measuring implementation and impact on outcomes. Given the considerable time investment required to perform a formal RCA, more abbreviated incident analysis techniques may be appropriate in some cases.

Current Context

The Joint Commission has mandated use of RCA to analyze sentinel events (such as wrong-site surgery) since 1997. As of 2009, 25 states and the District of Columbia have mandated reporting of serious adverse events (increasingly using the National Quality Forum's list of "Never Events"), and many states also require that RCA be performed and reported after any serious event. Although no data are yet available on this subject, RCA use has likely increased with the growth in mandatory reporting systems.

This project was funded under contract number 75Q80119C00004 from the Agency for Healthcare Research and Quality (AHRQ), U.S. Department of Health and Human Services. The authors are solely responsible for this report’s contents, findings, and conclusions, which do not necessarily represent the views of AHRQ. Readers should not interpret any statement in this report as an official position of AHRQ or of the U.S. Department of Health and Human Services. None of the authors has any affiliation or financial involvement that conflicts with the material presented in this report. View AHRQ Disclaimers
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