Attempts to learn from high-risk industries

Attempts to learn from high-risk industries such as aviation and nuclear power have been a prominent feature of the patient safety movement since the late 1990s. One noteworthy practice adopted from such industries, endorsed by healthcare systems worldwide for the investigation of serious incidents, (1-3) is root cause analysis (RCA). Broadly understood as a method of structured risk identification and management in the aftermath of adverse events, (1) RCA is not a single technique. Rather, it describes a range of approaches and tools drawn from fields including human factors and safety science (4,5) that are used to establish how and why an incident occurred in an attempt to identify how it, and similar problems, might be prevented from happening again.(6) In this article, we propose that RCA does have potential value in healthcare, but it has been widely applied without sufficient attention paid to what makes it work in its contexts of origin, and without adequate customisation for the specifics of healthcare. (7, Cool

As a result, its potential has remained under-realised (7) and the phenomenon of organisational forgetting (9) remains widespread (Box 1). Here, we identify eight challenges facing the utilisation of RCA in healthcare and offer some proposals on how to improve learning from incidents
Why was the machine not powered down? Because those running the surgeries did not know the computer needed to be shut down, and it was faster simply to hibernate the machine.

After determining the root cause of the problem, the problem could be solved and someone was designated to power down the computer after operations. Problem discovery for healthcare systems often is more complex than in the previous example, in which many causes are found to interact with an event. Connelly (2012) suggests involvement of all stakeholders in an interdisciplinary team is important for drilling down to causes. The team needs to answer as to what happened, how it happened, why it happened, and what should be done to prevent a reoccurrence (p. 316).

Teams rather than individuals have become the focus for accreditation bodies, and a thorough analysis of root causes can often avoid sanctions, particularly for sentinel events such as the one described above in which the patient died (Dattilo and Constantino, 2006). Evidently the Joint Commission, formerly called the JCAHO, maintains a database of sentinel events, their tracking, and reviews. The JCAHO started the endeavor in 1995 and continues to today. Over 3,100 events had been collected as of 2005. What a treasure trove that database would be for medical data miners.

In the United Kingdom, the National Patient Safety Association set up a procedure for root cause analysis (Mengis and Nicolini, 2010) by focusing on questions. The questions are given in Table 11.2. Everyone is asked to answer the questions in writing so that a matrix of events may be constructed, and a time-line of events devised, and in order to identify all the factors involved. Further, a plan is devised so that the same problem will not happen in the future. The plan specifies responsibilities and times for those responsibilities to be carried out. The authors recommended solutions for common challenges to successful root cause analysis. For example, they emphasized that nurses should be trained in RCA so that they can be more assertive when the meetings take place.
Medication errors can have serious consequences for patients, and medication safety is essential to pharmaceutical care. Insight is needed into the vulnerability of the working process at community pharmacies to identify what causes error incidents, so that the system can be improved to enhance patient safety. 40 randomly selected Danish community pharmacies collected data on medication errors. Cases that reached patients were analysed, and the most serious cases were selected for root-cause analyses by an interdisciplinary analysis team. 401 cases had reached patients and a substantial number of them had possible clinical significance. Most of these errors were made in the transcription stage, and the most serious were errors in strength and dosage. The analysis team identified four root causes: handwritten prescriptions; "traps" such as similarities in packaging or names, or strength and dosage stated in misleading ways; lack of effective control of prescription label and medicine; and lack of concentration caused by interruptions. A substantial number of the medication errors identified at pharmacies that reach patients have possible clinical significance. Root-cause analysis shows potential for identifying the underlying causes of the incidents and for providing a basis for action to improve patient safety.