• The discovery

    • Who discovered/reported the event—role, not names

    • How it was discovered

  • The event itself

    • What happened—the type of adverse event

    • Where in the care process the event was discovered and/or occurred

    • When it occurred

    • Who was involved—functions, not names

    • Why—the most dominant cause based on a preliminary analysis

    • Likelihood of recurrence of similar adverse events

    • Severity of the event

    • Preventability of the event

  • Ancillary information

    • Product information (blood, devices, drugs) if involved in the adverse event

    • Patient information, including age, gender, ethnicity, diagnoses, procedures, and comorbid conditions

  • Detailed analysis

On the basis of the above information, a decision should be made as to whether a formal root-cause analysis should be carried out (a similar decision is required to investigate a near miss; see Chapter 7). Using automated surveillance together with other detection methods will lead to the detection of a much greater number of adverse events that might warrant such an analysis than would otherwise be possible. All such events cannot feasibly be investigated. Thus if root-cause analyses are not focused on a critical subset, then (1) useless analyses will be carried out because there is no time to do them properly, and (2) effort will be devoted to performing root-cause analyses at the expense of testing and implementing real system changes that can reduce injury rates. The decision to carry out a root-cause analysis will normally depend on the following factors:

  • The likelihood of recurrence of similar adverse events—the assessment is facilitated by access to a database of adverse events. If a similar case has recently been investigated, full root-cause analysis will have only marginal utility.

  • The severity of the adverse event—can be assessed by direct observation.



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