and (3) use decision support tools (e.g., computerized physician order entry). Thus, comprehensive clinical and patient safety data are necessary for adverse event detection and monitoring.

ANALYSIS OF ADVERSE EVENT SYSTEMS

Functional Requirements
Understanding an Adverse Event

An outside physician calls hospital administration after one of her patients develops a near-fatal adverse reaction thought to be secondary to a drug–drug reaction to a medication prescribed in an emergency department 2 days previously. The patient safety team is assembled and after some careful detective work determines that the cause of the problem was that house staff rotating into the hospital from outside institutions were trained inadequately in use of the hospital electronic health record.

Determining which of many interwoven processes should be implicated in a typical case of error is a critical step in eliminating sources of risk in the health care system. Making this determination involves asking four main questions.2 First, what is the event we are trying to eliminate? In this case we are trying to prevent patients from receiving an inappropriate drug. Second, which roles or processes must occur for this event to happen? Here, steps include recognizing a patient’s need for a medication, prescribing, filling the prescription, delivering it to the patient, and so on. Next, when did the event occur, and were there co-occurring events that could be related? Here, the fact that this reaction occurred in close proximity to the initiation of a new medication is helpful. Finally, where did the event or associated processes take place? In this case, characteristics of emergency departments, outpatient pharmacies, and homes are important.

In the parlance of public health professionals, adverse event surveillance should characterize a latent3 problem within a complex system, placing the event in context rather than characterizing it as primarily the failing of a single upstream process, such as a hospital, patient, or provider. The

2  

A similar approach is adopted for the analysis of a near miss; see the next chapter.

3  

James Reason distinguishes two types of errors—active and latent (Reason, 1990). Active errors are associated with the performance of front-line operators, such as doctors and nurses. Latent errors result from underlying system failures.



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