Medical error classification

ADEs and medication errors can be extracted from practice data, incidents reports from health professionals, and patient surveys. Practice data include charts, laboratory, prescription data, and administrative databases, and can be reviewed manually or screened by computer systems to identify signals. A method of ADE and medication error detection and classification has been presented that is feasible and has good reliability (Marimoto et al. 2004). It can be used in various clinical settings to measure and improve medication safety. 

To identify opportunities for reducing medication errorS/ it is important that each error be carefully reviewed by a limited number of individuals to gain intimate knowledge of each reported incident. Collection and classification of error data must be followed by use of a careful epidemiological approach to problem solving at the system level. Narrative data which may not be seen by looking at the categorical data alone/ can be used to provide important details about proximal causes and latent error that may have contributed to the event. Success in this type of error reduction requires the reviewers to read between the lineS/ look for common threads between reports/ and link multiple errors that are the result of system weaknesses. 

Often multidisciplinary teams have never met to establish consensus on critical definitions, that is, to establish a common language," says an administrative leader who took part in developing the system. "Physicians, administrators, nurses, pharmacists, and performance improvement staff created error classification schemes for medication variances together."... 

Scarborough A. Bailey L. Pounds J. 2005. Examining ATC Operational Errors Using the Human Factors Analysis and Classification System. Civil Aerospace Medical Institute, Federal Aviation Administration, Oklahoma City, OK 73125. 

The two items belonging to the remote patient monitoring classification are telemedicine and telehealth. Finally, the pattern identification (to learn from errors and systems influences on adverse events) classification includes items such as electronic medical records and workload and staffing data systems. Additional information on technology commonly used by the nursing profession is available in Ref. [4]. 

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