Adverse drug event
Adverse drug events and medication errors: detection and classification methods FREE T Morimoto1,2, T K Gandhi1,3, A C Seger1,4, T C Hsieh1,3, D W Bates1,3 Author affiliations Abstract Investigating the incidence, type, and preventability of adverse drug events (ADEs) and medication errors is crucial to improving the quality of health care delivery. ADEs, potential ADEs, and medication errors can be collected by extraction from practice data, solicitation of incidents 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. Research nurses, pharmacists, or research assistants review these signals, and those that are likely to represent an ADE or medication error are presented to reviewers who independently categorize them into ADEs, potential ADEs, medication errors, or exclusions. These incidents are also classified according to preventability, ameliorability, disability, severity, stage, and responsible person. These classifications, as well as the initial selection of incidents, have been evaluated for agreement between reviewers and the level of agreement found ranged from satisfactory to excellent (κ = 0.32–0.98). The method of ADE and medication error detection and classification described is feasible and has good reliability. It can be used in various clinical settings to measure and improve medication safety.
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Picked up by 1 news outlets Blogged by 1 Referenced in 2 policy sources Tweeted by 2 Referenced in 1 Wikipedia pages 261 readers on Mendeley Request Permissions Medications are the most frequent cause of adverse events, and such injuries are called adverse drug events (ADEs).1,2 ADEs are common in most clinical settings including adult inpatients with a reported incidence of 6.5%,3 adult outpatients with an incidence of 27.4%,4 and pediatric inpatients with a reported incidence of 2.3%.5 These ADEs have substantial consequences including hospital admissions, prolonged hospital stay, additional resource utilization, and time away from work, as well as lower patient satisfaction.6,7
Some ADEs are caused by errors called medication errors.2 Medication errors are much more frequent than ADEs but only a small minority actually cause ADEs.2 In one inpatient study the frequency of medication errors was 5.3 per 100 medication orders, much higher than the ADE rate of 0.25 per 100 orders.2 Another recent report from 36 hospitals which evaluated the administration stage in particular showed that 19% of medication administrations contained an error.8
The goal of research in ADEs and medication errors is to reduce the likelihood of harm related to medications. To do this it is essential to be able to describe the epidemiology of these problems. Building on previous work, we have developed over the last decade a methodology for identifying and classifying medication safety issues which we present here so that others may use these methods to investigate ADEs and medication errors in their own settings. We also describe the strengths and limitations of this approach, including assessment of reliability.9
The methodology includes:
definitions of incidents (ADEs, medication errors, and other drug related terms);
general processes for identifying them;
case identification methods (practice data review, self-reports from health professionals, and patient surveys);
comparison of methods;
methods for classifying incidents; and
tools for validating the findings.
METHODOLOGICAL APPROACH Definition of incidents An incident includes any irregularity in the process of medication use. It might represent an ADE, potential ADE, medication error, or none of these—it is essentially a “catch all” term for what to call something before it has been classified. An incident can occur at any point in the medication use process (ordering, transcribing, dispensing, administrating, and monitoring). There are several ways to categorize incidents: actual (ADEs) v potential; preventable v non-preventable; ameliorable v non-ameliorable; and error v non-error. These categories may overlap and it is important to understand their relationship with each other .
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