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Harmful medication errors involving unfractionated and low-molecular-weight heparin in three patient safety reporting
Matthew C Grissinger1, Rodney W Hicks, Mark A Keroack
1Pennsylvania Patient Safety Reporting System, Institute for Safe Medication Practices, Horsham, Pennsylvania, USA. mgrissinger@ismp.org
Background:
External reporting of medical errors a adverse events enables learning from the errors of others in the pursuit of systems-level improvements that can prevent future errors. It is logical to presume that medication errors involving the use of anticoagulants, among the most frequently cited product classes involved in harmful medication errors, would be captured in a variety of patient safety reporting programs.
Methods:
Data on reported errors involving the anticoagulant heparin were reviewed, compared, and aggregated from the databases of three large patient safety reporting programs-MEDMARX, the Pennsylvania Patient Safety Authority's Patient Safety Reporting System, and the University Health System Consortium, together representing more than 1,000 reporting organizations for 2005
Results:
Approximately 300,000 medication errors and near misses were reported to the programs, and 10,359-a mean of 3.6% (range, 3.1%-5.5%)-involved heparin products. The proportion of heparin-related reports that involved patient harm ranged from 1.4% to 4.9%. The phase of the medication use process cited most frequently in harmful events was the administration phase (56% of errors leading to harm), followed by the prescribing phase (19% of errors leading to harm).
Discussion:
This study represents the first attempt by these three large reporting systems to combine data on a single clinical process. The consistent patterns evident in the reports, such as the percentage of all medication errors that involved heparin, suggests that reporting programs, at least for common events such as medication errors, may reach a point of diminishing returns in which aggregating more reports of a certain type yields no additional insight once a large volume of similar events is captured and analyzed.
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