Data Requirements for the Correct Identification of Medication Errors and Adverse Drug Events in Patients Presenting at an Emergency Department
| Autor: | Fabian Müller, Barbara Pfistermeister, Renke Maas, Thomas Bürkle, Harald Dormann, Anja Sonst, Bettina Plank-Kiegele, Andrius Patapovas |
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| Rok vydání: | 2016 |
| Předmět: |
Drug
020205 medical informatics Side effect Drug-Related Side Effects and Adverse Reactions media_common.quotation_subject Statistics as Topic Health Informatics Pharmacy 02 engineering and technology Clinical decision support system law.invention 03 medical and health sciences 0302 clinical medicine Health Information Management law 0202 electrical engineering electronic engineering information engineering medicine Humans Medication Errors 030212 general & internal medicine Prospective cohort study media_common Advanced and Specialized Nursing Clinical pharmacology business.industry Emergency department medicine.disease Identification (information) Medical emergency business Emergency Service Hospital |
| Zdroj: | Methods of information in medicine. 56(4) |
| ISSN: | 2511-705X |
| Popis: | Summary Background: Adverse drug events (ADE) involving or not involving medication errors (ME) are common, but frequently remain undetected as such. Presently, the majority of available clinical decision support systems (CDSS) relies mostly on coded medication data for the generation of drug alerts. It was the aim of our study to identify the key types of data required for the adequate detection and classification of adverse drug events (ADE) and medication errors (ME) in patients presenting at an emergency department (ED). Methods: As part of a prospective study, ADE and ME were identified in 1510 patients presenting at the ED of an university teaching hospital by an interdisciplinary panel of specialists in emergency medicine, clinical pharmacology and pharmacy. For each ADE and ME the required different clinical data sources (i.e. information items such as acute clinical symptoms, underlying diseases, laboratory values or ECG) for the detection and correct classification were evaluated. Results: Of all 739 ADE identified 387 (52.4%), 298 (40.3%), 54 (7.3%), respectively, required one, two, or three, more information items to be detected and correctly classified. Only 68 (10.2%) of the ME were simple drug-drug interactions that could be identified based on medication data alone while 381 (57.5%), 181 (27.3%) and 33 (5.0%) of the ME required one, two or three additional information items, respectively, for detection and clinical classification. Conclusions: Only 10% of all ME observed in emergency patients could be identified on the basis of medication data alone. Focusing electronic decisions support on more easily available drug data alone may lead to an under-detection of clinically relevant ADE and ME. |
| Databáze: | OpenAIRE |
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