Data Requirements for the Correct Identification of Medication Errors and Adverse Drug Events in Patients Presenting at an Emergency Department

Plank-Kiegele, Bettina; Bürkle, Thomas; Müller, Fabian; Patapovas, Andrius; Sonst, Anja; Pfistermeister, Barbara; Dormann, Harald; Maas, Renke

doi:10.3414/me16-01-0126

Cited by 8 publications

(8 citation statements)

References 36 publications

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“…This is a relevant proportion, but still less than one would expect based on the literature. In an analysis of ADE and medication errors in patients presented at an emergency department, originating from the same region as the present study, only 10% could be identified based on medication data alone (i.e., the data typically available to a pharmacist), the rest required consideration of additional clinical data [ 8 ]. This may constitute a somewhat unfair comparison though, because in emergency patients, the diagnoses may play a more critical role with respect to the sensitivity to adverse drug effects, as the patients may be even more critically ill than the average residents of a nursing home.…”

Section: Discussionmentioning

confidence: 99%

“…If all prescriptions that have been prescribed to a patient by different doctors, and possibly also over-the-counter (“OTC”) drugs, are dispensed and recorded by a single pharmacy, the completeness of the information is improved and the chance of recognizing, at least, medication problems such as drug interactions, increases [ 6 , 7 ]. Investigations in emergency patients have shown that with the usual focus on the easy to (electronically) detect drug–drug interactions, a significant proportion of medication errors could possibly go undetected, as these often result from contraindicated “drug–diagnosis” combinations [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

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Extended Pharmacist Assessment of Medication Safety for Nursing Home Residents—A Cross-Sectional and Prospective Study

Führling

Maas

2022

JCM

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In the routine pharmacist’s medication review in ambulatory care and nursing homes in Germany, clinical diagnoses are often insufficiently considered as they are frequently not accessible to pharmacists and their electronic support tools. This may leave a significant proportion of medication-related problems (MRP) undetected and unresolved. Moreover, limited and incomplete data may promote spurious alerts of low clinical relevance. In order to assess the impact of improved data availability, we conducted a study (German Clinical Trials Register DRKS00025346) to evaluate the impact of an extended pharmacist’s medication review, made possible by diagnosis data being routinely available to the pharmacist. At six nursing homes in the Nuremberg metropolitan area, 338 patients treated by 32 physicians were enrolled. A pharmacist’s medication review, considering only the medication data, identified 114 potential MRPs, and additional consideration of diagnoses further identified 69 potential MRPs. The physicians adapted the therapy in response to 69.9% of alerts. The observed gain in MRP identified indicates that efforts should be intensified to facilitate and improve consideration of drug–diagnosis-related MRP by improving data sharing and communication between pharmacists and physicians caring for nursing home residents.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Extended Pharmacist Assessment of Medication Safety for Nursing Home Residents—A Cross-Sectional and Prospective Study

Führling

Maas

2022

JCM

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“…Pharmacists filling prescriptions have to make sure that no medication error exists and often rely on support by electronic interaction checks. Existing interaction checks often focus on drug–drug interactions, although according to an analysis from Plank‐Kiegele et al, only 10.3% of all medication errors are related to the medication data alone (i.e., drug–drug interactions and drug–drug contraindications) 35 . Therefore, the generation of extended information from a patient's medication may allow assessment of a broader spectrum of medication errors.…”

Section: Discussionmentioning

confidence: 99%

Use of medication data alone to identify diagnoses and related contraindications: Application of algorithms to close a common documentation gap

Andrikyan

Then

Gaßmann

et al. 2022

Brit J Clinical Pharma

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Aims Automated checks for medication‐related problems have become a cornerstone of medication safety. In many clinical settings medication checks remain confined to drug–drug interactions because only medication data are available in an adequately coded form, leaving possible contraindicated drug–disease combinations unaccounted for. Therefore, we devised algorithms that identify frequently contraindicated diagnoses based on medication patterns related to these diagnoses. Methods We identified drugs that are associated with diseases constituting common contraindications based on their exclusive use for these conditions (such as allopurinol for gout or salbutamol for bronchial obstruction). Expert‐based and machine learning algorithms were developed to identify diagnoses based on highly specific medication patterns. The applicability, sensitivity and specificity of the approach were assessed by using an anonymized real‐life sample of medication and diagnosis data excerpts from 3506 discharge records of geriatric patients. Results Depending on the algorithm, the desired focus (i.e., sensitivity vs. specificity) and the disease, we were able to identify the diagnoses gout, epilepsy, coronary artery disease, congestive heart failure and bronchial obstruction with a specificity of 44.0–99.8% (95% CI 41.7–100.0%) and a sensitivity of 3.8–83.1% (95% CI 1.0–86.1%). Using only medication data, we were able to identify 123 (51.3%) of 240 contraindications identified by experts with access to medication data and diagnoses. Conclusion This study provides a proof of principle that some key diagnosis‐related contraindications can be identified based on a patient's medication data alone, while others cannot be identified. This approach offers new opportunities to analyse drug–disease contraindications in community pharmacy or clinical routine data.

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“…In 2006, Kopp et al, proposed a direct observation method to detect MEs ( Kopp et al, 2006 ). Later, a number of reports used prospective ( Ewig et al, 2017 , Plank-Kiegele et al, 2017 ) or retrospective ( Silva et al, 2011 , Stultz and Nahata, 2015 ) methods to explore MEs; however, both these methods have limitations. A prospective study is usually costly and a large sample investigation is difficult to carry out.…”

Section: Introductionmentioning

confidence: 99%

Investigation of the characteristics of medication errors and adverse drug reactions using pharmacovigilance data in China

Tan

Lin³

et al. 2020

Saudi Pharmaceutical Journal

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The aim of this study was to investigate the characteristics of medication errors (MEs) and adverse drug reactions (ADRs) using data from the spontaneous reporting system, which is helpful to understand the actual situation of MEs in China. Data from 2015 in a south distinct in Shanghai were gathered from the spontaneous reporting system and analyzed. The general information, cause of errors, severity, primary diseases, involved system and organs, symptoms, and suspected drugs were investigated. A total of 1290 adverse drug events (ADEs), including 1079 ADRs and 211 MEcs (MEs causing ADE), were reported. Older patients suffered from both ADRs and MEcs (age distribution and dosage form were different between ADRs and MEcs). The main causes of errors were inappropriate usage and dosage of drugs and inappropriate indication selection. Most ADR and MEc cases were mild; the possibility of developing a severe adverse event was quite low. The distribution of the top 10 system and organs, and symptoms involved was significantly different between ADRs and MEcs, with J01 drugs (antibacterials for systemic use) being the leading cause in both. Our results suggested that a direct analysis of data from the spontaneous reporting system is a reliable, and convenient method to investigate MEs and ADRs, despite the existing limitations, and contributes to further understanding the current situation of MEs and ADRs in China.

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Data Requirements for the Correct Identification of Medication Errors and Adverse Drug Events in Patients Presenting at an Emergency Department

Abstract: 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.

Cited by 8 publications

References 36 publications

Extended Pharmacist Assessment of Medication Safety for Nursing Home Residents—A Cross-Sectional and Prospective Study

Extended Pharmacist Assessment of Medication Safety for Nursing Home Residents—A Cross-Sectional and Prospective Study

Use of medication data alone to identify diagnoses and related contraindications: Application of algorithms to close a common documentation gap

Investigation of the characteristics of medication errors and adverse drug reactions using pharmacovigilance data in China

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