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Forschungsdatenbank PMU-SQQUID

Detecting, Monitoring, and Reporting Possible Adverse Drug Events Using an Arden-Syntax-based Rule Engine.
Fehre, K; Plössnig, M; Schuler, J; Hofer-Dückelmann, C; Rappelsberger, A; Adlassnig, KP;
Stud Health Technol Inform. 2015; 216: 950
Originalarbeiten (Zeitschrift)

PMU-Autor/inn/en

Schuler Jochen

Abstract

The detection of adverse drug events (ADEs) is an important aspect of improving patient safety. The iMedication system employs predefined triggers associated with significant events in a patients clinical data to automatically detect possible ADEs. We defined four clinically relevant conditions: hyperkalemia, hyponatremia, renal failure, and over-anticoagulation. These are some of the most relevant ADEs in internal medical and geriatric wards. For each patient, ADE risk scores for all four situations are calculated, compared against a threshold, and judged to be monitored, or reported. A ward-based cockpit view summarizes the results.


Useful keywords (using NLM MeSH Indexing)

Blood Coagulation Disorders/chemically induced

Blood Coagulation Disorders/diagnosis

Blood Coagulation Disorders/epidemiology

Blood Coagulation Disorders/prevention*

control

Decision Support Systems, Clinical

Drug-Related Side Effects and Adverse Reactions/diagnosis*

Drug-Related Side Effects and Adverse Reactions/epidemiology

Humans

Hyperkalemia/chemically induced

Hyperkalemia/diagnosis

Hyperkalemia/epidemiology

Hyperkalemia/prevention*

control

Hyponatremia/chemically induced

Hyponatremia/diagnosis

Hyponatremia/epidemiology

Hyponatremia/prevention*

control

Medical Order Entry Systems*

Renal Insufficiency/chemically induced

Renal Insufficiency/diagnosis

Renal Insufficiency/epidemiology

Renal Insufficiency/prevention*

control

Software