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Related Concept Videos

Pharmacovigilance01:19

Pharmacovigilance

Post-marketing surveillance is a critical component of pharmaceutical regulation, often uncovering unanticipated adverse drug reactions (ADRs) once a drug is widely used over an extended period.
This process, termed pharmacovigilance, aims to detect, evaluate, and minimize harmful effects related to medication use. The data collection for pharmacovigilance depends on spontaneous reporting systems, where healthcare professionals or patients voluntarily report suspected ADRs.
In some cases, there...
Therapeutic Drug Monitoring: Affecting Factors01:29

Therapeutic Drug Monitoring: Affecting Factors

Therapeutic Drug Monitoring (TDM) is the clinical practice of measuring specific drug levels in a patient's blood or body tissues to manage and optimize therapy. TDM is crucial for drugs with narrow therapeutic windows, like warfarin and phenytoin, where incorrect doses can lead to treatment failure or severe side effects. This monitoring ensures the dosage administered is within a safe and effective range. The factors affecting therapeutic drug monitoring include:Patient-Specific Factors:a.
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Dosage Regimen: Individualization01:24

Dosage Regimen: Individualization

Individualization in dosing regimens is the customization of medication doses for individual patients. Its necessity arises from the goal of maximizing therapeutic benefits while minimizing risks. This approach is pivotal because human responses to drugs can vary widely; what is effective for one person may be inadequate or excessive for another. Interpatient (intersubject) variability refers to differences in drug responses between individuals, while intrapatient (intrasubject) variability...
Bioequivalence of Drugs: Drugs with Multiple Indications01:09

Bioequivalence of Drugs: Drugs with Multiple Indications

The concept of therapeutic equivalence (TE) in drugs with multiple indications is complex. A generic drug may be therapeutically equivalent to a brand-name product for one specific indication, but this doesn't necessarily mean it's equivalent for all other indications. Evidence of TE in one patient group and bioequivalence shown in healthy volunteers can support—but not confirm—TE for other indications. However, definitive proof requires individual clinical studies for each indication due to...
Therapeutic Drug Monitoring: Overview and Classification01:16

Therapeutic Drug Monitoring: Overview and Classification

Therapeutic Drug Monitoring (TDM) is a clinical practice that measures specific drug levels in a patient's blood at designated intervals to ensure the drug concentration stays within a therapeutic range. This monitoring is crucial for optimizing individual dosage regimens, enhancing therapeutic efficacy, and minimizing drug-related toxicity. TDM is vital for drugs with narrow therapeutic windows, significant variability in pharmacokinetics, and a clear correlation between plasma levels and...

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Updated: May 24, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Detecting Contraindications in Routinely Collected Healthcare Data to Emulate Decision Support for Medication Reviews

Florian Schmidt1, Alexander Struebing1, Helene Koester2

  • 1Institute of Medical Informatics, Statistics and Epidemiology, Leipzig University, Germany.

Studies in Health Technology and Informatics
|May 23, 2026
PubMed
Summary
This summary is machine-generated.

This study developed a computable, FHIR-based approach to detect medication contraindications in electronic health records. The method successfully identified potential medication-related problems in over half of analyzed inpatient cases.

Keywords:
Clinical decision supportContraindicationsDrug safetyElectronic health recordsFHIRMedical Informatics InitiativeMedication-related problemsPharmacist validationReal-world dataTemporal reasoning

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Area of Science:

  • Health Informatics
  • Clinical Decision Support
  • Pharmacovigilance

Background:

  • Medication-related problems (MRPs), including contraindications, are a significant source of preventable patient harm.
  • Existing clinical decision support systems (CDSS) often fail to detect contraindications due to a lack of clinical context in electronic health records (EHRs).

Purpose of the Study:

  • To develop and evaluate a computable, FHIR-based approach for identifying contraindications within routinely collected EHR data.
  • To address the limitations of current CDSS in detecting medication contraindications by incorporating temporal context.

Main Methods:

  • A FHIR-based approach was developed using the CDS Toolchain to process EHR data.
  • Standardized FHIR resources were harmonized under the German Medical Informatics Initiative (MII) Core Dataset.
  • Contraindications were mapped to standard terminologies and implemented as two-trigger rules requiring temporal overlap.

Main Results:

  • The algorithm was applied to 2,005 inpatient cases from 1,729 unique patients.
  • A potential medication-related problem was identified in 411 cases (52.1%).
  • Of the analyzed cases, 789 had a documented medication review.

Conclusions:

  • The FHIR-based approach demonstrates the feasibility of detecting temporally defined contraindications from routine EHR data.
  • This method provides a reproducible foundation for pharmacist validation and future multicenter studies.
  • The findings highlight the potential for improved medication safety through enhanced clinical decision support.