Preventing potential drug-drug interactions through alerting decision support systems: A clinical context based
Habibollah Pirnejad1, Parasto Amiri2, Zahra Niazkhani3
1Patient Safety Research Center, Urmia University of Medical Sciences, Urmia, Iran; Erasmus School of Health Policy & Management (ESHPM), Erasmus University Rotterdam, Rotterdam, the Netherlands.
Background:
The effectiveness of the clinical decision support systems (CDSSs) is hampered by frequent workflow interruptions and alert fatigue because of alerts with little or no clinical relevance. In this paper, we reported a methodology through which we applied knowledge from the clinical context and the international recommendations to develop a potential drug-drug interaction (pDDI) CDSS in the field of kidney transplantation.
Methods:
Prescriptions of five nephrologists were prospectively recorded through non-participatory observations for two months. The Medscape multi-drug interaction checker tool was used to detect pDDIs. Alongside the Stockley's drug interactions reference, our clinicians were consulted with respect to the clinical relevance of detected pDDIs. We performed semi-structured interviews with five nephrologists and one informant nurse. Our clinically relevant pDDIs were checked with the Dutch "G-Standard". A multidisciplinary team decided the design characteristics of pDDI-alerts in a CDSS considering the international recommendations and the inputs from our clinical context. Finally, the performance of the CDSS in detecting DDIs was evaluated iteratively by a multidisciplinary research team.
Results:
Medication data of 595 patients with 788 visits were collected and analyzed. Fifty-two types of interactions were most common, comprising 90% of all pDDIs. Among them 33 interactions (comprising 77% of all pDDIs) were rated as clinically relevant and were included in the CDSS's knowledge-base. Of these pDDIs, 73% were recognized as either pseudoduplication of drugs or not a pDDI when checked with the Dutch G-standard. Thirty-three alerts were developed and physicians were allowed to customize the appearance of pDDI-alerts based on a proposed algorithm.
Conclusion:
Clinical practice contexts should be studied to understand the complexities of clinical work and to learn the type, severity and frequency of pDDIs. In order to make the alerts more effective, clinicians' points of view concerning the clinical relevance of pDDIs are critical. Moreover, flexibility should be built into a pDDI-CDSS to allow clinicians to customize the appearance of pDDI-alerts based on their clinical context.
More Related Videos
08:21Monitoring GPCR-β-arrestin1/2 Interactions in Real Time Living Systems to Accelerate Drug Discovery
Published on: June 28, 2019
08:46Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms
Published on: December 9, 2015
Related Concept Videos
Pharmacokinetics: Drug–Drug Interactions
Pharmacokinetics: Drug–Food and Drug–Viral Interactions
Drug-Receptor Interactions
Several parameters, such as the drug's affinity for its receptor and its efficacy, which is its ability to activate the receptor, determine the drug's effect on the tissue....
Factors Affecting Protein-Drug Binding: Drug Interactions
Displacement interactions can have varying outcomes, ranging from toxicity to virtually...
Factors Affecting Renal Clearance: Drug Distribution and Drug Interactions
One important factor is the relationship between renal clearance and the apparent volume of distribution. Renal clearance tends to be inversely proportional to the apparent volume of distribution. Drugs with an extensive distribution volume or those...
Drug-Receptor Interaction: Antagonist
Antagonists can be classified as competitive or noncompetitive based on their...
