Drug-drug interactions: where do we go from here?

Countrywide prevalence of critical drug interactions in Hungarian outpatients: a retrospective analysis of pharmacy dispensing data

Background

Drug-drug interactions (DDIs) present a significant source of adverse drug reactions. Despite being one of the commonly cited risks to patient safety, prevention of DDIs still poses a challenge to healthcare systems. The prevalence of DDIs can be used as a quality indicator for the safety of prescribing. With the analysis of drug utilization databases, real-world data on critical DDIs can be obtained. The aim of this study was to establish a list of critical DDIs and estimate their prevalence in the Hungarian outpatient population.

Methods

Since there is no conclusive and generally accepted repository of high-risk DDIs, a systematic search of the literature for consensus-based lists was performed. Based on these results and their analysis with 5 interaction compendia, we propose a simple methodology to identify critical combinations. Present study focused on DDIs which are (1) of high clinical importance thus being most likely to cause significant harm if not detected, (2) well-supported by available evidence and (3) affect drugs which are routinely dispensed in the community pharmacy setting. A retrospective analysis of prescriptions filled between 2013 and 2016 was performed. The source of drug utilization data was the IQVIA’s national prescription fill database. The number of interacting drug pairs dispensed at the same time to the same patient was established.

Results

After excluding drugs with low dispensing rates, the analysis covered 39 DDIs. The distribution of risk categories of the analysed DDIs was inconsistent among different drug interaction compendia. The total number of prescriptions filled varied between 173924449 and 176368468 per year. The prevalence of the selected potential DDIs ranged from 0.00 to 355.89 per 100000 prescriptions per year. There was significant variation between how the number of cases had changed for each DDI throughout the study period, no general tendency could have been described.

Conclusions

There were 1.8 million cases of co-dispensing each year, where prescribers’ and community pharmacists’ role in recognizing and managing potentially serious interactions was or would have been critical. The method presented to identify high-risk DDIs can serve as a starting point for the much-needed improvement of routine interaction screening.

Electronic supplementary material

The online version of this article (10.1186/s40360-019-0311-0) contains supplementary material, which is available to authorized users.

Comparative assessment of four drug interaction compendia

AIMS

To assess the consistency of inclusion and grading of major drug interactions for 50 drugs in four leading international drug interaction compendia. METHODS Four international drug interaction compendia were compared: the drug interactions appendix of the British National Formulary, the interaction supplement in the French drug compendium Vidal, and two US drug interaction compendia, Drug Interaction Facts and the Micromedex (Drug-Reax) program. Major interactions were defined as potentially hazardous in BNF or with the warning 'contraindication' or 'avoid' in Vidal or with the significance grading 1 or 2 in DIF. Major interactions for a list of 50 drugs were searched in all four compendia.

RESULTS

A total of 1264 interactions meeting the inclusion criteria were identified for these 50 drugs. After deletion of 169 duplicates, 1095 interactions were included in the analysis. Of the drug interactions classified as major in any one compendium between 14% and 44% were not listed in the other compendia. The grading systems used for the severity and the quality of the supporting evidence in Micromedex and DIF were inconsistent.

CONCLUSIONS

There is a lack of consistency in the inclusion and grading of drug interactions of major significance for 50 drugs across the four drug compendia examined. This may reflect the lack of standardization of the terminology used to classify drug interactions and the lack of good epidemiological evidence on which to base the assessment of the clinical relevance of drug interactions.

Drug-associated disease: cytochrome P450 interactions

Critically ill patients generally are older, frequently have organ failure, and commonly receive multiple medications, all of which make them susceptible to adverse effects of drugs. Drug interactions are a common adverse effect, and many are predictable based on understanding the mechanisms that underlie drug interactions. This article identifies commonly used medications in critically ill patients and the associated drug interactions that may occur with emphasis on the cytochrome P450 enzyme system.

Evaluation of drug interaction software to identify alerts for transplant medications

BACKGROUND

The ability of computerized physician order entry (CPOE) systems to identify clinically significant drug interactions is dependent upon the integrity of the drug information populating the software. A CPOE system with incomplete or inaccurate drug information will fail to identify clinically important drug interactions and, therefore, fail to reduce preventable adverse drug events (pADEs).

OBJECTIVE

To evaluate, from the prescribers' perspective, the ability of a common drug interaction database to identify clinically important drug interactions involving drugs used in transplantation.

METHODS

The clinical significance of drug interactions involving 5 transplant drugs was evaluated by an expert panel to determine whether alerts should be generated for physicians not involved in the transplant at the time of order entry. Drug interactions included in the analysis were generated from the expert panel, a common drug interaction database, and 2 standard drug interaction references. Responses on the clinical significance were used to calculate the sensitivity, specificity, and positive and negative predictive values for each severity setting of a common electronic drug interaction database.

RESULTS

Overall, the database failed to identify approximately 70% of interactions considered significant by the expert panel. Of the alerts that were generated, >85% were considered clinically significant. The database was most deficient in identifying interactions resulting from additive toxicity.

CONCLUSIONS

To expect a decrease in pADEs caused by drug interactions, the information used to populate CPOE systems must be validated. Establishing consistency and integrity of this information may be a future role for pharmacists.