A pharmacokinetic drug-drug interaction model of simvastatin and clarithromycin in humans

Reduced Effectiveness of Interruptive Drug-Drug Interaction Alerts after Conversion to a Commercial Electronic Health Record

BACKGROUND

Drug-drug interaction (DDI) alerts in electronic health records (EHRs) can help prevent adverse drug events, but such alerts are frequently overridden, raising concerns about their clinical usefulness and contribution to alert fatigue.

OBJECTIVE

To study the effect of conversion to a commercial EHR on DDI alert and acceptance rates.

DESIGN

Two before-and-after studies.

PARTICIPANTS

3277 clinicians who received a DDI alert in the outpatient setting.

INTERVENTION

Introduction of a new, commercial EHR and subsequent adjustment of DDI alerting criteria.

MAIN MEASURES

Alert burden and proportion of alerts accepted.

KEY RESULTS

Overall interruptive DDI alert burden increased by a factor of 6 from the legacy EHR to the commercial EHR. The acceptance rate for the most severe alerts fell from 100 to 8.4%, and from 29.3 to 7.5% for medium severity alerts (P < 0.001). After disabling the least severe alerts, total DDI alert burden fell by 50.5%, and acceptance of Tier 1 alerts rose from 9.1 to 12.7% (P < 0.01).

CONCLUSIONS

Changing from a highly tailored DDI alerting system to a more general one as part of an EHR conversion decreased acceptance of DDI alerts and increased alert burden on users. The decrease in acceptance rates cannot be fully explained by differences in the clinical knowledge base, nor can it be fully explained by alert fatigue associated with increased alert burden. Instead, workflow factors probably predominate, including timing of alerts in the prescribing process, lack of differentiation of more and less severe alerts, and features of how users interact with alerts.

A pharmacokinetic model of drug-drug interaction between clopidogrel and omeprazole at CYP2C19 in humans

BACKGROUND

Clopidogrel is a thienopryridine antiplatelet agent commonly used in the management of cardiovascular diseases. Clopidogrel is metabolized by hepatic CYP2C19 and CYP2B6, therefore, co-administration of clopidogrel and CYP2C19 inhibitors can alter pharmacokinetics of clopidogrel. Omeprazole is a proton pump inhibitor used for decreasing gastric acid production. Omeprazole is known to be a potent inhibitor of CYP2C19. Thus when the drugs are simultaneously administered, clopidogrel plasma concentration levels can be increased. However, plasma levels of the active metabolite of clopidogrel can be significantly decreased, thereby, its antiplatelet activity is reduced.

OBJECTIVES

We aimed to develop a mathematical model describing a drug-drug interaction between clopidogrel and omeprazole in humans.

METHODS

Searching for pharmacokinetic interaction studies between clopidogrel and omeprazole in humans was performed in PubMed. Six studies were selected into our modeling purposes to develop 3 mathematical models (i.e. 4 studies for clopidogrel alone, 1 study for omeprazole alone and 1 study for clopidogrel-omeprazole interaction). Subsequently, concentration-time course data from the selected studies were extracted. Computer codes and simulations were performed using the Advanced Continuous Simulating Language Extreme (ACSLX) program.

RESULTS

We successfully developed 3 mathematical models which are able to describe all of the datasets.

CONCLUSIONS

Our clopidogrel-omeprazole pharmacokinetic interaction model with a description of competitive inhibition at CYP2C19 could successfully describe concentration-time courses from the selected datasets. Our interaction model may be useful in predicting plasma levels of clopidogrel and its active metabolite.

Adverse Drug Reactions in the Intensive Care Unit

Adverse drug reactions (ADRs) are undesirable effects of medications used in normal doses [1]. ADRs can occur during treatment in an intensive care unit (ICU) or result in ICU admissions. A meta-analysis of 4139 studies suggests the incidence of ADRs among hospitalized patients is 17% [2]. Because of underreporting and misdiagnosis, the incidence of ADRs may be much higher and has been reported to be as high as 36% [3]. Critically ill patients are at especially high risk because of medical complexity, numerous high-alert medications, complex and often challenging drug dosing and medication regimens, and opportunity for error related to the distractions of the ICU environment [4]. Table 1 summarizes the ADRs included in this chapter.