Clinical usefulness of electronic drug-drug interaction checking in the care of cardiovascular surgery inpatients

Interaction alerts: A comparison of classifications and recommendations for clinical management between Janusmed and three other knowledge resources

Classifications of drug interaction alerts differ between knowledge resources, but agreement regarding recommendations for clinical management is less explored. Starting from the medication lists of 274 older patients with ≥2 drugs, all unique drug pairs that triggered a clinically significant interaction alert in Janusmed were included: 100 Category C (manageable by, e.g. dose adjustment) and nine Category D interactions (should be avoided). Out of 109 C/D alerts in Janusmed, 89 (82%), 75 (69%) and 45 (41%) drug pairs triggered an alert of similar clinical significance in Lexicomp, Micromedex® and Stockley's Drug Interactions/Checker (Stockley), respectively. Eight (7%), 20 (18%) and 10 (9%) drug pairs did not trigger any alert in these resources. For 81 (74%), 81 (74%) and 94 (86%) drug pairs, Lexicomp, Micromedex and Stockley provided at least one recommendation for clinical management similar to those provided by Janusmed. For 16 (15%), 9 (8%) and 21 (19%) drug pairs, these resources provided recommendation(s) entirely in agreement with Janusmed. Although many drug pairs elicit alerts of similar significance, and partly concordant recommendations, a non-negligible proportion do not. The findings encourage medical/pharmaceutical reflection by prescribing clinicians and dispensing pharmacists; recommendations provided by knowledge resources vary considerably and cannot be considered definite.

Appropriateness of Alerts and Physicians’ Responses with a Medication-related Clinical Decision Support System (Preprint)

Background

Alert fatigue is unavoidable when many irrelevant alerts are generated in response to a small number of useful alerts. It is necessary to increase the effectiveness of the clinical decision support system (CDSS) by understanding physicians’ responses.

Objective

This study aimed to understand the CDSS and physicians’ behavior by evaluating the clinical appropriateness of alerts and the corresponding physicians’ responses in a medication-related passive alert system.

Methods

Data on medication-related orders, alerts, and patients’ electronic medical records were analyzed. The analyzed data were generated between August 2019 and June 2020 while the patient was in the emergency department. We evaluated the appropriateness of alerts and physicians’ responses for a subset of 382 alert cases and classified them.

Results

Of the 382 alert cases, only 7.3% (n=28) of the alerts were clinically appropriate. Regarding the appropriateness of the physicians’ responses about the alerts, 92.4% (n=353) were deemed appropriate. In the classification of alerts, only 3.4% (n=13) of alerts were successfully triggered, and 2.1% (n=8) were inappropriate in both alert clinical relevance and physician’s response. In this study, the override rate was 92.9% (n=355).

Conclusions

We evaluated the appropriateness of alerts and physicians’ responses through a detailed medical record review of the medication-related passive alert system. An excessive number of unnecessary alerts are generated, because the algorithm operates as a rule base without reflecting the individual condition of the patient. It is important to maximize the value of the CDSS by comprehending physicians’ responses.

Effects of piperacillin/tazobactam or cefepime on folinate dose in patients receiving high-dose methotrexate: A retrospective cohort study using Japanese administrative claims data

INTRODUCTION

Delayed methotrexate (MTX) clearance with the co-administration of piperacillin/tazobactam (PIPC/TAZ) has been reported. Penicillins have been associated with reduced MTX clearance but the evidence is limited. There are no cases described with cefepime but penicillins are listed as interacting with MTX. We aimed to reveal whether the co-administration of PIPC/TAZ or CFPM affects MTX clearance using data from an administrative database.

METHODS

We used data from the JMDC database, a large insurance claims database constructed in Japan. We included patients who were prescribed PIPC/TAZ or CFPM between days 1 and 3 in high-dose MTX (HD-MTX). We compared one co-administration episode (with PIPC/TAZ or CFPM) to one control episode (without), as a match-control study of two different episodes in the same patient. The primary outcomes were the duration and cumulative dose of leucovorin (LV) as a surrogate indicator of delayed MTX clearance.

RESULTS

Three patients who were co-administered PIPC/TAZ and 16 patients who were co-administered CFPM with HD-MTX were included. In the PIPC/TAZ group, the duration and the cumulative doses of LV were similar in co-administration and control episode (median 3.0 vs. 3.0 days and 288.0 vs. 219.0 mg). In the CFPM group, the duration and the cumulative doses of LV were not significantly different in co-administration and control episode (3.0 vs. 4.0 days and 169.5 vs. 258.0 mg).

CONCLUSIONS

Our findings revealed that PIPC/TAZ did not necessarily cause a delay in MTX clearance during HD-MTX therapy. Moreover, the co-administration of CFPM with HD-MTX did not affect MTX clearance.

Evaluating the appropriateness of clinical decision support alerts: A case study

RATIONALE, AIMS, AND OBJECTIVES

Clinical decision support (CDS) generates excessive alerts that disrupt the workflow of clinicians. Therefore, inefficient clinical processes that contribute to the misfit between CDS alert and workflow must be evaluated. This study evaluates the appropriateness of CDS alerts in supporting clinical workflow from a socio-technical perspective.

METHOD

A qualitative case study evaluation was conducted at a 620-bed public teaching hospital in Malaysia using interview, observation, and document analysis to investigate the features and functions of alert appropriateness and workflow-related issues in cardiological and dermatological settings. The current state map for medication prescribing process was also modelled to identify problems pertinent to CDS alert appropriateness.

RESULTS

The main findings showed that CDS was not well designed to fit into a clinician's workflow due to influencing factors such as technology (usability, alert content, and alert timing), human (training, perception, knowledge, and skills), organizational (rules and regulations, privacy, and security), and processes (documenting patient information, overriding default option, waste, and delay) impeding the use of CDS with its alert function. We illustrated how alert affect workflow in clinical processes using a Lean tool known as value stream mapping. This study also proposes how CDS alerts should be integrated into clinical workflows to optimize their potential to enhance patient safety.

CONCLUSION

The design and implementation of CDS alerts should be aligned with and incorporate socio-technical factors. Process improvement methods such as Lean can be used to enhance the appropriateness of CDS alerts by identifying inefficient clinical processes that impede the fit of these alerts into clinical workflow.

Potential drug-drug interactions in hospitalized pediatric patients with respiratory disorders: a retrospective review of clinically important interactions

Background Hospitalized pediatric patients are at an increased risk of experiencing potential drug-drug interactions (pDDIs) due to polypharmacy and the unlicensed and off-label administration of drugs. The aim of this study is to characterize clinically significant pDDIs in pediatric patients hospitalized in a tertiary respiratory center. Methods A retrospective analysis of medications prescribed to pediatric patients admitted to the pediatric ward (PW) and pediatric intensive care unit (PICU) of a respiratory referral center was carried out over a six-month period. The pDDIs were identified using the Lexi-Interact database and considered as clinically relevant according to the severity rating as defined in the database. Frequency, drug classes, mechanisms, clinical managements, and risk factors were recorded for these potential interactions. Results Eight hundred and forty-five pDDIs were identified from the analysis of 176 prescriptions. Of the total pDDIs, 10.2% in PW and 14.6% in PICU were classified as clinically significant. Anti-infective agents and central nervous system drugs were the main drug classes involved in clinically significant pDDIs as object and/or precipitant drugs. A higher number of medications [odds ratio (OR): 4.8; 95% confidence interval (CI): 2.0-11.4; p < 0.001] and the existence of a nonrespiratory disease, which led to a respiratory disorder (OR: 3.8; 95% CI: 1.40-10.4; p < 0.05), were the main risk factors associated with an increased incidence of pDDIs. Conclusions A high and similar risk of pDDIs exists in pediatric patients with respiratory disorders hospitalized in PW and PICU. The patients prescribed a higher number of medications and presenting respiratory symptoms induced by a nonrespiratory disease require extra care and monitoring. Pediatricians should be educated about clinically significant DDIs for highly prescribed medications in their settings in order to take preventive measures and safeguard patient safety.

Drug-drug interactions in patients undergoing chemoradiotherapy and the impact of an expert team intervention

Background Several studies have examined the drug-drug interaction patterns in different patient populations and treatment settings; however, there is a need, particularly in the field of oncology and radiotherapy, for evaluating methods targeted towards preventing potential drug-drug interactions. One of the measures proposed is identifying potential interactions using computer programs and their evaluation by pharmacologists or clinical pharmacists, thereby providing clinically relevant information to the treating physician regarding the required prescription changes. Objective To determine the prevalence of potential drug-drug interactions in patients receiving chemoradiotherapy and assess the usefulness of expert team recommendations in minimizing interactions. Setting Patients admitted to the radiotherapy and oncology ward of a tertiary care teaching hospital in Karnataka, India. Method We conducted a prospective, cross-sectional study of prescriptions written for patients receiving chemoradiotherapy. Prescriptions containing two or more drugs, at least one of the drugs being an anticancer drug, were analyzed. They were screened for potential drug-drug interactions using the Lexicomp® drug interaction software. The interactions were classified as X, drug combination to be avoided; D, modification of therapy to be considered; and C, therapy to be monitored, as per the Lexicomp criteria. Main outcome measure The number of drug-drug interactions detected that were accepted by the treating radio-oncologist as requiring prescription change before and after the prescription review by an expert team. Results Two hundred twenty-three prescriptions were screened for the presence of drug-drug interactions; 106 prescriptions (47.53%) containing 620 drugs and 211 drug-drug interactions were identified. Of the 211 interactions identified, 6.64% (14/211), 18.48% (39/211), and 74.88% (158/211) drug-drug interactions belonged to category X, D, and C, respectively. Twenty-seven (50.94%) of the 53 category X and D interactions identified were accepted the oncologist as requiring a change in the prescription; an additional 13 (24.53%) interactions were identified as significant by the expert team, and 11 (84.62%) of these were accepted by the oncologist. Conclusion A system of alerting the treating physician to a potential drug-drug interaction leads to avoidance of prescription of the interacting drug combination, and the assistance by an expert team adds significantly to avoidance of clinically relevant drug interactions.

Are drug-drug interactions a real clinical concern?

Aim:

Although drug-drug interactions (DDIs) cause major adverse drug reactions (ADRs) in patients under polypharmacy, the risk of some specific DDIs may be overrated in literature and different software. This study was conducted to determine the frequency and type of potential and clinically significant DDIs among inpatients admitted in a tertiary care hospital in South India.

Materials and Methods:

This longitudinal study was conducted for 30 days. Preformatted forms were used to collect data on the second day of admission. “Medscape Drug Interaction Checker” was used to evaluate and grade the DDIs. All the potential serious DDIs were intimated to the treating physicians and their responses in the prescriptions were noted. The same patients were followed up to evaluate the occurrence of any clinically significant DDIs.

Results:

A total of 763 drugs with 125 discrete types were prescribed in 155 patients with an average of 4.9 drugs per patient. One hundred and eight minor, 169 significant, and 24 serious potential DDIs were identified. Patient's age did not correlate, but number of drugs prescribed strongly correlated (P < 0.001) with the incidence of different types of DDIs. The prescription was modified in only 6 (25%) cases where potential serious DDIs were reported. Interestingly, no ADRs or impaired efficacy was observed due to the potential serious DDIs.

Conclusion:

There was a disparity between the potential and clinically relevant DDIs. Hence, clinical prudency is required before changing prescription due to potential DDIs reported by different software.

Identify and categorize drug-related problems in hospitalized surgical patients in China

Background Data is lacking on types and severities of drug-related problems (DRPs) in hospitalized surgical patients in China. Objective To identify and categorize types and causes of DRPs, and to assess severities of these DRPs. Setting An academic teaching hospital in Chongqing, China. Method We retrospectively reviewed all medication orders for patients in six surgical departments during a six-month period. DRPs were classified using the Pharmaceutical Care Network Europe (PCNE) classification, and the severity ratings of these DRPs were based on the National Coordinating Council for Medication Error Reporting and Prevention (NCCMERP) classification. Main outcome measure The number, types, causes and severities of the DRPs. Results A total of 291,944 medication orders in 10,643 patients were reviewed, and 3548 DRPs were identified. The average DRP number per patient was 0.3. The most common problem was treatment effectiveness (39.9%) and the major cause of the problems was dose selection (47.0%). Total 80.1% of the DRPs were rated at severity categories B to D (causing no or potential harm), whereas 19.9% were rated as categories E to H (causing actual harm). Conclusion DRPs are common in surgical patients, and prospective pharmacist medication order review services are needed to improve patients' pharmaceutical care.

Improving medication-related clinical decision support

PURPOSE

Current uses of medication-related clinical decision support (CDS) and recommendations for improving these systems are reviewed.

SUMMARY

Using a systematic approach, articles published from 2007 through 2014 were identified in MEDLINE and EMBASE using MeSH terms and keywords relating to the 5 basic medication-related CDS functionalities. A total of 156 full-text articles and 28 conference abstracts were reviewed across each of the 5 areas: drug-drug interaction (DDI) checks (n = 78), drug allergy checks (n = 20), drug dose support (n = 55), drug duplication checks (n = 11), and drug formulary support (n = 20). The success of medication-related CDS depends on users finding the alerts valuable and acting on the information received. Improving alert specificity and sensitivity is important for all domains. Tiering is important for improving the acceptance of DDI alerts. The ability to perform appropriate cross-sensitivity checks is key to producing appropriate drug allergy checks. Drug dosage alerts should be individualized and deliver practical recommendations. How the system is configured to identify certain drug duplications is important to prevent possible patient toxicity. Accurate knowledge databases are needed to produce relevant drug formulary alerts and encourage formulary adherence. Medication-related CDS is still relatively immature in some organizations and has substantial room for improvement. For example, decision support should consider more patient-specific factors, human factors principles should always be considered, and alert specificity must be improved in order to reduce alert fatigue.

CONCLUSION

Standardization, integration of patient-specific parameters, and consideration of human factors design principles are central to realizing the potential benefits of medication-related CDS.

The Community Pharmacist's Role in Reducing Cardiovascular Risk Factors in Lebanon: A Longitudinal Study

OBJECTIVE

To assess the role of the pharmacist in modifying risk factors for cardiovascular disease (CVD) among Lebanese adults in urban and rural areas.

METHODS

In a prospective survey, 865 out of 1,000 participants aged ≥45 years, previously interviewed, agreed to be followed at 1 and 2 years time points. Parameters including blood pressure, lipid profile, blood glucose, average number of risk factors, and atherosclerotic CVD (ASCVD) risk were assessed and evaluated at the beginning of the study, then after 1 and 2 years.

RESULTS

During both follow-ups, the mean average body mass index and systolic blood pressure decreased significantly and the lipid profile improved significantly. Further significant improvements in ASCVD risk occurred during the second follow-up. Monitoring parameters revealed significant improvements as well.

CONCLUSION

This study showed that a plan that includes pharmacists, who regularly monitor and follow-up patients, could improve CVD prevention through the reduction of risk factors.

Cytochrome P450 interactions are common and consequential in Massachusetts hospital discharges

Despite the recognition that drug-drug interactions contribute substantially to preventable health-care costs, the prevalence of such interactions related to the cytochrome P450 system in clinical practice remains poorly characterized. This study drew retrospective hospital discharge cohorts from a large health claims data set and a large health system data set. For every hospital discharge, frequency of co-occurrence of substrates and inducers or inhibitors at cytochrome P450 2D6, 2C19, 3A4 and 1A2 were determined. A total of 124 520 individuals in the state of Massachusetts (health claims cohort) and 77 026 individuals in two large academic medical centers (electronic health record (EHR) cohort) were examined. In the claims cohort, 35 157 (28.2%) exhibited at least one CYP450 drug-drug interaction at hospital discharge, whereas in the EHR cohort, 36 750 (47.7%) had at least one interaction. The most commonly affected CYP450 systems were 2C19 and 2D6, with putative interactions observed in at least 10% of individuals at discharge in each cohort. Odds of hospital readmission within 90 days among those discharged with at least one interaction were 10-16% greater, with mean health-care cost $574/month greater over the subsequent year, after adjusting for age, sex, insurance type, total number of medications prescribed, Charlson comorbidity score and presence or absence of a psychiatric diagnosis. These two distinct clinical data types show that CYP450 drug-drug interactions are prevalent and associated with greater probability of early hospital readmission and greater health-care cost, despite the widespread availability and application of drug-drug interaction checking software.

Clinical-pharmacist intervention reduces clinically relevant drug-drug interactions in patients with heart failure: A randomized, double-blind, controlled trial

BACKGROUND

Incidence of drug-drug interactions (DDIs) increases with complexity of treatment and comorbidities, as in heart failure (HF). This randomized, double-blind study evaluated the intervention of the pharmacist on prevalence of clinically relevant DDIs (NCT01855165).

METHODS

Patients admitted with HF were screened for clinically relevant DDIs, and randomized to control or intervention. All attending physicians received standard advice about pharmacological therapy; those in the intervention group also received alerts about clinically relevant DDIs. Primary endpoint was DDI at discharge and secondary were re-hospitalization or death during follow-up.

RESULTS

Of 213 patients, 51 (mean age, 79 ± 6 years; male, 47%) showed 66 clinically relevant DDIs and were randomized. For intervention (n=26) versus control (n=25), the number of patients with and the number of DDIs were significantly lower at discharge: 8 vs. 18 and 10 vs. 31; p=0.003 and 0.0049, respectively. Over a 6 month follow-up period, 11 control and 9 intervention patients were re-hospitalized or died (p>0.2 for all). No significant differences were seen between control and intervention for patients with eGFR <60 mL/min/1.73 m(2) (78%) for re-hospitalization or death (10 vs. 7; p=0.74).

CONCLUSIONS

Pharmacist intervention significantly reduces the number of patients with clinically relevant DDIs, but not clinical endpoints 6 months from discharge.

Drug-drug interaction software in clinical practice: a systematic review

PURPOSE

Several electronic databases which report the prevalence of drug-drug interactions (DDIs) are used as a tool for evaluation of potentially harmful DDIs. The aim of our review was to evaluate the usability and appropriateness of commercially available electronic databases which assess the prevalence of potential DDIs.

METHODS

The systematic electronic literature search was conducted with the following search terms: "database" AND "software," and "drug-drug interactions" AND "database," and the inclusion and exclusion criteria were applied in order to identify the publications of interest.

RESULTS

A total of 3766 papers were identified by systematic search. After applying inclusion and exclusion criteria, 38 publications were included in the analysis. The most commonly used software in the included studies was Micromedex® Drug-Reax, for which some authors argue to be the most reliable due to highest sensitivity. It gives information about clinical consequences of DDIs, classifies underlying mechanism and onset of the adverse outcome (either rapid, or delayed) as well as severity (such as minor, moderate, or major), and provides the level of evidence which supports this information. This data is also provided by Drug Interaction Facts®, Lexi-Interact®, and Pharmavista®. A small number of studies which compared assessment of DDIs with electronic database and the clinician's assessment showed large discrepancy in number and relevance of detected DDIs. The overlap was in some cases as low as 11 %.

CONCLUSION

The deficiency of clinical relevance of detected DDIs should be addressed in the upcoming research as it would provide more relevant information to the prescribers' in clinical practice.

Optimization of drug-drug interaction alert rules in a pediatric hospital's electronic health record system using a visual analytics dashboard

OBJECTIVE

To develop and evaluate an electronic dashboard of hospital-wide electronic health record medication alerts for an alert fatigue reduction quality improvement project.

METHODS

We used visual analytics software to develop the dashboard. We collaborated with the hospital-wide Clinical Decision Support committee to perform three interventions successively deactivating clinically irrelevant drug-drug interaction (DDI) alert rules. We analyzed the impact of the interventions on care providers' and pharmacists' alert and override rates using an interrupted time series framework with piecewise regression.

RESULTS

We evaluated 2 391 880 medication alerts between January 31, 2011 and January 26, 2014. For pharmacists, the median alert rate prior to the first DDI deactivation was 58.74 alerts/100 orders (IQR 54.98-60.48) and 25.11 alerts/100 orders (IQR 23.45-26.57) following the three interventions (p<0.001). For providers, baseline median alert rate prior to the first round of DDI deactivation was 19.73 alerts/100 orders (IQR 18.66-20.24) and 15.11 alerts/100 orders (IQR 14.44-15.49) following the three interventions (p<0.001). In a subgroup analysis, we observed a decrease in pharmacists' override rates for DDI alerts that were not modified in the system from a median of 93.06 overrides/100 alerts (IQR 91.96-94.33) to 85.68 overrides/100 alerts (IQR 84.29-87.15, p<0.001). The medication serious safety event rate decreased during the study period, and there were no serious safety events reported in association with the deactivated alert rules.

CONCLUSIONS

An alert dashboard facilitated safe rapid-cycle reductions in alert burden that were temporally associated with lower pharmacist override rates in a subgroup of DDIs not directly affected by the interventions; meanwhile, the pharmacists' frequency of selecting the 'cancel' option increased. We hypothesize that reducing the alert burden enabled pharmacists to devote more attention to clinically relevant alerts.

A study on drug-drug interactions through prescription analysis in a South Indian teaching hospital

OBJECTIVE

The objective of this study was to assess the drug-drug interactions (DDIs) through prescription analysis among the inpatients of a South Indian teaching hospital.

METHODS

The study was a prospective observational prescription analysis conducted for a period of 6 months, from October 2010 to March 2011. The prescriptions having two or more drugs and where a DDI was suspected were selected by the physician in charge of the ward. The drugs in the prescription were then entered into the drug interaction checker software. The DDIs were classified based on the mechanism of interactions, severity of interactions, relation to the number of drugs prescribed, and disease conditions were also determined.

RESULTS

A total of 204 prescriptions were analyzed, of which 186 prescriptions had 856 DDIs. Most of the DDIs were pharmacokinetic drug interactions (42%) followed by unknown mechanisms (34%) and pharmacodynamic mechanisms (24%). The study findings showed that the prescriptions for cardiovascular with respiratory disease conditions had the greatest number of drug interactions on average. A severity assessment showed that majority of the DDIs were moderate (70%) followed by minor (28%). The study results showed that as the number of drugs increases in a prescription, the number of DDIs also increases. The interventions determined showed that dosage adjustment (12%) was to be followed in most of the DDIs.

CONCLUSION

This study assists in understanding the factors associated with DDIs that can help in safe and effective use of drugs in the future.