Analysis of consensus among drug interaction databases with regard to combinations of psychotropics

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.

Prevalence of potentially harmful multidrug interactions on medication lists of elderly ambulatory patients

Background

It has been hypothesized that polypharmacy may increase the frequency of multidrug interactions (MDIs) where one drug interacts with two or more other drugs, amplifying the risk of associated adverse drug events (ADEs). The main objective of this study was to determine the prevalence of MDIs in medication lists of elderly ambulatory patients and to identify the medications most commonly involved in MDIs that amplify the risk of ADEs.

Methods

Medication lists stored in the electronic health record (EHR) of 6,545 outpatients ≥60 years old were extracted from the enterprise data warehouse. Network analysis identified patients with three or more interacting medications from their medication lists. Potentially harmful interactions were identified from the enterprise drug-drug interaction alerting system. MDIs were considered to amplify the risk if interactions could increase the probability of ADEs.

Results

MDIs were identified in 1.3 % of the medication lists, the majority of which involved three interacting drugs (75.6 %) while the remainder involved four (15.6 %) or five or more (8.9 %) interacting drugs. The average number of medications on the lists was 3.1 ± 2.3 in patients with no drug interactions and 8.6 ± 3.4 in patients with MDIs. The prevalence of MDIs on medication lists was greater than 10 % in patients prescribed bupropion, tramadol, trazodone, cyclobenzaprine, fluoxetine, ondansetron, or quetiapine and greater than 20 % in patients prescribed amiodarone or methotrexate. All MDIs were potentially risk-amplifying due to pharmacodynamic interactions, where three or more medications were associated with the same ADE, or pharmacokinetic, where two or more drugs reduced the metabolism of a third drug. The most common drugs involved in MDIs were psychotropic, comprising 35.1 % of all drugs involved. The most common serious potential ADEs associated with the interactions were serotonin syndrome, seizures, prolonged QT interval and bleeding.

Conclusions

An identifiable number of medications, the majority of which are psychotropic, may be involved in MDIs in elderly ambulatory patients which may amplify the risk of serious ADEs. To mitigate the risk, providers will need to pay special attention to the overlapping drug-drug interactions which result in MDIs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02594-z.

Comparison of potential psychiatric drug interactions in six drug interaction database programs: A replication study after 2 years of updates

OBJECTIVE

Drug interaction database programs are a fundamental clinical tool. In 2018, we compared the category of potential drug-drug interaction (DDI) provided by six drug interaction database programs for 100 drug interaction pairs including psychiatric drugs, and found the category often differed. This study replicated the comparison in 2020 after 2 years of updates to all six drug interaction database programs.

METHODS

The 100 drug pairs included 94 different drugs: 67 pairs with a psychiatric and non-psychiatric drug, and 33 pairs with two psychiatric drugs. The assigned category of potential DDI for the drug pairs was compared using percent agreement and Fleiss kappa statistic of interrater reliability.

RESULTS

Despite 67 updates involving 46 of the 100 drug pairs, differences remained. The overall percent agreement among the six drug interaction database programs for the category of potential DDI was 67%. The interrater agreement results did not change. The Fleiss kappa overall interrater agreement was fair. The kappa agreement for a drug pair with any severe category rating was substantial, and the kappa agreement for a drug pair with any major category rating was fair.

CONCLUSIONS

Physicians should be aware of the inconsistency among drug interaction database programs in the category of potential DDI for drug pairs including psychiatric drugs. Additionally, the category of potential DDI for a drug pair may change over time. This study highlights the importance of ongoing international efforts to standardize methods used to define and classify potential DDI.

The Prevalence of Selected Potential Drug-Drug Interactions of Analgesic Drugs and Possible Methods of Preventing Them: Lessons Learned From the Analysis of the Real-World National Database of 38 Million Citizens of Poland

Introduction: Drug-drug interactions may lead to poor health outcomes, as well as increased costs and utilization of healthcare services. Unfortunately, real-world data continuously prove high prevalence of potential drug-drug interactions (pDDIs) worldwide. Among identified drivers, ageing, multimorbidity and polypharmacy play a very important role. With these factors being widespread, the need for implementation of strategies minimizing the burden of pDDIs becomes an urgency. This, however, requires a better understanding of the prevalence of pDDIs and the underlying causative factors.

Aim of study: To assess the real-world prevalence of pDDIs and its characteristics in the general population of Poland, using analgesic drugs as a model, and to find out whether pDDIs are caused by prescribing coming from the very same prescribers (co-prescribing).

Methods: A retrospective analysis of the 2018 dispensation data of the National Health Fund (NHF) - the only Polish public healthcare payer organization with nationwide coverage. We searched for selected pDDIs of non-steroidal anti-inflammatory drugs (NSAIDs) with antihypertensives, other NSAIDs (double use), oral glucocorticoids, oral anticoagulants, selective serotonin reuptake inhibitors (SSRIs), serotonin–norepinephrine reuptake inhibitors (SNRIs), and antiplatelet drugs; as well as opioides with SSRIs, SNRIs, gabapentinoids, and benzodiazepines. A pDDI was deemed present if two drugs standing in a possible conflict were dispensed within the same calendar month.

Results: Out of 38.4 million citizens of Poland, 23.3 million were dispensed prescribed drugs reimbursed by NHF in 2018. In this cohort, we have identified 2,485,787 cases of analgesic drug pDDIs, corresponding with 6.47% of the Polish population. Out of these, the most prevalent pDDI was caused by “NSAIDs + antihypertensives” (1,583,575 cases, i.e., 4.12% of the Polish population), followed by “NSAIDs + NSAIDs” (538,640, 1.40%) and “NSAIDs + glucocorticoids” (213,504, 0.56%). The most persistent pDDIs among those studied were caused by “Opioids + Gabapentinoids” (2.19, 95%CI: 2.16–2.22 months). On average, 76.63% of all cases of pDDIs were caused by drugs prescribed by the very same prescribers.

Conclusion: Based on high-quality, nationwide data, we have found a high prevalence of analgesic drugs-related pDDIs in Poland. Over ¾ of the identified pDDIs were caused by co-prescribing, i.e., prescriptions issued by the same prescribers. The significance of the problem, illustrated with our findings on analgesic drugs-related pDDIs in Poland, deserves much more scientific and policymaker attention.

Review of Questions Concerning Clinical Drug Interactions in ADHD Treatment From Physicians in Norway

Pharmacological treatment of attention deficit hyperactivity disorder (ADHD) is challenging due to a wide age span among patients, risk of reduced adherence, and comorbidities like psychiatric disorders and drug addiction. Drugs used for ADHD are associated with risk of interactions and adverse drug reactions due to their potent pharmacological effect. In this brief report we aimed to describe real-world problem areas concerning interactions in pharmacotherapy of ADHD. We reviewed questions to a Norwegian drug information center from physicians concerning drug-drug interactions involving ADHD drugs in the last 10-year period. Questions were retrieved by a combination of indexed and Boolean database searches, in addition to manual inspection. ADHD drugs and interacting drugs were defined according to the Anatomical Therapeutic Chemical (ATC) classification system. Interactions were classified by use of Stockley’s Interactions Checker (SIC). Answers were examined with regard to whether the advice from the drug information center was more restrictive, similar or more liberal than SIC when assessing drug combinations. We retrieved 61 questions that included assessment of 96 drug combinations, and found 33 potential interactions according to SIC. Methylphenidate was involved in more than 50% of the interactions, and interacting drugs were in nearly 70% of the cases from ATC-group N (Nervous system) with antidepressants most frequently involved. Seventy percent of the interactions were pharmacodynamic, and interactions were frequently described as potentially severe although they were based on theoretical evidence. All the 33 interactions could be handled with monitoring or adjusting dose or with informative measures, and none was contraindicated according to SIC. More than 90% of the questions came from physicians in hospitals or outpatient specialist practice, and questions mainly concerned adults. In 75% of the drug combinations that involved ADHD drugs, we found similar advice from SIC and the drug information center. Our results suggest that future drug information efforts in ADHD treatment to clinicians, including specialists in the field, should focus on psychotropic interactions.

Potential Drug interactions with Drugs used for Bipolar Disorder: A Comparison of 6 Drug Interaction Database Programs

Background Patients with bipolar disorder frequently experience polypharmacy, putting them at risk for clinically significant drug-drug interactions (DDI). Online drug interaction database programs are used to alert physicians, but there are no internationally recognized standards to define DDI. This study compared the category of potential DDI returned by 6 commercial drug interaction database programs for drug interaction pairs involving drugs commonly prescribed for bipolar disorder.

Methods The category of potential DDI provided by 6 drug interaction database programs (3 subscription, 3 open access) was obtained for 125 drug interaction pairs. The pairs involved 103 drugs (38 psychiatric, 65 nonpsychiatric); 88 pairs included a psychiatric and nonpsychiatric drug; 37 pairs included 2 psychiatric drugs. Every pair contained at least 1 mood stabilizer or antidepressant. The category provided by 6 drug interaction database programs was compared using percent agreement and Fleiss kappa statistic of interrater reliability.

Results For the 125 drug pairs, the overall percent agreement among the 6 drug interaction database programs was 60%; the Fleiss kappa agreement was slight. For drug interaction pairs with any category rating of severe (contraindicated), the kappa agreement was moderate. For drug interaction pairs with any category rating of major, the kappa agreement was slight.

Conclusion There is poor agreement among drug interaction database programs for the category of potential DDI involving psychiatric drugs. Drug interaction database programs provide valuable information, but the lack of consistency should be recognized as a limitation. When assistance is needed, physicians should check more than 1 drug interaction database program.