Clinical decision support systems: great promises for better management of patients’ drug therapy

Opioid metabolism and drug-drug interaction in cancer

Concomitant use of multiple drugs in most patients with cancer may result in drug-drug interactions (DDIs), potentially causing serious adverse effects. These patients often experience unrelieved cancer-related pain (CRP) during and after cancer treatment, which can lead to a reduced quality of life. Opioids can be used as part of a multimodal pain management strategy when non-opioid analgesics are not providing adequate pain relief, not tolerated, or are contraindicated. However, due to their narrow therapeutic window, opioids are more susceptible to adverse events when a DDI occurs. Clinically relevant DDIs with opioids are usually pharmacokinetic, mainly occurring via metabolism by cytochrome P450 (CYP). This article aims to provide an overview of potential DDIs with opioids often used in the treatment of moderate-to-severe CRP and commonly used anticancer drugs such as chemotherapeutics, tyrosine kinase inhibitors (TKIs), or biologics. A DDI-checker tool was used to contextualize the tool-informed DDI assessment outcomes with clinical implications and practice. The findings were compared to observations from a literature search conducted in Embase and PubMed to identify clinical evidence for these potential DDIs. The limited results mainly included case studies and retrospective reviews. Some potential DDIs on the DDI-checker were aligned with literature findings, while others were contradictory. In conclusion, while DDI-checkers are useful tools in identifying potential DDIs, it is necessary to incorporate literature verification and comprehensive clinical assessment of the patient before implementing tool-informed decisions in clinical practice.

Decision-support systems for managing polypharmacy in the elderly: A scoping review

Polypharmacy, the consuming of more than five drugs, is a public health problem. It can lead to many interactions and adverse drug reactions and is very expensive. Therapeutic guidelines for managing polypharmacy in the elderly have been issued, but are highly complex, limiting their use. Decision-support systems have therefore been developed to automate the execution of these guidelines, or to provide information about drugs adapted to the context of polypharmacy. These systems differ widely in terms of their technical design, knowledge sources and evaluation methods. We present here a scoping review of electronic systems for supporting the management, by healthcare providers, of polypharmacy in elderly patients. Most existing reviews have focused mainly on evaluation results, whereas the present review also describes the technical design of these systems and the methodologies for developing and evaluating them. A systematic bibliographic search identified 19 systems differing considerably in terms of their technical design (rule-based systems, documentary approach, mixed); outputs (textual report, alerts and/or visual approaches); and evaluations (impact on clinical practices, impact on patient outcomes, efficiency and/or user satisfaction). The evaluations performed are minimal (among all the systems identified, only one system has been evaluated according to all the criteria mentioned above) and no machine learning systems and/or conflict management systems were retrieved. This review highlights the need to develop new methodologies, combining various approaches for decision support system in polypharmacy.

Physiologically-based Pharmacokinetic Modeling to Assess the Impact of CYP2D6-Mediated Drug-Drug Interactions on Tramadol and O-Desmethyltramadol Exposures via Allosteric and Competitive Inhibition

Tramadol is an opioid medication used to treat moderately severe pain. Cytochrome P450 (CYP) 2D6 inhibition could be important for tramadol, as it decreases the formation of its pharmacologically active metabolite, O‐desmethyltramadol, potentially resulting in increased opioid use and misuse. The objective of this study was to evaluate the impact of allosteric and competitive CYP2D6 inhibition on tramadol and O‐desmethyltramadol pharmacokinetics using quinidine and metoprolol as prototypical perpetrator drugs. A physiologically based pharmacokinetic model for tramadol and O‐desmethyltramadol was developed and verified in PK‐Sim version 8 and linked to respective models of quinidine and metoprolol to evaluate the impact of allosteric and competitive CYP2D6 inhibition on tramadol and O‐desmethyltramadol exposure. Our results show that there is a differentiated impact of CYP2D6 inhibitors on tramadol and O‐desmethyltramadol based on their mechanisms of inhibition. Following allosteric inhibition by a single dose of quinidine, the exposure of both tramadol (51% increase) and O‐desmethyltramadol (52% decrease) was predicted to be significantly altered after concomitant administration of a single dose of tramadol. Following multiple‐dose administration of tramadol and a single‐dose or multiple‐dose administration of quinidine, the inhibitory effect of quinidine was predicted to be long (≈42 hours) and to alter exposure of tramadol and O‐desmethyltramadol by up to 60%, suggesting that coadministration of quinidine and tramadol should be avoided clinically. In comparison, there is no predicted significant impact of metoprolol on tramadol and O‐desmethyltramadol exposure. In fact, tramadol is predicted to act as a CYP2D6 perpetrator and increase metoprolol exposure, which may necessitate the need for dose separation.

Longitudinal Association of a Medication Risk Score With Mortality Among Ambulatory Patients Acquired Through Electronic Health Record Data

The use of electronic health records allows for the application of a novel medication risk score for the rapid identification of ambulatory patients at risk of adverse drug events. We sought to examine the longitudinal association of medication risk score with mortality. This retrospective cohort study included patients whose data were available through electronic health records from multiple health care organizations in the United States that provided data as part of a Patient Safety Organization. Patients were included if they had ≥1 visit and ≥1 medication in their record between January 1, 2011, to June 30, 2017. Cox proportional hazards regression was used to examine the association between continuous and categorized medication risk score with all-cause mortality. Among 427,103 patients, the median age was 50 years (interquartile range, 29-64 years); 61% were female; 50% were White, 11% were Black, and 38% were Hispanic; and 6873 had a death date recorded. Patients 30 to 49 years old had the highest hazard ratios (HRs), followed by the 50- to 64-year-olds and lastly those 65 years or older. Controlling for all covariates, 30- to 49-year-olds with a score of 20 to 30 (versus <10) had a 604% increase in the hazard of death (HR, 7.04; 95% confidence interval [CI], 3.86-12.85), 50- to 64-year-olds had a 254% increase (HR, 3.54; 95% CI, 2.71-4.63), and ≥65-year-olds had an 87% increase (HR, 1.87; 95% CI, 1.67-2.09). The medication risk score was independently associated with death, adjusting for multimorbidities and other conditions. Risk was found to vary by age group and score. Results suggest that pharmaceutical interventions among those with elevated scores could improve medication safety for patients taking multiple medications.

Prevalence and Clinical Significance of Drug-Drug and Drug-Dietary Supplement Interactions among Patients Admitted for Cardiothoracic Surgery in Greece

Background: Drug interactions represent a major issue in clinical settings, especially for critically ill patients such as those with cardiovascular disease (CVD) who require cardiothoracic surgery (CTS) and receive a high number of different medications. Methods: A cross-sectional study aimed at evaluating the exposure and clinical significance of drug–drug (DDIs) and drug–dietary supplement interactions (DDSIs) in patients admitted for CTS in the University Hospital of Crete Greece. DDIs were evaluated regarding underlying pharmacological mechanisms upon admission, preoperation, postoperation, and discharge from CTS clinic. Additionally, upon admission, the use of dietary supplements (DSs) and if patients had informed their treating physician that they were using these were recorded with subsequent analysis of potential DDSIs with prescribed medications. Results: The study employed 76 patients who were admitted for CTS and accepted to participate. Overall, 166 unique DDIs were identified, with 32% of them being related to pharmacokinetic (PK) processes and the rest (68%) were related to possible alterations of pharmacodynamic (PD) action. CVD medications and drugs for central nervous system disorders were the most frequently interacting medications. In total, 12% of the identified DDIs were of serious clinical significance. The frequency of PK-DDIs was higher during admission and discharge, whereas PD-DDIs were mainly recorded during pre- and postoperation periods. Regarding DS usage, 60% of patients were using DSs and perceived them as safe, and the majority had not informed their treating physician of this or sought out medical advice. Analysis of medical records showed 30 potential combinations with prescribed medications that could lead in DDSIs due to modulation of PK or PD processes, and grapefruit juice consumption was involved in 38% of them. Conclusions: An increased burden of DDIs and DDSIs was identified mostly upon admission for patients in CTS clinics in Greece. Healthcare providers, especially prescribing physicians in Greece, should always take into consideration the possibility of DDIs and the likely use of DS products by patients to promote their well-being; this should only be undertaken after receiving medical advice and an evidenced-based evaluation.

Effectiveness of an Advanced Clinical Decision Support System on Clinical Decision-Making Skills in a Call Center Medication Therapy Management Pharmacy Setting: A Pilot Study

(1) Background: There is limited evidence related to the efficacy of advanced clinical decision support systems (CDSS) on the quantity of high-quality clinical recommendations in a pharmacy-related medication therapy management (MTM) setting. The study aimed to assess the effect of an advanced CDSS on the quantity of relevant clinical pharmacist recommendations in a call center MTM setting. (2) Methods: This pre-test/post-test with comparator group study compared clinical skills assessment scores between certified MTM pharmacists in March 2020. A Wilcoxon Signed Rank test assessed the difference between pre- and post-test scores in both groups. (3) Results: Of 20 participants, the majority were less than 40 years old (85%) with a Doctor of Pharmacy degree (90%). Nine were female. Intervention group participants had less than three years of experience as a pharmacist. The control group had less than three years (40%) or seven to ten years (40%) of experience. There was a significant increase in intervention group scores between pre- (median = 3.0, IQR = 3.0) and post-test segments (median = 6.5, IQR = 4.0, p = 0.02). There was no significant change between control group pre- and post-test segments (p = 0.48). (4) Conclusion: Pharmacist exposure to an advanced CDSS was associated with significantly increased quantity of relevant clinical recommendations in an MTM pharmacy setting.

Opioids, Polypharmacy, and Drug Interactions: A Technological Paradigm Shift Is Needed to Ameliorate the Ongoing Opioid Epidemic

Polypharmacy is a common phenomenon among adults using opioids, which may influence the frequency, severity, and complexity of drug–drug interactions (DDIs) experienced. Clinicians must be able to easily identify and resolve DDIs since opioid-related DDIs are common and can be life-threatening. Given that clinicians often rely on technological aids—such as clinical decision support systems (CDSS) and drug interaction software—to identify and resolve DDIs in patients with complex drug regimens, this narrative review provides an appraisal of the performance of existing technologies. Opioid-specific CDSS have several system- and content-related limitations that need to be overcome. Specifically, we found that these CDSS often analyze DDIs in a pairwise manner, do not account for relevant pharmacogenomic results, and do not integrate well with electronic health records. In the context of polypharmacy, existing systems may encourage inadvertent serious alert dismissal due to the generation of multiple incoherent alerts. Future technological systems should minimize alert fatigue, limit manual input, allow for simultaneous multidrug interaction assessments, incorporate pharmacogenomic data, conduct iterative risk simulations, and integrate seamlessly with normal workflow.

Medication-related problems encountered in the Program of All-Inclusive Care for the Elderly: An observational study

OBJECTIVE

To evaluate pharmacist-encountered medication-related problems (MRPs) among the participants of the Program of All-Inclusive Care for the Elderly (PACE).

DESIGN

This was a retrospective analysis of proprietary pharmacy records detailing pharmacist encounters with PACE clinical staff.

SETTING AND PARTICIPANTS

A national provider of pharmacy services to more than 75 PACE organizations. In total, 1057 PACE participants at 69 PACE sites across the United States with documented pharmacist encounters between March and May 2018.

OUTCOME MEASURES

MRPs were classified using the Hepler-Strand taxonomy, and pharmacists' recommendations made to prescribers to resolve these MRPs were classified using a modified Hoth taxonomy. In addition, pharmacists' communication methods and prescribers' responses were analyzed.

RESULTS

Overall, 2004 MRPs were encountered. The most frequent MRPs identified were related to medication safety concerns, including drug interactions (720, 35.9%), adverse drug reactions (ADRs, 356, 17.8%), high doses (270, 13.5%), and unindicated drugs (252, 12.6%). Drug interactions frequently involved competitive inhibition, 3 or more drugs, opioids, anticoagulants, antiplatelets, and antidepressants. Deprescribe medication (561, 24.8%), start alternative therapy (553, 24.4%), change doses (457, 20.2%), and monitor (243, 10.7%) were the top 4 types of recommendations made by pharmacists. Among 1730 responses obtained from PACE prescribers, 78.1% (n = 1351) of pharmacists' recommendations were accepted. Compared with electronic communication, telephonic communication was associated with more acceptance and less prescriber nonresponse (χ² = 78.5, P < 0.001).

CONCLUSION

Pharmacists identified a substantial number of MRPs in PACE, especially those related to medication safety such as drug interactions and ADRs. In this practice setting, significant collaboration occured between pharmacists and PACE prescribers, as evidenced by the rate of prescribers' acceptance of pharmacists' recommendations. Further research is needed to fully evaluate the economic, clinical, and humanistic outcomes associated with pharmacists' encounters in PACE.

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis

BACKGROUND

Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care.

OBJECTIVE

The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data.

METHODS

The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors.

RESULTS

Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters.

CONCLUSIONS

MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians' skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments.