Marianne Kuijvenhoven

Introduction: Pharmacist-led medication reviews are increasingly recognised for generating cost savings within the hospital. However, no cost-analysis has investigated the budget impact of junior pharmacists conducting medication reviews under supervision of clinical pharmacists, nor included recommendations to start-, increase-, or monitor medications. Aim: To assess the budget impact of medication reviews by supervised junior pharmacists across hospital wards, explore budget impact differences between drug classes, and identify patient predictors that potentially influence the budget impact. Method: Data of medication reviews were collected over a 19-month period in patients with polypharmacy (≥ 5 medications) who had at least one additional risk factor. We developed a cost model over a one-year horizon, from the hospital perspective. Intervention costs were derived from measured labour time per medication review and salary of junior- and clinical pharmacists. Cost avoidance from potential preventable medication-related readmissions were based on admission time, admission costs and an estimate of preventable medication-related admissions (4.8%). Costs and savings from medication recommendations were aggregated using drug price per daily defined dose and its predicted days of therapy per year, and clustered by drug class. Scenario analyses tested the robustness of medication recommendation savings to account for effectively implemented and additional monitoring recommendations. Patient predictors of budget impact related to medication recommendations were assessed using multivariable linear regression, including age, gender, eGFR, acute admission, medication count, comorbidity, expensive drugs, and ward type. Results: We collected 271 medication reviews, including 1,689 medication recommendations. Per-patient budget impact was negative for the intervention (€104 costs), but positive for medication recommendations (€46 savings), and preventable medication-related readmissions (€239 savings). Total estimated savings were €181 per patient, and €688,000 when upscaled hospital-wide. Opiates, beta receptor agonists, corticosteroids, urological drugs, and muscarine receptor antagonists generated 43% of medication recommendation savings. Erythropoietic growth factors, SGLT2 inhibitors, etanercept, etravirine, and calcium/vitamin D formulations generated 70% of medication recommendation costs. No significant associations were found between any of the included patient characteristics and budget impact related to medication recommendations. Conclusion: Junior pharmacist-led medication reviews provide a modest cost-saving intervention from the hospital perspective, demonstrating savings across clinical populations with polypharmacy.

Aims: The study aims to predict and improve the absorption of tyrosine kinase inhibitors (TKIs) in patients with malabsorption issues, particularly those who have undergone bariatric surgery or are using proton‐pump inhibitors. The research involves 2 main components: the development of an artificial intelligence (AI) model to identify TKIs that are susceptible to reduced absorption in these patients, and the application of case‐specific absorption enhancements based on 2 clinical scenarios. Methods: A fully connected neural network was applied using pH‐dependent solubility data from 137 785 compounds to identify TKIs at risk of reduced bioavailability when bypassing the stomach. The clinical impact of gastric acid suppressants on the bioavailability of 71 approved TKIs was evaluated by correlating the AI solubility estimates with the effect of proton‐pump inhibitors on clinical exposure. Furthermore, absorption enhancement was applied in 2 clinical scenarios, with therapeutic drug monitoring assessing the effectiveness of the enhancement. Results: Two AI models were developed to predict the difference in molecular aqueous solubility between acid and neutral pH and to capture the concentration available for intestinal absorption in healthy and in patients with malabsorption issues. The AI model capturing the solubility difference between acidic and neutral pH demonstrated predictive capabilities, with a Pearson correlation coefficient of .95 and a coefficient of determination of .90. It predicted that the solubility difference, between acidic and neutral pH, was associated with clinical bioavailability ( P < .001). Nilotinib, lapatinib and dacomitinib were ranked as TKIs with the highest risk of malabsorption in case of increased stomach pH. Conclusion: We developed an AI‐based model that predicts TKIs that are at risk of malabsorption when bypassing the stomach or used with gastric acid suppressants. Drugs with a high malabsorption risk can be enhanced by various methods to improve bioavailability.

Background In the Netherlands, home treatment with intravenous antimicrobial therapy is a relatively new concept. Although several studies have shown that outpatient parenteral antimicrobial therapy (OPAT) can be administered safely, people receiving antimicrobials at home remain at risk for adverse events, including readmission. Aim The aim of our retrospective study was to identify risk factors for readmission in patients discharged with OPAT. Method Patients who were at least 18 years or older, discharged with OPAT between January 2016–December 2018 were included. Variables that were collected consisted of baseline demographics, complications, readmission within 30 days and treatment failure. Multivariate logistic regression analysis was performed to identify risk factors for readmission. Results A total of 247 patients were included; the most common reason for OPAT was bone and joint infections (17%). Penicillin (37%), cephalosporin (26%) and vancomycin/aminoglycoside (15%) were the most commonly prescribed antimicrobials. Among patients receiving medication subject to therapeutic drug monitoring (i.e. aminoglycosides or vancomycin), 51% (19/37) received weekly therapeutic drug monitoring. Receiving aminoglycosides or vancomycin (adjusted OR 2.05; 95% CI 1.30–3.25, p < 0.05) and infection of prosthetic material (adjusted OR 2.92, 95% CI 1.11–7.65, p < 0.05) were independent risk factors associated with readmission. Conclusion Although patients receiving medication subject to therapeutic drug monitoring are at higher risk of readmission, only half of the patients discharged with aminoglycosides or vancomycin were monitored according to IDSA guidelines. A specialized team in charge of monitoring patients with OPAT is more likely to increase the rate of monitoring to prevent readmissions and complications.