Background: Medication reconciliation has become standard care to prevent medication transfer errors. However, this process is time-consuming but could be more efficient when patients are engaged... Show moreBackground: Medication reconciliation has become standard care to prevent medication transfer errors. However, this process is time-consuming but could be more efficient when patients are engaged in medication reconciliation via a patient portal. Objectives: To explore whether medication reconciliation by the patient via a patient portal is noninferior to medication reconciliation by a pharmacy technician. Design (including intervention): Open randomized controlled noninferiority trial. Patients were randomized between medication reconciliation via a patient portal (intervention) or medication reconciliation by a pharmacy technician at the preoperative screening (usual care). Setting and Participants: Patients scheduled for elective surgery using at least 1 chronic medication were included. Measures: The primary endpoint was the number of medication discrepancies compared to the electronic nationwide medication record system (NMRS). For the secondary endpoint, time investment of the pharmacy technician for the medication reconciliation interview and patient satisfaction were studied. Noninferiority was analyzed with an independent t test, and the margin was set at 20%. Results: A total of 499 patients were included. The patient portal group contained 241 patients; the usual care group contained 258 patients. The number of medication discrepancies was 2.6 +/- 2.5 in the patient portal group and 2.8 +/- 2.7 in the usual care group. This was not statistically different and within the predefined noninferiority margin. Patients were satisfied with the use of the patient portal tool. Also, the use of the portal can save on average 6.8 minutes per patient compared with usual care. Conclusions and Implications: Medication reconciliation using a patient portal is noninferior to medication reconciliation by a pharmacy technician with respect to medication discrepancies, and saves time in the medication reconciliation process. Future studies should focus on identifying patient characteristics for successful implementation of patient portal medication reconciliation. (c) 2021 The Authors. Published by Elsevier Inc. on behalf of AMDA -The Society for Post-Acute and Long-Term Care Medicine. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/). Show less
Berger, F.A.; Weteringen, W. van; Sijs, H. van der; Hunfeld, N.G.M.; Bunge, J.J.H.; Groot, N.M.S. de; ... ; Gelder, T. van 2021
QTc interval prolongation is an adverse effect associated with the use of fluoroquinolones and macrolides. Ciprofloxacin and erythromycin are both frequently prescribed QTc-prolonging drugs in... Show moreQTc interval prolongation is an adverse effect associated with the use of fluoroquinolones and macrolides. Ciprofloxacin and erythromycin are both frequently prescribed QTc-prolonging drugs in critically ill patients. Critically ill patients may be more vulnerable to developing QTc prolongation, as several risk factors can be present at the same time. Therefore, it is important to know the QTc-prolonging potential of these drugs in the intensive care unit (ICU) population. The aim of this study was to assess the dynamics of the QTc interval over a 24-hour dose interval during intravenous ciprofloxacin and low-dose erythromycin treatment. Therefore, an observational study was performed in ICU patients (>= 18 years) receiving ciprofloxacin 400 mg t.i.d. or erythromycin 100 mg b.i.d. intravenously. Continuous ECG data were collected from 2 h before to 24 h after the first administration. QT-analyses were performed using high-end holter software. The effect was determined with a two-sample t-test for clustered data on all QTc values. A linear mixed model by maximum likelihood was applied, for which QTc values were assessed for the available time intervals and therapy. No evident effect over time on therapy with ciprofloxacin and erythromycin was observed on QTc time. There was no significant difference (p = 0.22) in QTc values between the ciprofloxacin group (mean 393 ms) and ciprofloxacin control group (mean 386 ms). The erythromycin group (mean 405 ms) and erythromycin control group (mean 404 ms) neither showed a significant difference (p = 0.80). In 0.6% of the registrations (1.138 out of 198.270 samples) the duration of the QTc interval was longer than 500 ms. The index groups showed slightly more recorded QTc intervals over 500 ms. To conclude, this study could not identify differences in the QTc interval between the treatments analyzed. Show less
Hendriksen, L.C.; Linden, P.D. van der; Lagro-Janssen, A.L.M.; Bemt, P.M.L.A. van den; Siiskonen, S.J.; Teichert, M.; ... ; Visser, L.E. 2021
Background Adverse drug events, including adverse drug reactions (ADRs), are responsible for approximately 5% of unplanned hospital admissions: a major health concern. Women are 1.5-1.7 times more... Show moreBackground Adverse drug events, including adverse drug reactions (ADRs), are responsible for approximately 5% of unplanned hospital admissions: a major health concern. Women are 1.5-1.7 times more likely to develop ADRs. The main objective was to identify sex differences in the types and number of ADRs leading to hospital admission. Methods ADR-related hospital admissions between 2005 and 2017 were identified from the PHARMO Database Network using hospital discharge diagnoses. Patients aged >= 16 years with a drug possibly responsible for the ADR and dispensed within 3 months before admission were included. Age-adjusted odds ratios (OR) with 95% CIs for drug-ADR combinations for women versus men were calculated. Results A total of 18,469 ADR-related hospital admissions involving women (0.35% of all women admitted) and 14,678 admissions involving men (0.35% of all men admitted) were included. Most substantial differences were seen in ADRs due to anticoagulants and diuretics. Anticoagulants showed a lower risk of admission with persistent haematuria (ORadj 0.31; 95%CI 0.21, 0.45) haemoptysis (ORadj 0.47, 95%CI 0.30,0.74) and subdural haemorrhage (ORadj 0.61; 95%CI 0.42,0.88) in women than in men and a higher risk of rectal bleeding in women (ORadj 1.48; 95%CI 1.04,2.11). Also, there was a higher risk of admission in women using thiazide diuretics causing hypokalaemia (ORadj 3.03; 95%CI 1.58, 5.79) and hyponatraemia (ORadj 3.33, 95%CI 2.31, 4.81) than in men. Conclusions There are sex-related differences in the risk of hospital admission in specific drug-ADR combinations. The most substantial differences were due to anticoagulants and diuretics. Show less
Ebbens, M.M.; Dorp, E.L.A. van; Gombert-Handoko, K.B.; Bemt, P.M.L.A. van den 2021
Introduction: The handling of drug-drug interactions regarding QTc-prolongation (QT-DDIs) is not well defined. A clinical decision support (CDS) tool will support risk management of QT-DDIs.... Show moreIntroduction: The handling of drug-drug interactions regarding QTc-prolongation (QT-DDIs) is not well defined. A clinical decision support (CDS) tool will support risk management of QT-DDIs. Therefore, we studied the effect of a CDS tool on the proportion of QT-DDIs for which an intervention was considered by pharmacists.Methods: An intervention study was performed using a pre- and post-design in 20 community pharmacies in The Netherlands. All QT-DDIs that occurred during a before- and after-period of three months were included. The impact of the use of a CDS tool to support the handling of QT-DDIs was studied. For each QT-DDI, handling of the QT-DDI and patient characteristics were extracted from the pharmacy information system. Primary outcome was the proportion of QT-DDIs with an intervention. Secondary outcomes were the type of interventions and the time associated with handling QT-DDIs. Logistic regression analysis was used to analyse the primary outcome.Results: Two hundred and forty-four QT-DDIs pre-CDS tool and 157 QT-DDIs post-CDS tool were included. Pharmacists intervened in 43.0% and 35.7% of the QT-DDIs pre- and post-CDS tool respectively (odds ratio 0.74; 95% confidence interval 0.49-1.11). Substitution of interacting agents was the most frequent intervention. Pharmacists spent 20.8 +/- 3.5 min (mean +/- SD) on handling QT-DDIs pre-CDS tool, which was reduced to 14.9 +/- 2.4 min (mean +/- SD) post-CDS tool. Of these, 4.5 +/- 0.7 min (mean +/- SD) were spent on the CDS tool.Conclusion: The CDS tool might be a first step to developing a tool to manage QT-DDIs via a structured approach. Improvement of the tool is needed in order to increase its diagnostic value and reduce redundant QT-DDI alerts. Show less
Berger, F.A.; Sijs, H. van der; Gelder, T. van; Kuijper, A.F.M.; Bemt, P.M.L.A. van den; Becker, M.L. 2021
Background: QTc-prolongation is an independent risk factor for developing life-threatening arrhythmias. Risk management of drug-induced QTc-prolongation is complex and digital support tools could... Show moreBackground: QTc-prolongation is an independent risk factor for developing life-threatening arrhythmias. Risk management of drug-induced QTc-prolongation is complex and digital support tools could be of assistance. Bindraban et al. and Berger et al. developed two algorithms to identify patients at risk for QTc-prolongation.Objective: The main aim of this study was to compare the performances of these algorithms for managing QTcprolonging drug-drug interactions (QT-DDIs).Materials and Methods: A retrospective data analysis was performed. A dataset was created from QT-DDI alerts generated for inand outpatients at a general teaching hospital between November 2016 and March 2018. ECGs recorded within 7 days of the QT-DDI alert were collected. Main outcomes were the performance characteristics of both algorithms. QTc-intervals of > 500 ms on the first ECG after the alert were taken as outcome parameter, to which the performances were compared. Secondary outcome was the distribution of risk scores in the study cohort.Results: In total, 10,870 QT-DDI alerts of 4987 patients were included. ECGs were recorded in 26.2 % of the QT-DDI alerts. Application of the algorithms resulted in area under the ROC-curves of 0.81 (95 % CI 0.79-0.84) for Bindraban et al. and 0.73 (0.70-0.75) for Berger et al. Cut-off values of >= 3 and >= 6 led to sensitivities of 85.7 % and 89.1 %, and specificities of 60.8 % and 44.3 % respectively.Conclusions: Both algorithms showed good discriminative abilities to identify patients at risk for QTcprolongation when using >= 2 QTc-prolonging drugs. Implementation of digital algorithms in clinical decision support systems could support the risk management of QT-DDIs. Show less
Berger, F.A.; Sijs, H. van der; Becker, M.L.; Gelder, T. van; Bemt, P.M.L.A. van den 2020
Background The exact risk of developing QTc-prolongation when using a combination of QTc-prolonging drugs is still unknown, making it difficult to interpret these QT drug-drug interactions (QT-DDIs... Show moreBackground The exact risk of developing QTc-prolongation when using a combination of QTc-prolonging drugs is still unknown, making it difficult to interpret these QT drug-drug interactions (QT-DDIs). A tool to identify high-risk patients is needed to support healthcare providers in handling automatically generated alerts in clinical practice. The main aim of this study was to develop and validate a tool to assess the risk of QT-DDIs in clinical practice. Methods A model was developed based on risk factors associated with QTc-prolongation determined in a prospective study on QT-DDIs in a university medical center inthe Netherlands. The main outcome measure was QTc-prolongation defined as a QTc interval > 450 ms for males and > 470 ms for females. Risk points were assigned to risk factors based on their odds ratios. Additional risk factors were added based on a literature review. The ability of the model to predict QTc-prolongation was validated in an independent dataset obtained from a general teaching hospital against QTc-prolongation as measured by an ECG as the gold standard. Sensitivities, specificities, false omission rates, accuracy and Youden's index were calculated. Results The model included age, gender, cardiac comorbidities, hypertension, diabetes mellitus, renal function, potassium levels, loop diuretics, and QTc-prolonging drugs as risk factors. Application of the model to the independent dataset resulted in an area under the ROC-curve of 0.54 (95% CI 0.51-0.56) when QTc-prolongation was defined as > 450/470 ms, and 0.59 (0.54-0.63) when QTc-prolongation was defined as > 500 ms. A cut-off value of 6 led to a sensitivity of 76.6 and 83.9% and a specificity of 28.5 and 27.5% respectively. Conclusions A clinical decision support tool with fair performance characteristics was developed. Optimization of this tool may aid in assessing the risk associated with QT-DDIs. Show less
Ebbens, M.M.; Errami, H.; Moes, D.J.A.R.; Bemt, P.M.L.A. van den; Boog, P.J.M. van der; Gombert-Handoko, K.B. 2019
Background: Medication reconciliation in transitions of care can prevent medication transfer errors (MTE). MTE can cause patient harm. Since performing medication reconciliation for every patient... Show moreBackground: Medication reconciliation in transitions of care can prevent medication transfer errors (MTE). MTE can cause patient harm. Since performing medication reconciliation for every patient is not always feasible, identification of potential risk factors of MTE could aid in targeting this intervention to the right patients.Objective: To establish the proportion of patients with one or more MTE in the outpatient nephrology setting. Secondary patient characteristics associated with MTE, type and potential harm, and medication groups were investigated.Methods: This retrospective observational cohort study was conducted in the Leiden University Medical Center, the Netherlands, between November 2017 and April 2018. The cohort involved patients in whom medication reconciliation was performed by a medical attendant using the electronic tool 'Medical Dashboard' prior to visiting the nephrologist. MTE were defined as unintended discrepancies between the medication in the hospital system and the result of the medication reconciliation. The proportion of patients with one or more MTE was calculated and the association of patient characteristics (age, sex, number of medications and kidney function (CKD-EPI)) with MTE was analyzed using multivariate logistic regression.Results: Of 380 patients, 235 patients (61.8%) had at least one MTE. On average patients used 10.3 medications. The number of medications per patient was significantly associated with MTE; OR 1.11 (95%CI 1.05-1.16). No association was found for age, sex, and kidney function.Conclusion: In ambulatory nephrology patients 61.8% had at least one MTE. Nephrology patients using a higher number of drugs are more prone to MTE. Show less
Bosma, L.B.E.; Rein, N. van; Hunfeld, N.G.M.; Steyerberg, E.W.; Melief, P.H.G.J.; Bemt, P.M.L.A. van den 2019
