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Carlota Mestres Gonzalvo,1 Kim PGM Hurkens,2 Hugo AJM de Wit,3 Brigit PC van Oijen,1 Rob Janknegt,1 Jos MGA Schols,4 Wubbo J Mulder,5 Frans R Verhey,6 Bjorn Winkens,7 Paul-Hugo M van der Kuy1 1Department of Clinical Pharmacology and Toxicology, Orbis Medical Centre, Sittard, 2Department of Internal Medicine, Section of Geriatric Medicine, Academic Medical Centre, Amsterdam, 3Department of Clinical Pharmacy and Toxicology, Atrium Medical Centre, Heerlen, 4Department of Family Medicine and Department of Health Services Research, School for Public Health and Primary Care, Maastricht University, 5Department of Internal Medicine, Maastricht University Medical Centre, 6Department of Psychiatry and Neuropsychology, Alzheimer Centre Limburg/School for Mental Health and Neurosciences, 7Department of Methodology and Statistics, School for Public Health and Primary Care, Maastricht University, Maastricht, the Netherlands Background: The aim of this study was to evaluate to what extent laboratory data, actual medication, medical history, and/or drug indication influence the quality of medication reviews for nursing home patients. Methods: Forty-six health care professionals from different fields were requested to perform medication reviews for three different cases. Per case, the amount of information provided varied in three subsequent stages: stage 1, medication list only; stage 2, adding laboratory data and reason for hospital admission; and stage 3, adding medical history/drug indication. Following a slightly modified Delphi method, a multidisciplinary team performed the medication review for each case and stage. The results of these medication reviews were used as reference reviews (gold standard). The remarks from the participants were scored, according to their potential clinical impact, from relevant to harmful on a scale of 3 to -1. A total score per case and stage was calculated and expressed as a percentage of the total score from the expert panel for the same case and stage. Results: The overall mean percentage over all cases, stages, and groups was 37.0% when compared with the reference reviews. For one of the cases, the average score decreased significantly from 40.0% in stage 1, to 30.9% in stage 2, and 27.9% in stage 3; no significant differences between stages was found for the other cases. Conclusion: The low performance, against the gold standard, of medication reviews found in the present study highlights that information is incorrectly used or wrongly interpreted, irrespective of the available information. Performing medication reviews without using the available information in an optimal way can have potential implications for patient safety. Keywords: polypharmacy, medication therapy management, decision support systems management, aged, medication review

Background: Inappropriate prescribing is associated with negative patient outcomes. In hospitalized patients, the use of Clinical Decision Support Systems (CDSSs) may reduce inappropriate prescribing and thereby improve patient-related outcomes. However, recently published large clinical trials (OPERAM and SENATOR) have shown negative results on the use of CDSSs and patient outcomes and strikingly low acceptance of recommendations., Objective: The purpose of the present study was to investigate the use of a CDSS in a real-life clinical setting of hospitalized older patients. As such, we report on the real-life pattern of this in-hospital implemented CDSS, including (i) whether generated alerts were resolved; (ii) whether a recorded action by the pharmacist led to an improved number of resolved alerts; and (iii) the natural course of generated alerts, in particular of those in the non-intervention group; as these data are largely lacking in current studies., Methods: Hospitalized patients, aged 60 years and older, admitted to Zuyderland Medical Centre, the Netherlands, in 2018 were included. The evaluation of the CDSS was investigated using a database used for standard care. Alongside demographic and clinical data, we also collected the total numbers of CDSS alerts, the number of alerts 'handled' by the pharmacist, those that resulted in an action by the pharmacist, and finally the outcome of the alerts at day 1 and day 3 after the alert was generated., Results: A total of 3574 unique hospitalized patients, mean age 76.7 (SD 8.3) years and 53% female, were included. From these patients, 8073 alerts were generated, of which 7907 (97.9% of total) were handled by the pharmacist (day 1). In 51.6% of the alerts handled by the pharmacist, an action was initiated, resulting in 36.1% of the alerts resolved after day 1, compared with 27.3% if the pharmacist did not perform an action (p < 0.001). On day 3, in 52.6% of the alerts an action by the pharmacist was initiated, resulting in 62.4% resolved alerts, compared with 48.0% when no action was performed (p < 0.001). In the category renal function, the percentages differed significantly between an action versus no action of the pharmacist at day 1 and at day 3 (16.6% vs 10.6%, p < 0.001 [day 1]; 29.8% vs 19.4%, p < 0.001 [day 3])., Conclusion: This study demonstrates the pattern and natural course of clinical alerts of an in-hospital implemented CDSS in a real-life clinical setting of hospitalized older patients. Besides the already known beneficial effect of actions by pharmacists, we have also shown that many alerts become resolved without any specific intervention. As such, our study provides an important insight into the spontaneous course of resolved alerts, since these data are currently lacking in the literature., (© 2023. The Author(s).)

Background: The prevalence of medication-related emergency department visits and acute hospital admissions in older patients is rising due to the ageing of the population and increasing prevalence of multimorbidity and associated polypharmacy., Aim: To explore whether a combined medication review performed in the outpatient setting reduces the number of medication-related emergency department visits and hospital (re)admissions., Method: All consecutive patients visiting the geriatric outpatient clinic underwent a multifaceted medication review (i.e. evaluation by at least a geriatrician, and/or pharmacist and use of clinical decision support system). Subsequently, we analysed the number of, and reason for, emergency department visits, acute hospital admissions and readmissions in the year prior to and the year following the index-date (date of first presentation and medication review)., Results: A multifaceted medication review reduced the number of potentially medication-related emergency department visits (38.9% vs. 19.6%, p < 0.01), although the total number of ED visits or acute hospital admissions per patient in the year before and after medication review did not differ., Conclusion: A multifaceted medication review performed in the outpatient clinic reduced the number of potentially medication-related emergency department visits and could therefore reduce negative health outcomes and healthcare costs., (© 2023. The Author(s).)

Background: Of all hospital admissions in older patients, 10-30% seem to be medication-related. However, medication-related admissions are often unidentified in clinical practice. To increase the identification of medication-related hospital admissions in older patients a triggerlist is published in the Dutch guideline for polypharmacy., Aim: To assess whether the triggerlist has value as selection criterion to identify patients at high risk of medication-related hospital admissions., Method: This retrospective cohort study was carried out in 100 older (≥ 60 years) patients with polypharmacy and having two triggers from the triggerlist. The admissions were assessed as either possibly or unlikely medication-related according to the Assessment Tool for identifying Hospital Admissions Related to Medications., Results: Of all the admissions 48% were classified as possibly medication-related. Patients with a possible medication-related hospital admission were more likely to have an impaired renal function (p = 0.015), but no differences with regard to age, sex, comorbidity or number of medicines were found., Conclusion: The high prevalence of medication-related hospital admissions, suggests the triggerlist may have added value as selection criterion in a cohort of older patients with polypharmacy and can be used to improve the identification of a population at high risk of medication-related hospital admissions., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Background: Due to ageing of the population the incidence of multimorbidity and polypharmacy is rising. Polypharmacy is a risk factor for medication-related (re)admission and therefore places a significant burden on the healthcare system. The reported incidence of medication-related (re)admissions varies widely due to the lack of a clear definition. Some medications are known to increase the risk for medication-related admission and are therefore published in the triggerlist of the Dutch guideline for Polypharmacy in older patients. Different interventions to support medication optimization have been studied to reduce medication-related (re)admissions. However, the optimal template of medication optimization is still unknown, which contributes to the large heterogeneity of their effect on hospital readmissions. Therefore, we implemented a clinical decision support system (CDSS) to optimize medication lists and investigate whether continuous use of a CDSS reduces the number of hospital readmissions in older patients, who previously have had an unplanned probably medication-related hospitalization., Methods: The CHECkUP study is a multicentre randomized study in older (≥60 years) patients with an unplanned hospitalization, polypharmacy (≥5 medications) and using at least two medications from the triggerlist, from Zuyderland Medical Centre and Maastricht University Medical Centre+ in the Netherlands. Patients will be randomized. The intervention consists of continuous (weekly) use of a CDSS, which generates a Medication Optimization Profile, which will be sent to the patient's general practitioner and pharmacist. The control group will receive standard care. The primary outcome is hospital readmission within 1 year after study inclusion. Secondary outcomes are one-year mortality, number of emergency department visits, nursing home admissions, time to hospital readmissions and we will evaluate the quality of life and socio-economic status., Discussion: This study is expected to add evidence on the knowledge of medication optimization and whether use of a continuous CDSS ameliorates the risk of adverse outcomes in older patients, already at an increased risk of medication-related (re)admission. To our knowledge, this is the first large study, providing one-year follow-up data and reporting not only on quality of care indicators, but also on quality-of-life., Trial Registration: The trial was registered in the Netherlands Trial Register on October 14, 2018, identifier: NL7449 (NTR7691). https://www.trialregister.nl/trial/7449 ., (© 2022. The Author(s).)

Objectives: To develop (part I) and validate (part II) an electronic fall risk clinical rule (CR) to identify nursing home residents (NH-residents) at risk for a fall incident., Design: Observational, retrospective case-control study., Setting: Nursing homes., Participants: A total of 1668 (824 in part I, 844 in part II) NH-residents from the Netherlands were included. Data of participants from part I were excluded in part II., Primary and Secondary Outcome Measures: Development and validation of a fall risk CR in NH-residents. Logistic regression analysis was conducted to identify the fall risk-variables in part I. With these, three CRs were developed (ie, at the day of the fall incident and 3 days and 5 days prior to the fall incident). The overall prediction quality of the CRs were assessed using the area under the receiver operating characteristics (AUROC), and a cut-off value was determined for the predicted risk ensuring a sensitivity ≥0.85. Finally, one CR was chosen and validated in part II using a new retrospective data set., Results: Eleven fall risk-variables were identified in part I. The AUROCs of the three CRs form part I were similar: the AUROC for models I, II and III were 0.714 (95% CI: 0.679 to 0.748), 0.715 (95% CI: 0.680 to 0.750) and 0.709 (95% CI: 0.674 to 0.744), respectively. Model III (ie, 5 days prior to the fall incident) was chosen for validation in part II. The validated AUROC of the CR, obtained in part II, was 0.603 (95% CI: 0.565 to 0.641) with a sensitivity of 83.41% (95% CI: 79.44% to 86.76%) and a specificity of 27.25% (95% CI 23.11% to 31.81%)., Conclusion: Medication data and resident characteristics alone are not sufficient enough to develop a successful CR with a high sensitivity and specificity to predict fall risk in NH-residents., Trial Registration Number: Not available., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.)

Background The number of medication related hospital admissions and readmissions are increasing over the years due to the ageing population. Medication related hospital admissions and readmissions lead to decreased quality of life and high healthcare costs. Aim of the review To assess what is currently known about medication related hospital admissions, medication related hospital readmissions, their risk factors, and possible interventions which reduce medication related hospital readmissions. Method We searched PubMed for articles about the topic medication related hospital admissions and readmissions. Overall 54 studies were selected for the overview of literature. Results Between the different selected studies there was much heterogeneity in definitions for medication related admission and readmissions, in study population and the way studies were performed. Multiple risk factors are found in the studies for example: polypharmacy, comorbidities, therapy non adherence, cognitive impairment, depending living situation, high risk medications and higher age. Different interventions are studied to reduce the number of medication related readmission, some of these interventions may reduce the readmissions like the participation of a pharmacist, education programmes and transition-of-care interventions and the use of digital assistance in the form of Clinical Decision Support Systems. However the methods and the results of these interventions show heterogeneity in the different researches. Conclusion There is much heterogeneity in incidence and definitions for both medication related hospital admissions and readmissions. Some risk factors are known for medication related admissions and readmissions such as polypharmacy, older age and additional diseases. Known interventions that could possibly lead to a decrease in medication related hospital readmissions are spare being the involvement of a pharmacist, education programs and transition-care interventions the most mentioned ones although controversial results have been reported. More research is needed to gather more information on this topic.

Purpose: The chronic use of benzodiazepines and benzodiazepine-related drugs (BZ/Z) in older people is common and not without risks. The objective of this study was to evaluate whether the implementation of a clinical rule promotes the discontinuation of chronically used BZ/Z for insomnia., Methods: A clinical rule, generating an alert in case of chronic BZ/Z use, was created and applied to the nursing home (NH) setting. The clinical rule was a one-off intervention, and alerts did not occur over time. Reports of the generated alerts were digitally sent to NH physicians with the advice to phase out and eventually stop the BZ/Z. In cases where the advice was adopted, a follow-up period of 4 months on the use of BZ/Z was taken into account in order to determine whether the clinical rule alert led to a successful discontinuation of BZ/Z., Results: In all, 808 NH patients were screened. In 161 (19.1%) of the patients, BZ/Z use resulted in a clinical rule alert. From these, the advice to phase out and stop the BZ/Z was adopted for 27 patients (16.8%). Reasons for not following the advice consisted of an unsuccessful attempt in the past (38 patients), patients family and/or patient resistance (37 patients), the non-continuous use of BZ/Z (32 patients) and indication still present (27 patients). Of the 12 NH physicians, seven adopted the advice., Conclusions: The success rate of a clinical rule for discontinuation of chronically used BZ/Z for insomnia was low, as reported in the present study. Actions should be taken to help caregivers, patients and family members understand the importance of limiting BZ/Z use to achieve higher discontinuation rates.

Objectives: Delirium is an underdiagnosed, severe and costly disorder, and 30%-40% of cases can be prevented. A fully automated model to predict delirium (DEMO) in older people has been developed, and the objective of this study is to validate the model in a hospital setting., Setting: Secondary care, one hospital with two locations., Design: Observational study., Participants: The study included 450 randomly selected patients over 60 years of age admitted to Zuyderland Medical Centre. Patients who presented with delirium on admission were excluded., Primary Outcome Measures: Development of delirium through chart review., Results: A total of 383 patients were included in this study. The analysis was performed for delirium within 1, 3 and 5 days after a DEMO score was obtained. Sensitivity was 87.1% (95% CI 0.756 to 0.939), 84.2% (95% CI 0.732 to 0.915) and 82.7% (95% CI 0.734 to 0.893) for 1, 3 and 5 days, respectively, after obtaining the DEMO score. Specificity was 77.9% (95% CI 0.729 to 0.882), 81.5% (95% CI 0.766 to 0.856) and 84.5% (95% CI 0.797 to 0.884) for 1, 3 and 5 days, respectively, after obtaining the DEMO score., Conclusion: DEMO is a satisfactory prediction model but needs further prospective validation with in-person delirium confirmation. In the future, DEMO will be applied in clinical practice so that physicians will be aware of when a patient is at an increased risk of developing delirium, which will facilitate earlier recognition and diagnosis, and thus will allow the implementation of prevention measures., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)