Adoption of antithrombotic stewardship and utilization of clinical decision support systems-A questionnaire-based survey in Dutch hospitals.

Antithrombotics require careful monitoring to prevent adverse events. Safe use can be promoted through so-called antithrombotic stewardship. Clinical decision support systems (CDSSs) can be used to monitor safe use of antithrombotics, supporting antithrombotic stewardship efforts. Yet, previous research shows that despite these interventions, antithrombotics continue to cause harm. Insufficient adoption of antithrombotic stewardship and suboptimal use of CDSSs may provide and explanation. However, it is currently unknown to what extent hospitals adopted antithrombotic stewardship and utilize CDSSs to support safe use of antithrombotics. A semi-structured questionnaire-based survey was disseminated to 12 hospital pharmacists from different hospital types and regions in the Netherlands. The primary outcome was the degree of antithrombotic stewardship adoption, expressed as the number of tasks adopted per hospital and the degree of adoption per task. Secondary outcomes included characteristics of CDSS alerts used to monitor safe use of antithrombotics. All 12 hospital pharmacists completed the survey and report to have adopted antithrombotic stewardship in their hospital to a certain degree. The median adoption of tasks was two of five tasks (range 1-3). The tasks with the highest uptake were: drafting and maintenance of protocols (100%) and professional's education (58%), while care transition optimization (25%), medication reviews (8%) and patient counseling (8%) had the lowest uptake. All hospitals used a CDSS to monitor safe use of antithrombotics, mainly via basic alerts and less frequently via advanced alerts. The most frequently employed alerts were: identification of patients using a direct oral anticoagulant (DOAC) or a vitamin K antagonist (VKA) with one or more other antithrombotics (n = 6) and patients using a VKA to evaluate correct use (n = 6), both reflecting basic CDSS. All participating hospitals adopted antithrombotic stewardship, but the adopted tasks vary. CDSS alerts used are mainly basic in their logic.

The use of artificial intelligence to optimize medication alerts generated by clinical decision support systems: a scoping review.

OBJECTIVE: Current Clinical Decision Support Systems (CDSSs) generate medication alerts that are of limited clinical value, causing alert fatigue. Artificial Intelligence (AI)-based methods may help in optimizing medication alerts. Therefore, we conducted a scoping review on the current state of the use of AI to optimize medication alerts in a hospital setting. Specifically, we aimed to identify the applied AI methods used together with their performance measures and main outcome measures. MATERIALS AND METHODS: We searched Medline, Embase, and Cochrane Library database on May 25, 2023 for studies of any quantitative design, in which the use of AI-based methods was investigated to optimize medication alerts generated by CDSSs in a hospital setting. The screening process was supported by ASReview software. RESULTS: Out of 5625 citations screened for eligibility, 10 studies were included. Three studies (30%) reported on both statistical performance and clinical outcomes. The most often reported performance measure was positive predictive value ranging from 9% to 100%. Regarding main outcome measures, alerts optimized using AI-based methods resulted in a decreased alert burden, increased identification of inappropriate or atypical prescriptions, and enabled prediction of user responses. In only 2 studies the AI-based alerts were implemented in hospital practice, and none of the studies conducted external validation. DISCUSSION AND CONCLUSION: AI-based methods can be used to optimize medication alerts in a hospital setting. However, reporting on models' development and validation should be improved, and external validation and implementation in hospital practice should be encouraged.

Prescription Sequence Symmetry Analysis (PSSA) to assess prescribing cascades: a step-by-step guide.

Prescribing cascades occur when patients are prescribed medication to treat the adverse drug reaction of previously prescribed medication. Prescription sequence symmetry analysis (PSSA) can be used to assess the association between two medications in prescription or dispensing databases and thus the potential occurrence of prescribing cascades. In this article, a step-by-step guide is presented for conducting PSSA to assess prescribing cascades. We describe considerations for medication data collection and setting time periods for relevant parameters, including washout window, exposure window, continued exposure interval and blackout period. With two examples, we illustrate the impact of changes in these parameters on the strengths of associations observed. Given the impact seen, we recommend that researchers clearly specify and explain all considerations regarding medication included and time windows set when studying prescribing cascades with PSSA, and conduct subgroup and sensitivity analyses.

Prescribing Cascades with Recommendations to Prevent or Reverse Them: A Systematic Review.

BACKGROUND: To reduce prescribing cascades occurring in clinical practice, healthcare providers require information on the prescribing cascades they can recognize and prevent. OBJECTIVE: This systematic review aims to provide an overview of prescribing cascades, including dose-dependency information and recommendations that healthcare providers can use to prevent or reverse them. METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was followed. Relevant literature was identified through searches in OVID MEDLINE, OVID Embase, OVID CINAHL, and Cochrane. Additionally, Web of Science and Scopus were consulted to analyze reference lists and citations. Publications in English were included if they analyzed the occurrence of prescribing cascades. Prescribing cascades were included if at least one study demonstrated a significant association and were excluded when the adverse drug reaction could not be confirmed in the Summary of Product Characteristics. Two reviewers independently extracted and grouped similar prescribing cascades. Descriptive summaries were provided regarding dose-dependency analyses and recommendations to prevent or reverse these prescribing cascades. RESULTS: A total of 95 publications were included, resulting in 115 prescribing cascades with confirmed adverse drug reactions for which at least one significant association was found. For 52 of these prescribing cascades, information regarding dose dependency or recommendations to prevent or reverse prescribing cascades was found. Dose dependency was analyzed and confirmed for 12 prescribing cascades. For example, antipsychotics that may cause extrapyramidal syndrome followed by anti-parkinson drugs. Recommendations focused on dosage lowering, discontinuing medication, and medication switching. Explicit recommendations regarding alternative options were given for three prescribing cascades. One example was switching to ondansetron or granisetron when extrapyramidal syndrome is experienced using metoclopramide. CONCLUSIONS: In total, 115 prescribing cascades were identified and an overview of 52 of them was generated for which recommendations to prevent or reverse them were provided. Nonetheless, information regarding alternative options for managing prescribing cascades was scarce.

Patient participation during discharge medication counselling: Observing real-life communication between healthcare professionals and patients.

OBJECTIVES: Previous studies on hospital discharge showed limited patient involvement, despite its positive outcomes. In this study, provider-patient communication used to enhance patient participation during discharge medication counselling was examined. METHODS: This study comprises a qualitative descriptive observational study. Thirty-four discharge consultations were observed, audio recorded and analysed. We conducted a deductive analysis, elaborating on findings from earlier research. We selected themes and underlying codes illustrating professional-patient communication. For every theme, we identified examples to demonstrate its manifestation during discharge medication counselling. We also assessed what information healthcare professionals (HCPs) shared. RESULTS: HCPs used cues to increase patient participation, e.g. inquired about patient's preferences, showed empathy and support, and verified understanding of information shared. Patient participation occurred through asking questions, and expressing concerns. A central component in discharge medication counselling was the transmission of information from HCPs to patients. This resulted in HCPs taking a leading role. CONCLUSIONS: Several HCP cues were detected inviting patients to participate in consultations. Some patients participated in discharge medication counselling. This was influenced by timing of discharge consults, the performing HCP and presence of a relative. PRACTICE IMPLICATIONS: HCPs shared a lot of information with patients. However, this does not automatically mean that patients will be able to understand and apply this information. HCPs should understand the importance of using cues to enable patient participation. One example is using the teach-back method for verifying patient understanding. It may also be desirable to ensure that a relative is present when discharge information is offered.

Correlation between the number of patient-reported adverse events, adverse drug events, and quality of life in older patients: an observational study.

BACKGROUND: Previous studies on medication therapy management services, e.g. medication reconciliation and medication review, do not show consistent improvements in patient's health-related quality of life. However, these services can reduce adverse drug events. AIM: To evaluate the correlation between health-related quality of life and adverse events/adverse drug events reported by patients. METHOD: Older patients (≥ 65 years) with polypharmacy (≥ 5 medicines) admitted to orthopaedic or surgical wards were included. Patients were contacted post-discharge to evaluate patient-reported adverse events, health-related quality of life using the EuroQol questionnaire and self-perceived health status on a 5-point Likert scale. The outcomes were the correlation between health-related quality of life and the number of adverse events/adverse drug events, and potential predictors for these events. Spearman correlation and Poisson regression were used for data analysis. RESULTS: 102 patients were included. The correlation between health-related quality of life and adverse events was weak but significant (Spearman correlation coefficient: - 0.328, p = 0.001). No correlation was found for adverse drug events (- 0.064, p = 0.521). Self-perceived health status was a predictor for adverse events, not for adverse drug events. Health-related quality of life was neither a predictor for adverse events, nor for adverse drug events. CONCLUSION: The correlation between the number of patient-reported adverse events, adverse drug events and health-related quality of life measured by the EuroQol was weak. There is a need for a questionnaire that includes the impact of medication use and is sensitive to outcomes that are affected by medication therapy management services.

Medication-Related Readmissions: Documentation of the Medication Involved and Communication in the Care Continuum.

Background: Of all readmissions, 21% are medication-related readmissions (MRRs). However, it is unknown whether MRRs are recognized at the time of readmission and are communicated in the care continuum. Objectives: To identify the prevalence of MRRs that contain a documentation on the medication involved (and therefore are regarded as recognized), and the proportion of communicated MRRs. Setting: The study was performed in a teaching hospital. Methods: In a previous study, a multidisciplinary team of physicians and pharmacists assessed the medication-relatedness, the medication involved and preventability of unplanned readmissions from seven departments. In the current cross-sectional study, two pharmacy team members evaluated the patient records independently. An MRR was regarded as recognized when the medication involved was documented in patient records. An MRR was regarded as communicated to the patient and/or the next healthcare provider when the medication involved or a description was mentioned in discharge letters or discharge prescriptions. The relationship between documented MRRs and whether the MRR was preventable as well as the relationship between (un)documented MRRs and the length of stay (LOS) were assessed. Descriptive data analysis was used. Results: Of 181 included MRRs, 72 (40%) were deemed preventable by the multidisciplinary team. For 159 of 181 MRRs (88%), a documentation on the medication involved was present. Of 159 documented MRRs, 93 (58%) were communicated to patients and/or caregivers, 137 (86%) to the general practitioner, and 4 (3%) to the community pharmacy. The medication involved was documented less often for potentially preventable MRRs than for non-preventable MRRs (78 vs. 95%; p = 0.002). The LOS was longer for MRRs where the medication involved was undocumented (median 8 vs. 5 days; p = 0.062). Conclusion: The results of this study imply that MRRs are not always recognized, which could impact patients' well-being. In this study an increased LOS was observed with unrecognized MRRs. Communication of MRRs to the patients and/or the next healthcare providers should be improved.

Implementation of a pharmacist-led transitional pharmaceutical care programme: Process evaluation of Medication Actions to Reduce hospital admissions through a collaboration between Community and Hospital pharmacists (MARCH).

WHAT IS KNOWN AND OBJECTIVE: The recently conducted Medication Actions to Reduce hospital admissions through a collaboration between Community and Hospital pharmacists (MARCH) transitional care programme, which aimed to test the effectiveness of a transitional care programme on the occurrence of ADEs post-discharge, did not show a significant effect. To clarify whether this non-significant effect was due to poor implementation or due to ineffectiveness of the intervention as such, a process evaluation was conducted. The aim of the study was to gain more insight into the implementation fidelity of MARCH. METHODS: A mixed methods design and the modified Conceptual Framework for Implementation Fidelity was used. For evaluation, the implementation fidelity and moderating factors of four key MARCH intervention components (teach-back, the pharmaceutical discharge letter, the post-discharge home-visit and the transitional medication review) were assessed. Quantitative data were collected during and after the intervention. Qualitative data were collected using semi-structured interviews with MARCH healthcare professionals (community pharmacists, clinical pharmacists, pharmacy assistants and pharmaceutical consultants) and analysed using thematic analysis. RESULTS AND DISCUSSION: Not all key intervention components were implemented as intended. Teach-back was not always performed. Moreover, 63% of the pharmaceutical discharge letters, 35% of the post-discharge home-visits and 44% of the transitional medication reviews were not conducted within their planned time frames. Training sessions, structured manuals and protocols with detailed descriptions facilitated implementation. Intervention complexity, time constraints and the multidisciplinary coordination were identified as barriers for the implementation. WHAT IS NEW AND CONCLUSION: Overall, the implementation fidelity was considered to be moderate. Not all key intervention components were carried out as planned. Therefore, the non-significant results of the MARCH programme on ADEs may at least partly be explained by poor implementation of the programme. To successfully implement transitional care programmes, healthcare professionals require full integration of these programmes in the standard work-flow including IT improvements as well as compensation for the time investment.

Commentary on the EMA reflection paper on the pharmaceutical development of medicines for use in the older population.

Older people are often affected by impaired organ and bodily functions resulting in multimorbidity and polypharmacy, turning them into the main user group of many medicines. Very often, medicines have not specifically been developed for older people, causing practical medication problems for them like limited availability of easy to swallow formulations, easy to open packaging and dosing instructions for enteral administration. In 2020, the European Medicines Agency (EMA) published a reflection paper 'Pharmaceutical development of medicines for use in the older population', which discusses how the emerging needs of an ageing European population can be addressed by medicines regulation. The paper intends to help industry to better consider the needs of older people during pharmaceutical/clinical medicines development by summarising data on the most relevant topics, providing early suggestions on how to move forward and prompting expert discussions and studies into knowledge gaps. Topics include patient acceptability, (dis)advantages of an administration route, formulation, dosage form, packaging, dosing device and user instruction. While the paper is directed at older people and the pharmaceutical industry, the reflections are also relevant to younger patients with similar disease-related needs and of value to other stakeholders parties, e.g., healthcare professionals, academics, patients and caregivers, as the paper makes clear what can be expected from industry and where collaborative work is needed. This commentary provides an overview of the different steps in the development of the reflection paper, discusses points considered most controversial and/or subject to (multidisciplinary) expert discussions and indicates their value for real world clinical practice.

Application of intervention mapping to develop and evaluate a pharmaceutical discharge letter to improve information transfer between hospital and community pharmacists.

BACKGROUND: Insufficient information transfer is a major barrier in the transition from hospital to home. This study describes the systematic development and evaluation of an intervention to improve medication information transfer between hospital and community pharmacists. OBJECTIVE: To develop and evaluate an intervention to improve the medication information transfer between hospital and community pharmacists based on patients', community and hospital pharmacists' needs. METHODS: The intervention development and evaluation was guided by the six-step Intervention Mapping (IM) approach: (1) needs assessment to identify determinants of the problem, with a scoping review and focus groups with patients and healthcare providers, (2) formulation of intervention objectives with an expert group, (3) inventory of communication models to design the intervention, (4) using literature review and qualitative research with pharmacists and patients to develop the intervention (5) pilot-testing of the intervention in two hospitals, and (6) a qualitative evaluation of the intervention as part of a multicenter before-after study with hospital and community pharmacists. RESULTS: Barriers in the information transfer are mainly time and content related. The intervention was designed to target a complete, accurate and timely medication information transfer between hospital and community pharmacists. A pharmaceutical discharge letter was developed to improve medication information transfer. Hospital and community pharmacists were positive about the usability, content, and comprehensiveness of the pharmaceutical discharge letter, which gave community pharmacists sufficient knowledge about in-hospital medication changes. However, hospital pharmacists reported that it was time-consuming to draft the discharge letter and not always feasible to send it on time. The intervention showed that pharmacists are positive about the usability, content and comprehensiveness. CONCLUSION: This study developed an intervention systematically to improve medication information transfer, consisting of a discharge letter to be used by hospital and community pharmacists supporting continuity of care.

Effects of a transitional care programme on medication adherence in an older cardiac population: A randomized clinical trial.

AIMS: Medication non-adherence post-discharge is common among patients, especially those suffering from chronic medical conditions, and contributes to hospital admissions and mortality. This study aimed to evaluate the effect of the Cardiac Care Bridge (CCB) intervention on medication adherence post-discharge. METHODS: We performed a secondary analysis of the CCB randomized single-blind trial, a study in patients ≥70 years, at high risk of functional loss and admitted to cardiology departments in six hospitals. In this multi-component intervention study, community nurses performed medication reconciliation and observed medication-related problems (MRPs) during post-discharge home visits, and pharmacists provided recommendations to resolve MRPs. Adherence to high-risk medications was measured using the proportion of days covered (PDC), using pharmacy refill data. Furthermore, MRPs were assessed in the intervention group. RESULTS: For 198 (64.7%) of 306 CCB patients, data were available on adherence (mean age: 82 years; 58.9% of patients used a multidose drug dispensing [MDD] system). The mean PDC before admission was 92.3% in the intervention group (n = 99) and 88.5% in the control group (n = 99), decreasing to 85.2% and 84.1% post-discharge, respectively (unadjusted difference: -2.6% (95% CI -9.8 to 4.6, P = .473); adjusted difference -3.3 (95% CI -10.3 to 3.7, P = .353)). Post-hoc analysis indicated that a modest beneficial intervention effect may be restricted to MDD non-users (Pinteraction = .085). In total, 77.0% of the patients had at least one MRP post-discharge. CONCLUSIONS: Our findings indicate that a multi-component intervention, including several components targeting medication adherence in older cardiac patients discharged from hospital back home, did not benefit their medication adherence levels. A modest positive effect on adherence may potentially exist in those patients not using an MDD system. This finding needs replication.

The effect of a transitional pharmaceutical care program on the occurrence of ADEs after discharge from hospital in patients with polypharmacy.

INTRODUCTION: Transitional care programs (i.e. interventions delivered both in hospital and in primary care), could increase continuity and consequently quality of care. However, limited studies on the effect of these programs on Adverse Drug Events (ADEs) post-discharge are available. Therefore, the aim of this study was to investigate the effect of a transitional pharmaceutical care program on the occurrence of ADEs 4 weeks post-discharge. METHODS: A multicentre prospective before-after study was performed in a general teaching hospital, a university hospital and 49 community pharmacies. The transitional pharmaceutical care program consisted of: teach-back to the patient at discharge, a pharmaceutical discharge letter, a home visit by a community pharmacist and a clinical medication review by both the community and the clinical pharmacist, on top of usual care. Usual care consisted of medication reconciliation at admission and discharge by pharmacy teams. The primary outcome was the proportion of patients who reported at least 1 ADE 4 weeks post-discharge. Multivariable logistic regression was used to adjust for potential confounders. RESULTS: In total, 369 patients were included (control: n = 195, intervention: n = 174). The proportion of patients with at least 1 ADE did not statistically significant differ between the intervention and control group (general teaching hospital: 59% vs. 67%, ORadj 0.70 [95% CI 0.38-1.31], university hospital: 63% vs 50%, OR adj 1.76 [95% CI 0.75-4.13]). CONCLUSION: The transitional pharmaceutical care program did not decrease the proportion of patients with ADEs after discharge. ADEs after discharge were common and more than 50% of patients reported at least 1 ADE. A process evaluation is needed to gain insight into how a transitional pharmaceutical care program could diminish those ADEs.

Clinical characteristics and risk factors of preventable hospital readmissions within 30 days.

Knowledge regarding preventable hospital readmissions is scarce. Our aim was to compare the clinical characteristics of potentially preventable readmissions (PPRs) with non-PPRs. Additionally, we aimed to identify risk factors for PPRs. Our study included readmissions within 30 days after discharge from 1 of 7 hospital departments. Preventability was assessed by multidisciplinary meetings. Characteristics of the readmissions were collected and 23 risk factors were analyzed. Of the 1120 readmissions, 125 (11%) were PPRs. PPRs occurred equally among different departments (p = 0.21). 29.6% of PPRs were readmitted by a practitioner of a different medical specialty than the initial admission (IA) specialist. The PPR group had more readmissions within 7 days (PPR 54% vs. non-PPR 44%, p = 0.03). The median LOS was 1 day longer for PPRs (p = 0.16). Factors associated with PPR were higher age (p = 0.004), higher socio-economic status (p = 0.049), fewer prior hospital admissions (p = 0.004), and no outpatient visit prior to readmission (p = 0.025). This study found that PPRs can occur at any department in the hospital. There is not a single type of patient that can easily be pinpointed to be at risk of a PPR, probably due to the multifactorial nature of PPRs.

Identifying medication-related readmissions: Two students using tools vs a multidisciplinary panel.

BACKGROUND: Polypharmacy may result in medication-related readmissions (MRRs). Identifying MRRs is time consuming. Screening of readmissions by students could increase efficiency for healthcare professionals. Recently, two screening tools have been published: the Assessment Tool for identifying Hospital Admissions Related to Medications (AT-HARM10) tool and the Drug-Related Admission (DRA) adjudication guide. It is unknown whether pharmacy students could identify MRRs with these tools. OBJECTIVE: To compare the agreement between two pharmacy students applying the AT-HARM10 tool and DRA adjudication guide in identifying MRRs vs a multidisciplinary panel. METHODS: A retrospective study was conducted from February to July 2020 at OLVG hospital. Readmissions within 30 days after discharge from seven departments were reviewed by a multidisciplinary panel (pharmacists and physicians). MRRs were defined as readmission where medication was the main cause or medication significantly contributed to the readmission. Two 5th year pharmacy-students volunteered to blindly apply both tools individually on all MRRs and a random sample of non-MRRs. The consensus results of the students and the multidisciplinary panel were compared and displayed as a percentage and Cohen's kappa (κ). RESULTS: Three hundred sixty-six readmission cases were selected in total, consisting of 181 MRRs and 185 non-MRRs. The agreement between the students using the AT-HARM10 tool vs the multidisciplinary panel was moderate (80%, κ = 0.60 (95% confidence interval (CI): 0.52-0.68)). The DRA adjudication guide had a moderate agreement (81%, κ = 0.62 (CI: 0.54-0.70)). Students misclassified MRRs mainly because the multidisciplinary panel found disease progression more profound than a contribution of medication. CONCLUSIONS: Two students have an overall agreement of 80% in comparison with the multidisciplinary panel with a moderate Cohen's kappa. Students are more often overestimated, but they may be a good option to preselect potential MRRs to save time for healthcare professionals. However, some MRRs will be missed.

The nurse-coordinated cardiac care bridge transitional care programme: a randomised clinical trial.

BACKGROUND: after hospitalisation for cardiac disease, older patients are at high risk of readmission and death. OBJECTIVE: the cardiac care bridge (CCB) transitional care programme evaluated the impact of combining case management, disease management and home-based cardiac rehabilitation (CR) on hospital readmission and mortality. DESIGN: single-blind, randomised clinical trial. SETTING: the trial was conducted in six hospitals in the Netherlands between June 2017 and March 2020. Community-based nurses and physical therapists continued care post-discharge. SUBJECTS: cardiac patients ≥ 70 years were eligible if they were at high risk of functional loss or if they had had an unplanned hospital admission in the previous 6 months. METHODS: the intervention group received a comprehensive geriatric assessment-based integrated care plan, a face-to-face handover with the community nurse before discharge and follow-up home visits. The community nurse collaborated with a pharmacist and participants received home-based CR from a physical therapist. The primary composite outcome was first all-cause unplanned readmission or mortality at 6 months. RESULTS: in total, 306 participants were included. Mean age was 82.4 (standard deviation 6.3), 58% had heart failure and 92% were acutely hospitalised. 67% of the intervention key-elements were delivered. The composite outcome incidence was 54.2% (83/153) in the intervention group and 47.7% (73/153) in the control group (risk differences 6.5% [95% confidence intervals, CI -4.7 to 18%], risk ratios 1.14 [95% CI 0.91-1.42], P = 0.253). The study was discontinued prematurely due to implementation activities in usual care. CONCLUSION: in high-risk older cardiac patients, the CCB programme did not reduce hospital readmission or mortality within 6 months. TRIAL REGISTRATION: Netherlands Trial Register 6,316, https://www.trialregister.nl/trial/6169.

Medication-Related Hospital Readmissions Within 30 Days of Discharge: Prevalence, Preventability, Type of Medication Errors and Risk Factors.

Background: Hospital readmission rates are increasingly used as a measure of healthcare quality. Medicines are the most common therapeutic intervention but estimating the contribution of adverse drug events as a cause of readmissions is difficult. Objectives: To assess the prevalence and preventability of medication-related readmissions within 30 days after hospital discharge and to describe the risk factors, type of medication errors and types of medication involved in these preventable readmissions. Design: A cross-sectional observational study. Setting: The study took place across the cardiology, gastroenterology, internal medicine, neurology, psychiatry, pulmonology and general surgery departments in the OLVG teaching hospital, Netherlands. Participants: Patients with an unplanned readmission within 30 days after discharge from an earlier hospitalization (index hospitalization: IH) were reviewed. Measurements: The prevalence and preventability of medication-related readmissions were assessed by residents in multidisciplinary meetings. A senior internist and hospital pharmacist reassessed the prevalence and preventability of identified cases. Generalized estimating equation with logistic regression was performed to identify risk factors of potentially preventable medication-related readmissions. Results: Of 1,111 included readmissions, 181 (16%) were medication-related, of which 72 (40%) were potentially preventable. The number of medication changes at IH (Adjusted odds ratio [ORadj]: 1.14; 95% CI: 1.05-1.24) and having ≥3 hospitalizations 6 months before IH (ORadj: 2.11; 95% CI: 1.12-3.98) were risk factors of a preventable medication-related readmission. Of these preventable readmissions, 35% were due to prescribing errors, 35% by non-adherence and 30% by transition errors. Medications most frequently involved were diuretics and antidiabetics. Conclusion: This study shows that 16% of readmissions are medication-related, of which 40% are potentially preventable. If the results are confirmed in larger multicentre studies, this may indicate that more attention should be paid to medication-related harm in order to lower the overall readmission rates.

Medication-related interventions delivered both in hospital and following discharge: a systematic review and meta-analysis.

BACKGROUND: Harm due to medications is common during the transition from hospital to home. Approaches that seek to prevent harm often involve isolated medication-related interventions and show conflicting results. However, until now, no review has focused on the effect of intervention components delivered both in hospital and following discharge from hospital to home. OBJECTIVE: To examine effects of medication-related interventions on hospital readmissions, medication-related problems (MRPs), medication adherence and mortality. METHODS: For this systematic review and meta-analysis, we searched the PubMed, Embase, CINAHL and CENTRAL databases without language restrictions. Citations of included articles were checked through Web of Science and Scopus from inception to 20 June 2019. We included prospective studies that examined effects of medication-related interventions delivered both in hospital and following discharge from hospital to home compared with usual care. Three authors independently extracted data and assessed study quality in pairs. RESULTS: Fourteen original studies were included, comprising 8182 patients. Interventions consisted mainly of patient education and medication reconciliation in the hospital, and patient education following discharge. Nine studies were included in the meta-analysis; compared with usual care (n=3376 patients), medication-related interventions (n=1820 patients) reduced hospital readmissions by 3.8 percentage points within 30 days of discharge (number needed to treat=27, risk ratio (RR) 0.79 (95% CI 0.65 to 0.96)). Meta-regression analysis suggested that readmission rates were reduced by 17% per additional intervention component (RR 0.83 (95% Cl 0.75 to 0.91)). Medication adherence and MRPs may be improved. Effects on mortality were unclear. CONCLUSIONS: Studied medication-related interventions reduce all-cause hospital readmissions within 30 days. The treatment effect appears to increase with higher intervention intensities. More evidence is needed for recommendations on adherence, mortality and MRPs.

Longitudinal medication reconciliation at hospital admission, discharge and post-discharge.

BACKGROUND: Medication reconciliation (MR) is a widely recognised method to promote patient safety. However, its implementation is generally limited to an interaction at a single transition point. OBJECTIVES: To examine the rates and types of changes implemented in patient's medication regimens when MR is performed longitudinally at hospital admission, discharge and post-discharge, and to assess the clinical impact. METHODS: A prospective multicentre cohort study was conducted in two hospitals. Patients received MR at admission, discharge and within five days post-discharge at home. Data was collected on rates and types of changes implemented in their medication regimens, due to MR, at all three transition points. These changes entailed corrections of unintentional discrepancies, e.g., between patients' actual medication use and physician prescriptions, and optimisations of pharmacotherapy, e.g., adding laxatives when opioids are prescribed. Using a validated instrument, the clinical impact of all medication changes were scored. Data were analysed using descriptive statistics. RESULTS: In total, 197 patients with a median age of 73 years were included. In 86.3% of patients at least one change was implemented in the medication regimen due to longitudinal MR. At admission, discharge and post-discharge, changes in medication regimens were necessary in 66.5%, 62.9% and 52.8% of patients, respectively. At admission and post-discharge, mainly unintentional discrepancies were corrected, and at discharge mainly optimisations were implemented. Implemented medication changes, due to longitudinal MR, prevented potential harm in 161 patients (81.7%). Potentially serious medication errors were most often prevented at hospital discharge, and predominantly involved optimising antithrombotic agents. CONCLUSIONS: Changes in medication regimens were implemented in 86.3% of patients due to longitudinal MR at admission, discharge and post-discharge. The rates and types of medication changes vary over time. Hospital discharge is an important moment for optimising pharmacotherapy.