Monika Lutters

Background: Bleeding complications are a major contributor to adverse drug events among older inpatients, particularly in those treated with antithrombotic agents. Timely and accurate detection of bleeding events is essential for improving drug safety surveillance and clinical risk management. Objective: The study aimed to develop and validate automated algorithms for detecting major bleeding (MB) and clinically relevant nonmajor bleeding (CRNMB) events from electronic medical records (EMRs) by combining structured data-based rule models and a natural language processing (NLP) approach, and to evaluate their performance and generalizability against a manually reviewed gold standard and an external dataset. Methods: We conducted a multicenter retrospective study using routinely collected EMR data from 3 Swiss university hospitals. Patients 65 years or older who received at least one antithrombotic agent and were hospitalized between January 2015 and December 2016 were included. To detect MB and CRNMB events, rule-based algorithms were developed using structured data ( International Statistical Classification of Diseases, 10th Revision, German Modification [ ICD-10-GM ] codes, laboratory values, transfusion records, and antihemorrhagic prescriptions), with variables and cutoff values defined according to adapted International Society on Thrombosis and Haemostasis definitions and expert consensus. In parallel, a supervised NLP model was applied to discharge summaries from one hospital. A manual review of 754 EMRs served as the reference standard for internal validation, and the algorithm performance of the structured data algorithms (SDA), NLP, and their combination (SDA+NLP) was evaluated against this manually reviewed gold standard using standard performance metrics. External validation was performed on an independent dataset from the Lausanne University Hospital to assess model robustness and generalizability. Results: Among 36,039 inpatient stays, SDA identified 8.26% (n=2979) as MB and 15.04% (n=5419) as CRNMB cases. ICD-10-GM codes alone detected 28.5% (n=849) of MB and 31.48% (n=1706) of CRNMB cases, while laboratory data contributed most to event detection (n=1994, 66.94% for MB and n=3663, 67.60% for CRNMB). Integrating SDA with NLP improved detection, identifying 12.2% (920/7513) of MB and 27.4% (2062/7513) of CRNMB cases at 1 hospital. The combined model achieved the best performance (sensitivity 0.84, positive predictive value 0.51, F ₁ -score 0.64). External validation on Lausanne University Hospital 2021‐2022 data (n=24,054 stays) confirmed the algorithms’ reproducibility; the prevalence of MB decreased while CRNMB increased, reflecting evolving clinical practices and antithrombotic use patterns. Conclusions: Our integrated approach, combining SDA with NLP, enhances the detection of hemorrhagic events in older hospitalized patients treated with antithrombotic agents, suggesting its potential usefulness for drug safety monitoring and clinical risk management.

AIMS OF THE STUDY: Opioid prescriptions have increased in Switzerland, even though current guidelines warn of their harms. If opioids for postoperative analgesia are not tapered before hospital discharge, patients are at risk of adverse events such as constipation, drowsiness, dependence, tolerance and withdrawal. The aim of this study was to investigate and quantify the potential association between opioids prescribed at discharge from hospital and rehospitalisation. METHODS: We conducted a nested case-control study using routinely collected electronic health records from a Swiss public acute hospital. Cases were patients aged 65 years or older admitted between November 2014 and December 2018, with documented opioid administration on the day of discharge and rehospitalisation within 18 or 30 days after discharge. Each case was matched to five controls for age, sex, year of hospitalisation and Charlson Comorbidity Index. We calculated odds ratios for 18-day and 30-day rehospitalisation based on exposure to opioids using a conditional logistic regression adjusted for potential confounders. Secondary analyses included stratifications into morphine-equivalent doses of <50 mg, 50–89 mg and ≥90 mg, and co-prescriptions of gabapentinoids and benzodiazepines. RESULTS: Of 22,471 included patients, 3144 rehospitalisations were identified, of which 1698 were 18-day rehospitalisations and 1446 were 30-day rehospitalisations. Documented opioid administration on the day of discharge was associated with 30-day rehospitalisation after adjustment for confounders (adjusted odds ratio 1.48; 95% CI 1.25–1.75, p 50 mg were rare. CONCLUSIONS: Patients receiving opioids on the day of discharge were 48% more likely to be readmitted to hospital within 30 days. Clinicians should aim to discontinue opioids started in hospital before discharge if possible. Patients receiving an opioid prescription should be educated and monitored as part of opioid stewardship programmes.

Objectives Medication management is a core process in hospital administration. The safety, timeliness and efficiency of medication distribution may be improved by automating logistical and administrative aspects of the process. Forming an accurate high-level picture of current practices may help decision-makers to better advance the state of automation. This study aims to identify which systems for automating the medication process are currently in use in Swiss hospitals, and to what extent each system is used. Methods A 27-question survey was developed and distributed to Swiss Association of Public Health Administration and Hospital Pharmacists (GSASA) members. The survey focused on enterprise resource planning (ERP) systems, automation of in-hospital distribution and dispensing of pharmaceutical goods, bedside scanning, and the management of drug master data. Results The response rate was 98% (58/59 hospital pharmacies). All institutions had an ERP system in use, most frequently SAP (n=23, 39%). Electronic invoices from suppliers were fully processed by 37% and partially processed by 17% of respondents. Twenty-five percent of respondents reported performing bedside scanning for the purpose of medication administration. Automated medication distribution systems were available in 20 hospitals (34%), of which 13 were central robots and seven were decentralised systems. Conclusion A considerable gap remains to achieve closed loop processes between multiple systems. The present results provide an inventory of existing systems and current trends for use by decision-makers in hospitals and hospital pharmacies.

(1) Background: Pharmacists are often challenged with situations where women are already on hormonal contraceptives (HC) but have no valid prescription. By Swiss law, pharmacists are allowed to supply prescription-only drugs in exceptional situations without a physician’s prescription. Because eligibility for HC can change, women at risk for complications, such as serious side effects, need to be identified. We aimed to develop a protocol to assist pharmacists in clarifying and documenting eligibility for HC. (2) Methods: We conducted a survey using the Delphi method to identify relevant clarifications and develop a protocol for pharmacists. Proposed material was created based on the literature and existing toolkits/protocols aimed at verifying eligibility for HC. A multidisciplinary expert panel, consisting of gynecologists and pharmacists, reviewed the proposed material and provided anonymized feedback over two survey cycles. (3) Results: This Delphi survey revealed items essential to the clarification of eligibility for HC in pharmacies for women who are already using it. This resulted in a protocol that maps “best practices” regarding these ad interim supplies of HC given without a prescription in Switzerland. (4) Conclusions: This survey, made using the Delphi method, allowed us to create a protocol for pharmacists that aims to verify and document eligibility for HC in Switzerland, where HC is frequently supplied without a prescription.

Background: One-third of older inpatients experience adverse drug events (ADEs), which increase their mortality, morbidity, and health care use and costs. In particular, antithrombotic drugs are among the most at-risk medications for this population. Reporting systems have been implemented at the national, regional, and provider levels to monitor ADEs and design prevention strategies. Owing to their well-known limitations, automated detection technologies based on electronic medical records (EMRs) are being developed to routinely detect or predict ADEs. Objective: This study aims to develop and validate an automated detection tool for monitoring antithrombotic-related ADEs using EMRs from 4 large Swiss hospitals. We aim to assess cumulative incidences of hemorrhages and thromboses in older inpatients associated with the prescription of antithrombotic drugs, identify triggering factors, and propose improvements for clinical practice. Methods: This project is a multicenter, cross-sectional study based on 2015 to 2016 EMR data from 4 large hospitals in Switzerland: Lausanne, Geneva, and Zürich university hospitals, and Baden Cantonal Hospital. We have included inpatients aged ≥65 years who stayed at 1 of the 4 hospitals during 2015 or 2016, received at least one antithrombotic drug during their stay, and signed or were not opposed to a general consent for participation in research. First, clinical experts selected a list of relevant antithrombotic drugs along with their side effects, risks, and confounding factors. Second, administrative, clinical, prescription, and laboratory data available in the form of free text and structured data were extracted from study participants’ EMRs. Third, several automated rule-based and machine learning–based algorithms are being developed, allowing for the identification of hemorrhage and thromboembolic events and their triggering factors from the extracted information. Finally, we plan to validate the developed detection tools (one per ADE type) through manual medical record review. Performance metrics for assessing internal validity will comprise the area under the receiver operating characteristic curve, F1-score, sensitivity, specificity, and positive and negative predictive values. Results: After accounting for the inclusion and exclusion criteria, we will include 34,522 residents aged ≥65 years. The data will be analyzed in 2022, and the research project will run until the end of 2022 to mid-2023. Conclusions: This project will allow for the introduction of measures to improve safety in prescribing antithrombotic drugs, which today remain among the drugs most involved in ADEs. The findings will be implemented in clinical practice using indicators of adverse events for risk management and training for health care professionals; the tools and methodologies developed will be disseminated for new research in this field. The increased performance of natural language processing as an important complement to structured data will bring existing tools to another level of efficiency in the detection of ADEs. Currently, such systems are unavailable in Switzerland. International Registered Report Identifier (IRRID): DERR1-10.2196/40456

Background The state of digitalisation in the healthcare sector in Switzerland is lagging, even as the national electronic health record (EHR) is being gradually implemented. Little is known about the implementation of electronic prescribing systems, their auxiliary features or drug datasets in Swiss hospitals. The aim of this study was to understand which electronic systems are implemented to support doctors in Swiss hospitals during the medication prescribing process. Methods The survey was sent in spring 2021 to the chief pharmacists of the main Swiss hospitals. The survey focused on the introduction of the EHR, the clinical information system (CIS) and its prescribing module, as well as drug information data and clinical decision support systems (CDSS). Results The response rate was 98% (58/59 hospitals). Almost half of the hospitals (47%) were connected to the national EHR, almost all hospitals (86%) used a CIS and a vast majority of the hospitals (84%) had implemented electronic prescribing systems in their CIS. 10 years ago, around 63% of hospitals used a CIS and 40% were equipped with an electronic prescribing system. Today, CDSS of any kind were implemented in 50% of the hospitals, predominantly for drug-drug interactions. Drug master data were maintained in most hospitals (76%) via an automated interface, but mostly supplemented manually. Clinical drug information data were maintained in 74% of hospitals. In 67% of hospitals, datasets were imported via an automated interface. Conclusions The digitalisation of the medical prescribing process in Swiss hospitals has progressed over the last decade. Drug prescriptions via electronic prescribing systems were introduced in most hospitals. However, this survey suggests that the current use of CDSS is far from exhausted, and that clinical drug information data could be maintained more efficiently. Optimising electronic support for healthcare professionals during the prescribing process still has considerable potential.

Background: Readmission prediction models have been developed and validated for targeted in-hospital preventive interventions. We aimed to externally validate the Potentially Avoidable Readmission-Risk Score (PAR-Risk Score), a 12-items prediction model for internal medicine patients with a convenient scoring system, for our local patient cohort.Methods: A cohort study using electronic health record data from the internal medicine ward of a Swiss tertiary teaching hospital was conducted. The individual PAR-Risk Score values were calculated for each patient. Univariable logistic regression was used to predict potentially avoidable readmissions (PARs), as identified by the SQLape algorithm. For additional analyses, patients were stratified intolow,medium, andhighrisk according to tertiles based on the PAR-Risk Score. Statistical associations between predictor variables and PAR as outcome were assessed using both univariable and multivariable logistic regression.Results: The final dataset consisted of 5,985 patients. Of these, 340 patients (5.7%) experienced a PAR. The overall PAR-Risk Score showed rather poor discriminatory power (C statistic 0.605, 95%-CI 0.575–0.635). When using stratified groups (low,medium,high), patients in thehigh-risk group were at statistically significant higher odds (OR 2.63, 95%-CI 1.33–5.18) of being readmitted within 30 days compared tolowrisk patients. Multivariable logistic regression identified previous admission within six months, anaemia, heart failure, and opioids to be significantly associated with PAR in this patient cohort.Conclusion: This external validation showed a limited overall performance of the PAR-Risk Score, although higher scores were associated with an increased risk for PAR and patients in thehigh-risk group were at significantly higher odds of being readmitted within 30 days. This study highlights the importance of externally validating prediction models.

(1) Background: Access to hormonal contraceptives (HC) strongly differs between countries and varies from over the counter (OTC) to prescription-only availability. This study aimed to identify opinions among physicians in Switzerland regarding extended access to HC. (2) Methods: Web-based survey among physicians (gynecologists, general practitioners, and pediatricians) in Switzerland. (3) Results: Hundred sixty-three physicians, mainly gynecologists, participated in this survey and 147 (90%) were included for analysis. A total of 68% (n = 100) answered that prescription-only status could be extended under certain conditions but physicians were concerned about patients’ safety (97%, n = 142). Moreover, there was concern about insufficient patient education on HC (93%, n = 136) and that women may forego preventive examinations (80%, n = 118). Participants did not support OTC availability (93%, n = 136). Pharmacists prescribing (including initiation of HC) revealed controversial results, but a combined access model (initial prescription from physician and follow-up prescriptions by pharmacists) found acceptance in 70% (n = 103). (4) Conclusions: Participating physicians stated that prescription-only status for HC could be lifted under certain conditions but also some concerns, e.g., patients’ safety or neglection of preventive examinations, were raised. Future research should focus on specific conditions in which extended access to HC could be agreed on.

Background: Worldwide the availability to Hormonal Contraceptives (HC) varies from over the counter (OTC) to prescription-only access. In various countries pharmacists are allowed to prescribe HC, although conditions may be different. In Switzerland, HC require a prescription from a physician, although Swiss law allows pharmacists to dispense prescription-only medications in justified exceptional cases without a valid physician’s prescription. This study aimed to identify current dispensing practices for HC in Swiss pharmacies, pharmacists’ knowledge about HC, and their opinion and interest about expanding access to HC. Methods: Web-based survey among Swiss pharmacists. Results: This survey was completed by 397 registered pharmacists and 331 (83%) were included for analysis. The survey showed that 21% of respondents regularly dispense HC without prescription and that a high number of participants are either very interested (57%, n = 189) or rather interested (33%, n = 110) in extended pharmacy access to HC. The majority did not or rather not support physician’s prescription-only status (77%, n = 256) or OTC availability (94%, n = 310). Furthermore, surveyed pharmacists are willing to train for contraception services (90%, n = 299). According to participants, resistance of physicians is the most relevant barrier to this service (88%, n = 292). Conclusion: Surveyed pharmacists are interested in extended access to HC.

Purpose: The purpose of this paper is to determine the prevalence of polypharmacy and drug–drug interactions (DDIs) in older and younger prisoners, and compared if age group is associated with risks of polypharmacy and DDIs.Design/methodology/approach: For 380 prisoners from Switzerland (190 were 49 years and younger; 190 were 50 years and older), data concerning their medication use were gathered. MediQ identified if interactions of two or more substances could lead to potentially adverse DDI. Data were analysed using descriptive statistics and generalised linear mixed models.Findings: On average, older prisoners took 3.8 medications, while younger prisoners took 2.1 medications. Number of medications taken on one reference day was higher by a factor of 2.4 for older prisoners when compared to younger prisoners (p= 0.002). The odds of polypharmacy was significantly higher for older than for younger prisoners (>=5 medications: odds ratio = 5.52,p= 0.035). Age group analysis indicated that for potentially adverse DDI there was no significant difference (odds ratio = 0.94;p= 0.879). However, when controlling for the number of medication, the risk of adverse DDI was higher in younger than older prisoners, but the result was not significant.Originality/value: Older prisoners are at a higher risk of polypharmacy but their risk for potentially adverse DDI is not significantly different from that of younger prisoners. Special clinical attention must be given to older prisoners who are at risk for polypharmacy. Careful medication management is also important for younger prisoners who are at risk of very complex drug therapies.