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Mannitol is the major compatible solute, next to glutamate, synthesized by the opportunistic human pathogen Acinetobacter baumannii under low water activities. The key enzyme for mannitol biosynthesis, MtlD, was identified. MtlD is highly similar to the bifunctional mannitol‐1‐phosphate dehydrogenase/phosphatase from Acinetobacter baylyi. After deletion of the mtlD gene from A. baumannii ATCC 19606T cells no longer accumulated mannitol and growth was completely impaired at high salt. Addition of glycine betaine restored growth, demonstrating that mannitol is an important compatible solute in the human pathogen. MtlD was heterologously produced and purified. Enzyme activity was strictly salt dependent. Highest stimulation was reached at 600 mmol/L NaCl. Addition of different sodium as well as potassium salts restored activity, with highest stimulations up to 41 U/mg protein by sodium glutamate. In contrast, an increase in osmolarity by addition of sugars did not restore activity. Regulation of mannitol synthesis was also assayed at the transcriptional level. Reporter gene assays revealed that expression of mtlD is strongly dependent on high osmolarity, not discriminating between different salts or sugars. The presence of glycine betaine or its precursor choline repressed promoter activation. These data indicate a dual regulation of mannitol production in A. baumannii, at the transcriptional and the enzymatic level, depending on high osmolarity.
Background: Oral anticoagulants can cause potentially serious adverse events. Therefore, before prescribing oral anticoagulants for ischemic stroke prevention in patients with atrial fibrillation (AF), stroke risk assessment is required to identify patients that are likely to benefit from treatment. Current guidelines recommend the CHA2DS2-VASc-score for stroke risk assessment. The CHA2DS2-VASc-score is based on observational studies from different treatment settings and countries. As ischemic stroke risk differs by setting and region, the aim of this study is to estimate ischemic stroke risk (stratified by the CHA2DS2-VASc-score) for a broadly representative population with AF from southern Germany and compare them to results from previous studies.
Methods: The study design is a retrospective cohort study on patients with atrial fibrillation based on secondary data. We calculated CHA2DS2-VASc-score based on patient’s diagnoses recorded in the year 2014 and assessed outcomes in 2015–2016. The primary outcome is hospitalization for ischemic stroke. The secondary outome is hospitalizations for any thromboembolic event, including ischemic stroke, transient ischemic attack, peripheral arterial embolism, pulmonary embolism, and mesenterial embolism. We estimated the incidence rates of the outcomes (and corresponding 95%-confidence intervals) stratified by CHA2DS2-VASc-score.
Results: The primary endpoint occurred in 961 of the 30,299 patients constituting the study population, resulting in a total incidence rate of 2.2 per 100 person-years. The secondary endpoint occurred in 1553 patients (3.6 per 100 person-years). Ischemic stroke rates stratified by the CHA2DS2-VASc-score tended to be lower than those reported previously. Thromboembolic event rates stratified tended to be similar to those reported previously.
Conclusions: Our results show that the performance of the CHA2DS2-VASc-score differs in the German population, as compared to internationally published data, with an overall trend towards lower risk of ischemic stroke in uncoagulated patients with AF. These results should not be practice changing, but they emphasize that stroke risk estimation in patients with atrial fibrillation should be further refined.
Background and Aims: The prevalence of hepatitis C virus (HCV) antibodies in Germany has been estimated to be in the range of 0.4–0.63%. Screening for HCV is recommended in patients with elevated ALT levels or significant risk factors for HCV transmission only. However, 15–30% of patients report no risk factors and ALT levels can be normal in up to 20–30% of patients with chronic HCV infection. The aim of this study was to assess the HCV seroprevalence in patients visiting two tertiary care emergency departments in Berlin and Frankfurt, respectively.
Methods: Between May 2008 and March 2010, a total of 28,809 consecutive patients were screened for the presence of anti-HCV antibodies. Anti-HCV positive sera were subsequently tested for HCV-RNA.
Results: The overall HCV seroprevalence was 2.6% (95% CI: 2.4–2.8; 2.4% in Berlin and 3.5% in Frankfurt). HCV-RNA was detectable in 68% of anti-HCV positive cases. Thus, the prevalence of chronic HCV infection in the overall study population was 1.6% (95% CI 1.5–1.8). The most commonly reported risk factor was former/current injection drug use (IDU; 31.2%) and those with IDU as the main risk factor were significantly younger than patients without IDU (p<0.001) and the male-to-female ratio was 72% (121 vs. 46 patients; p<0.001). Finally, 18.8% of contacted HCV-RNA positive patients had not been diagnosed previously.
Conclusions: The HCV seroprevalence was more than four times higher compared to current estimates and almost one fifth of contacted HCV-RNA positive patients had not been diagnosed previously.
Background: Although polypharmacy can cause adverse health outcomes, patients often know little about their medication. A regularly conducted medication review (MR) can help provide an overview of a patient’s medication, and benefit patients by enhancing their knowledge of their drugs. As little is known about patient attitudes towards MRs in primary care, the objective of this study was to gain insight into patient-perceived barriers and facilitators to the implementation of an MR.
Methods: We conducted a qualitative study with a convenience sample of 31 patients (age ≥ 60 years, ≥3 chronic diseases, taking ≥5 drugs/d); in Hesse, Germany, in February 2016. We conducted two focus groups and, in order to ensure the participation of elderly patients with reduced mobility, 16 telephone interviews. Both relied on a semi-structured interview guide dealing with the following subjects: patients’ experience of polypharmacy, general design of MRs, potential barriers and facilitators to implementation etc. Interviews were audio-recorded, transcribed verbatim, and analysed by two researchers using thematic analysis.
Results: Patients’ average age was 74 years (range 62–88 years). We identified barriers and facilitators for four main topics regarding the implementation of MRs in primary care: patient participation, GP-led MRs, pharmacist-led MRs, and the involvement of healthcare assistants in MRs. Barriers to patient participation concerned patient autonomy, while facilitators involved patient awareness of medication-related problems. Barriers to GP-led MRs concerned GP’s lack of resources while facilitators related to the trusting relationship between patient and GP. Pharmacist-led MRs might be hindered by a lack of patients’ confidence in pharmacists’ expertise, but facilitated by pharmacies’ digital records of the patients’ medications. Regarding the involvement of healthcare assistants in MRs, a potential barrier was patients’ uncertainty regarding the extent of their training. Patients could, however, imagine GPs delegating some aspects of MRs to them.
Conclusions: Our study suggests that patients regard MRs as beneficial and expect indications for their medicines to be checked, and possible interactions to be identified. To foster the implementation of MRs in primary care, it is important to consider barriers and facilitators to the four identified topics.
Background Polypharmacy interventions are resource-intensive and should be targeted to those at risk of negative health outcomes. Our aim was to develop and internally validate prognostic models to predict health-related quality of life (HRQoL) and the combined outcome of falls, hospitalisation, institutionalisation and nursing care needs, in older patients with multimorbidity and polypharmacy in general practices.
Methods Design: two independent data sets, one comprising health insurance claims data (n=592 456), the other data from the PRIoritising MUltimedication in Multimorbidity (PRIMUM) cluster randomised controlled trial (n=502). Population: ≥60 years, ≥5 drugs, ≥3 chronic diseases, excluding dementia. Outcomes: combined outcome of falls, hospitalisation, institutionalisation and nursing care needs (after 6, 9 and 24 months) (claims data); and HRQoL (after 6 and 9 months) (trial data). Predictor variables in both data sets: age, sex, morbidity-related variables (disease count), medication-related variables (European Union-Potentially Inappropriate Medication list (EU-PIM list)) and health service utilisation. Predictor variables exclusively in trial data: additional socio-demographics, morbidity-related variables (Cumulative Illness Rating Scale, depression), Medication Appropriateness Index (MAI), lifestyle, functional status and HRQoL (EuroQol EQ-5D-3L). Analysis: mixed regression models, combined with stepwise variable selection, 10-fold cross validation and sensitivity analyses.
Results Most important predictors of EQ-5D-3L at 6 months in best model (Nagelkerke’s R² 0.507) were depressive symptoms (−2.73 (95% CI: −3.56 to −1.91)), MAI (−0.39 (95% CI: −0.7 to −0.08)), baseline EQ-5D-3L (0.55 (95% CI: 0.47 to 0.64)). Models based on claims data and those predicting long-term outcomes based on both data sets produced low R² values. In claims data-based model with highest explanatory power (R²=0.16), previous falls/fall-related injuries, previous hospitalisations, age, number of involved physicians and disease count were most important predictor variables.
Conclusions Best trial data-based model predicted HRQoL after 6 months well and included parameters of well-being not found in claims. Performance of claims data-based models and models predicting long-term outcomes was relatively weak. For generalisability, future studies should refit models by considering parameters representing well-being and functional status.
Introduction: Clinically complex patients often require multiple medications. Polypharmacy is associated with inappropriate prescriptions, which may lead to negative outcomes. Few effective tools are available to help physicians optimise patient medication. This study assesses whether an electronic medication management support system (eMMa) reduces hospitalisation and mortality and improves prescription quality/safety in patients with polypharmacy. Methods and analysis: Planned design: pragmatic, parallel cluster-randomised controlled trial; general practices as randomisation unit; patients as analysis unit. As practice recruitment was poor, we included additional data to our primary endpoint analysis for practices and quarters from October 2017 to March 2021. Since randomisation was performed in waves, final study design corresponds to a stepped-wedge design with open cohort and step-length of one quarter. Scope: general practices, Westphalia-Lippe (Germany), caring for BARMER health fund-covered patients. Population: patients (≥18 years) with polypharmacy (≥5 prescriptions). Sample size: initially, 32 patients from each of 539 practices were required for each study arm (17 200 patients/arm), but only 688 practices were randomised after 2 years of recruitment. Design change ensures that 80% power is nonetheless achieved. Intervention: complex intervention eMMa. Follow-up: at least five quarters/cluster (practice). recruitment: practices recruited/randomised at different times; after follow-up, control group practices may access eMMa. Outcomes: primary endpoint is all-cause mortality and hospitalisation; secondary endpoints are number of potentially inappropriate medications, cause-specific hospitalisation preceded by high-risk prescribing and medication underuse. Statistical analysis: primary and secondary outcomes are measured quarterly at patient level. A generalised linear mixed-effect model and repeated patient measurements are used to consider patient clusters within practices. Time and intervention group are considered fixed factors; variation between practices and patients is fitted as random effects. Intention-to-treat principle is used to analyse primary and key secondary endpoints.
Background: Experienced and anticipated regret influence physicians’ decision-making. In medicine, diagnostic decisions and diagnostic errors can have a severe impact on both patients and physicians. Little empirical research exists on regret experienced by physicians when they make diagnostic decisions in primary care that later prove inappropriate or incorrect. The aim of this study was to explore the experience of regret following diagnostic decisions in primary care.
Methods: In this qualitative study, we used an online questionnaire on a sample of German primary care physicians. We asked participants to report on cases in which the final diagnosis differed from their original opinion, and in which treatment was at the very least delayed, possibly resulting in harm to the patient. We asked about original and final diagnoses, illness trajectories, and the reactions of other physicians, patients and relatives. We used thematic analysis to assess the data, supported by MAXQDA 11 and Microsoft Excel 2016.
Results: 29 GPs described one case each (14 female/15 male patients, aged 1.5–80 years, response rate < 1%). In 26 of 29 cases, the final diagnosis was more serious than the original diagnosis. In two cases, the diagnoses were equally serious, and in one case less serious. Clinical trajectories and the reactions of patients and relatives differed widely. Although only one third of cases involved preventable harm to patients, the vast majority (27 of 29) of physicians expressed deep feelings of regret.
Conclusion: Even if harm to patients is unavoidable, regret following diagnostic decisions can be devastating for clinicians, making them ‘second victims’. Procedures and tools are needed to analyse cases involving undesirable diagnostic events, so that ‘true’ diagnostic errors, in which harm could have been prevented, can be distinguished from others. Further studies should also explore how physicians can be supported in dealing with such events in order to prevent them from practicing defensive medicine.
Background: Critical incident reporting systems (CIRS) can be an important tool for the identification of organisational safety needs and thus to improve patient safety. In German primary care, CIRS use is obligatory but remains rare. Studies on CIRS implementation in primary care are lacking, but those from secondary care recommend involving management personnel.
Objective: This project aimed to increase CIRS use in 69 practices belonging to a local practice network.
Methods: The intervention consisted of the provision of a web-based CIRS, accompanying measures to train practice teams in error management and CIRS, and the involvement of the network’s management. Three measurements were used: (1) number of incident reports and user access rates to the web-based CIRS were recorded, (2) staff were given a questionnaire addressing incident reporting, error management and safety climate and (3) qualitative reflection conferences were held with network management.
Results: Over 20 months, 17 critical incidents were reported to the web-based CIRS. The number of staff intending to report the next incident online decreased from 42% to 20% of participants. In contrast, the number of practices using an offline CIRS (eg, incident book) increased from 23% to 49% of practices. Practices also began proactively approaching network management for help with incidents. After project completion, participants scored higher in the patient safety climate factor ‘perception of causes of errors’. For many practices, the project provided the first contact with structured error management.
Conclusion: Specific measures to improve the use of CIRS in primary care should focus on network management and practice owners. Practices need basic training on safety culture and error management. Continuing, practices should implement an offline CIRS, before they can profit from the exchange of reports via web-based CIRS. It is crucial that practices receive feedback on incidents, and trained network management personnel can provide such support.
[Jahresbericht 2014] Katholische Theologie der Johann Wolfgang Goethe-Universität Frankfurt am Main
(2014)
Hintergrund und Fragestellung: Patientensicherheit ist in den letzten Jahren zum intensiv diskutierten Thema geworden. Zudem rückt als potenzielle Basis der Patientensicherheit die Patientensicherheitskultur von Einrichtungen des Gesundheitswesens in den Fokus, bislang wurde dahingehend vor allem der stationäre Bereich untersucht. Ziel dieser Arbeit ist es, einen Einblick in den aktuellen Stand der Patientensicherheitskultur in Hausarztpraxen zu geben, und diesbezügliche Einflussfaktoren und Zusammenhänge aufzuzeigen. Dabei wurden insbesondere zwei Fragestellungen untersucht: 1. Lässt sich ein Zusammenhang aufzeigen zwischen einzelnen Praxis- und Teammerkmalen einerseits und den Ergebnissen in den Bereichen Sicherheitsklima, Patientensicherheitsindikatoren und Fehlermanagement andererseits? 2. Lassen sich durch einzelne Praxis- und Teammerkmale bzw. Sicherheitsklimafaktoren die Ausprägungen einer Praxis in bestimmten Patientensicherheitsindikatoren und dem Fehlermanagement einer Praxis vorhersagen?
Material und Methoden: In 60 allgemeinärztlich tätigen Praxen aus Hessen wurde die Patientensicherheitskultur anhand von drei Methoden gemessen. Dies waren 1. der auf Selbstauskunft beruhende „Fragebogen zum Sicherheitsklima“, 2. durch Praxisbegehungen und Interviews erfasste Patientensicherheitsindikatoren, sowie 3. detailliert analysierte Fehlerberichte. Die statistische Auswertung umfasste u.a. Korrelationsanalysen (Mann-Whitney-U, Wilcoxon-W, Spearman-Rangkorrelation) sowie multivariate schrittweise Regressionsanalysen.
Ergebnisse: Die Beurteilung des Sicherheitsklimas fiel über alle Praxen hinweg homogen positiv aus (acht von neun Sicherheitsklimafaktoren mit Mittelwerten von mind. vier von fünf Punkten). Bei den 12 Patientensicherheitsindikatoren ergaben sich differenziertere Werte (niedrigster Mittelwert: Indikator „Marcumartherapie“ mit 0,43 von 1, höchster Mittelwert: Indikator „Allergiehinweis“ mit 0,75 von 1). Es gingen 24 Berichte kritischer Ereignisse ein, die zu 79% als „Kein Fehlermanagement“ oder „Unbefriedigendes Fehlermanagement“ beurteilt wurden. Die Korrelations- und Regressionsanalysen zeigten Zusammenhänge auf, z.B. erzielten größere Praxisteams niedrigere Werte beim Patientensicherheitsklima und höhere Werte bei den Patientensicherheitsindikatoren im Vergleich zum Durchschnitt.
Diskussion: Sicherheitsklima, Patientensicherheitsindikatoren und Fehlermanagement sind in einer Hausarztpraxis mit den verwendeten Instrumenten messbar. Jedes der drei Instrumente misst einen anderen, wichtigen Bereich der Sicherheitskultur, wodurch jeweils unterschiedliche Einstellungen und Prozesse beleuchtet und anschließend auch beurteilt und verbessert werden können. In den Analysen zur Beantwortung der beiden Fragestellungen konnten Zusammenhänge und Vorhersagevariablen herausgearbeitet werden, allerdings waren diese Zusammenhänge zum Teil entgegengesetzt. Daraus ergibt sich die Hypothese, dass Praxis- und Teammerkmale als Voraussetzungen zu unterschiedlichen Ausprägungen von Sicherheitsklima, Patientensicherheitsindikatoren und Fehlermanagement führen können. Insgesamt könnte die Qualität der hausärztlichen Arbeit und die Sicherheit der Versorgung durch eine regelmäßige Reflektion der Praxisabläufe anhand der drei Messmethoden gesteigert werden.