Regional Differences in Thrombectomy Rates

Haverkamp, Christian; Ganslandt, Thomas; Horki, Petar; Boeker, Martin; Dörfler, Arnd; Schwab, Stefan; Berkefeld, Joachim; Pfeilschifter, Waltraud; Niesen, Wolf‐Dirk; Egger, Karl; Kaps, Manfred; Brockmann, Marc A.; Neumaier-Probst, Eva; Szabo, Kristina; Skalej, Martin; Bien, Siegfried; Best, C.; Prokosch, Hans‐Ulrich; Urbach, Horst

doi:10.1007/s00062-017-0656-y

Cited by 16 publications

(9 citation statements)

References 23 publications

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“…By agreeing on a common data model, the environment distributed to all participating sites provided the means to perform the same SQL statements and analysis scripts across all partnering hospitals and to deliver standardized aggregated data back to the UHE DIC team. This analysis approach was based on concepts that have already been applied for earlier distributed analyses pursued within the federated MIRACUM DIC infrastructure (15,25). Participating sites had to retrieve the respective docker container and subsequently prepare their local data to be loaded into the infrastructure environment.…”

Section: Data Acquisition and Data Governancementioning

confidence: 99%

“…The fundamental concept for all consortia and for crossconsortial cooperation, however, is a federated approach, that is, the data remain locally within each university hospitals' data repository and the analysis algorithms are distributed to the sites for joint analysis projects. At an early stage, this approach was already used to analyze regional differences in thrombectomy rates in stroke patients across the 10 MIRACUM university hospitals (15). In 2018/2019, the capabilities for data sharing across the sites of all MII consortia were illustrated by a demonstrator study, which focused on the analysis of comorbidity and rare diseases (16).…”

Section: Introductionmentioning

confidence: 99%

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Reduced Rate of Inpatient Hospital Admissions in 18 German University Hospitals During the COVID-19 Lockdown

Kapsner

Kampf

Seuchter

et al. 2021

Front. Public Health

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The COVID-19 pandemic has caused strains on health systems worldwide disrupting routine hospital services for all non-COVID patients. Within this retrospective study, we analyzed inpatient hospital admissions across 18 German university hospitals during the 2020 lockdown period compared to 2018. Patients admitted to hospital between January 1 and May 31, 2020 and the corresponding periods in 2018 and 2019 were included in this study. Data derived from electronic health records were collected and analyzed using the data integration center infrastructure implemented in the university hospitals that are part of the four consortia funded by the German Medical Informatics Initiative. Admissions were grouped and counted by ICD 10 chapters and specific reasons for treatment at each site. Pooled aggregated data were centrally analyzed with descriptive statistics to compare absolute and relative differences between time periods of different years. The results illustrate how care process adoptions depended on the COVID-19 epidemiological situation and the criticality of the disease. Overall inpatient hospital admissions decreased by 35% in weeks 1 to 4 and by 30.3% in weeks 5 to 8 after the lockdown announcement compared to 2018. Even hospital admissions for critical care conditions such as malignant cancer treatments were reduced. We also noted a high reduction of emergency admissions such as myocardial infarction (38.7%), whereas the reduction in stroke admissions was smaller (19.6%). In contrast, we observed a considerable reduction in admissions for non-critical clinical situations, such as hysterectomies for benign tumors (78.8%) and hip replacements due to arthrosis (82.4%). In summary, our study shows that the university hospital admission rates in Germany were substantially reduced following the national COVID-19 lockdown. These included critical care or emergency conditions in which deferral is expected to impair clinical outcomes. Future studies are needed to delineate how appropriate medical care of critically ill patients can be maintained during a pandemic.

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Section: Data Acquisition and Data Governancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reduced Rate of Inpatient Hospital Admissions in 18 German University Hospitals During the COVID-19 Lockdown

Kapsner

Kampf

Seuchter

et al. 2021

Front. Public Health

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“…Both stroke categories show a clear benefit of treatment with better outcome measured by mRS. Earlier studies in Germany (11,12), Spain (13) and Japan (14) showed no in-hospital difference regarding daytime and weekday of stroke admission. A small study in Nashville, USA compared transportation times for myocardial infarction and showed no significant differences between weekdays and weekends (15).…”

Section: Discussionmentioning

confidence: 76%

Stroke severity predicts transportation time and time until recanalization therapy in acute strokes

Mausbach

Jünemann

Braun

et al. 2019

Preprint

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Background Ischemic stroke has rising prevalence in aging populations. Treatment depends on quick symptom recognition, transport to a hospital with a dedicated stroke care, imaging, and initiation of treatment, if indicated. The aim of this study is to show that transport, imaging, and treatment times depend on the severeness of the stroke, with more severe strokes being favored. Methods Statistical analysis was performed with data from a registry for quality assurance in stroke care in Hesse, Germany. Data was analyzed regarding ICD-10, and patients with I63 were further investigated. Patients with NIHSS ≥ 4 were included and subdivided into 4 ≤ NIHSS ≤ 11 (moderate stroke) and NIHSS ≥ 12 (severe stroke). Transport to hospital, time to image, and time to treatment were analyzed. Results Patients with severe strokes reach the hospital faster and in higher numbers in comparison to moderate strokes. If appropriate therapy is applied, in-hospital treatment regarding imaging is similar in both groups. Thrombolysis or endovascular treatment is initiated faster for severe strokes. Conclusion More public awareness of strokes is needed, specifically for moderate strokes to reach faster transport times to hospital as well as modern treatment options up to 24 hours for eligible patients. Individual standards need to be applied in each stroke treating hospital to guarantee the same fast treatment times for moderate and severe strokes.

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“…After approval of such analysis by the local use and access committees (UAC), the predefined analysis were retrieved at each side and executed on the respective local data repositories. Research questions analyzed in the DIC’s stroke patients subcohort focused on acute treatment measures of acute ischemic stroke patients (and their development over time) between 2010 and 2016 [ 50 ]. The colorectal cancer cohort was analyzed to compare the distribution and pathway of therapeutic procedures within this patient subset.…”

Section: First Resultsmentioning

confidence: 99%

MIRACUM: Medical Informatics in Research and Care in University Medicine

Prokosch¹,

Acker²,

Bernarding³

et al. 2018

Methods Inf Med

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110

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Summary Introduction: This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. Similar to other large international data sharing networks (e.g. OHDSI, PCORnet, eMerge, RD-Connect) MIRACUM is a consortium of academic and hospital partners as well as one industrial partner in eight German cities which have joined forces to create interoperable data integration centres (DIC) and make data within those DIC available for innovative new IT solutions in patient care and medical research. Objectives: Sharing data shall be supported by common interoperable tools and services, in order to leverage the power of such data for biomedical discovery and moving towards a learning health system. This paper aims at illustrating the major building blocks and concepts which MIRACUM will apply to achieve this goal. Governance and Policies: Besides establishing an efficient governance structure within the MIRACUM consortium (based on the steering board, a central administrative office, the general MIRACUM assembly, six working groups and the international scientific advisory board), defining DIC governance rules and data sharing policies, as well as establishing (at each MIRACUM DIC site, but also for MIRACUM in total) use and access committees are major building blocks for the success of such an endeavor. Architectural Framework and Methodology: The MIRACUM DIC architecture builds on a comprehensive ecosystem of reusable open source tools (MIRACOLIX), which are linkable and interoperable amongst each other, but also with the existing software environment of the MIRACUM hospitals. Efficient data protection measures, considering patient consent, data harmonization and a MIRACUM metadata repository as well as a common data model are major pillars of this framework. The methodological approach for shared data usage relies on a federated querying and analysis concept. Use Cases: MIRACUM aims at proving the value of their DIC with three use cases: IT support for patient recruitment into clinical trials, the development and routine care implementation of a clinico-molecular predictive knowledge tool, and molecular-guided therapy recommendations in molecular tumor boards. Results: Based on the MIRACUM DIC release in the nine months conceptual phase first large scale analysis for stroke and colorectal cancer cohorts have been pursued. Discussion: Beyond all technological challenges successfully applying the MIRACUM tools for the enrichment of our knowledge about diagnostic and therapeutic concepts, thus supporting the concept of a Learning Health System will be crucial for the acceptance and sustainability in the medical community and the MIRACUM university hospitals.

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Regional Differences in Thrombectomy Rates

Cited by 16 publications

References 23 publications

Reduced Rate of Inpatient Hospital Admissions in 18 German University Hospitals During the COVID-19 Lockdown

Reduced Rate of Inpatient Hospital Admissions in 18 German University Hospitals During the COVID-19 Lockdown

Stroke severity predicts transportation time and time until recanalization therapy in acute strokes

MIRACUM: Medical Informatics in Research and Care in University Medicine

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