Design, Rationale and Initial Findings From HERA-FIB on 10 222 Patients With Atrial Fibrillation Presenting to an Emergency Department Over An 11-Year Period.

BACKGROUND: For the majority of patients with atrial fibrillation (AF), disease management has improved in recent years. However, there are still populations underrepresented or excluded in current registries and randomized controlled trials. HERA-FIB (Heidelberg Registry of Atrial Fibrillation) was planned to assess real-world evidence for the prevalence, demographic characteristics and management of patients with the diagnosis of AF presenting consecutively to a chest pain unit. METHODS AND RESULTS: HERA-FIB is a retrospective, observational, single-center study on patients with a diagnosis of AF presenting to a chest pain unit from June 2009 until March 2020. This article describes the structure, governance, outcome assessment, quality and data collection processes of the registry. Additionally, characteristics of populations of special interest are described. The study consecutively enrolled 10 222 patients presenting with AF to the chest pain unit of the University Hospital of Heidelberg. Clinical parameters and patient characteristics were assessed retrospectively. Outcome parameters included rates for all-cause death, stroke, myocardial infarction and major bleedings. We were able to investigate patient cohorts of special interest such as advanced chronic kidney disease, octogenarians, and those with acute coronary syndrome who are often underrepresented in current studies and randomized controlled trials. CONCLUSIONS: HERA-FIB is one of the largest real-world single-center retrospective registries on patients with AF, which captures the era of transition from vitamin K antagonists to non-vitamin K oral anticoagulation regimens in clinical practice and offers the possibility to investigate patient populations usually underrepresented or excluded in current available randomized controlled trials and registries. REGISTRATION: URL: https://www.clinicaltrials.gov; unique identifier: NCT05995561.

Interoperability Is a Process - The Data Sharing Framework.

Common syntax and data semantics are core components of healthcare interoperability standards. However, interoperable data exchange processes are also needed to enable the integration of existing systems between organizations. While solutions for healthcare delivery processes are available and have been widely adopted, support for processes targeting bio-medical research is limited. Our Data Sharing Framework creates a platform to implement research processes like cohort size estimation, reviews and approvals of research proposals, consent checks, record linkage, pseudonymization and data sharing across organizations. The described framework implements a distributed business process engine for executing BPMN 2.0 processes with synchronization and data exchange using FHIR R4 resources. Our reference implementation has been rolled out to 38 organizations across three research consortia in Germany and is available as open source under the Apache 2.0 license.

Cardiological parameters predict mortality and cardiotoxicity in oncological patients.

AIMS: Oncological patients suspected at risk for cardiotoxicity are recommended to undergo intensified cardiological surveillance. We investigated the value of cardiac biomarkers and patient-related risk factors [age, cardiovascular risk factors (CVRFs), and cardiac function] for the prediction of all-cause mortality (ACM) and the development of cardiotoxicity. METHODS AND RESULTS: Between January 2016 and December 2020, patients with oncological diseases admitted to the Cardio-Oncology Unit at the Heidelberg University Hospital were included. They were evaluated by medical history, physical examination, 12-lead electrocardiogram, 2D echocardiography, and cardiac biomarkers [high-sensitivity cardiac troponin T (hs-cTnT) and N-terminal pro-brain natriuretic peptide (NT-proBNP)]. The primary endpoint was defined as ACM and the secondary endpoint was defined as cardiotoxicity, as defined by the European Society of Cardiology. Of the 1971 patients enrolled, the primary endpoint was reached by 490 patients (25.7%) with a median of 363.5 [interquartile range (IQR) 121.8, 522.5] days after presentation. Hs-cTnT of ≥ 7 ng/L [odds ratio (OR) 1.82, P < 0.001] and NT-proBNP (OR 1.98, P < 0.001) were independent predictors of ACM, while reduced left ventricular ejection fraction was not associated with increased ACM (P = 0.85). The secondary endpoint was reached by 182 patients (9.2%) with a median of 793.5 [IQR 411.2, 1165.0] days. Patients with multiple CVRFs (defined as high risk, n = 886) had an increased risk of cardiotoxicity (n = 100/886, 11.3%; hazard ratio 1.57, P = 0.004). They showed elevated baseline values of hs-cTnT (OR 1.60, P = 0.006) and NT-proBNP (OR 4.00, P < 0.001) and had an increased risk of ACM (OR 1.43, P = 0.031). CONCLUSIONS: In cancer patients, CVRF accumulation predicts cardiotoxicity whereas elevated hs-cTnT or NT-proBNP levels are associated with ACM. Accordingly, less intensive surveillance protocols may be warranted in patients with low cardiac biomarker levels and absence of CVRFs.

Prognostic value of negative stress cardiac magnetic resonance imaging in patients with moderate-severe coronary artery stenosis.

Objective: This study aims to evaluate the prognostic value of stress cardiac magnetic resonance (CMR) without inducible ischemia in a real-world cohort of patients with known severe coronary artery stenosis. Background: The prognosis of patients with severe coronary artery stenosis and without inducible ischemia using stress CMR remains uncertain, even though its identification of functionally significant coronary artery disease (CAD) is excellent. Materials and methods: Patients without inducible ischemia and known CAD who underwent stress CMR between February 2015 and December 2016 were included in this retrospective study. These patients were divided into two groups: group 1 with stenosis of 50%-75% and group 2 with stenosis of >75%. The primary endpoint was defined as the occurrence of a major adverse cardiovascular event (MACE) [cardiac death, non-fatal myocardial infarction (MI), percutaneous coronary intervention (PCI), or coronary artery bypass grafting (CABG)]. Results: Real-world data collected from 169 patients with a median age of 69 (60-75) years were included. The median follow-up was 5.5 (IQR 4.1-6.6) years. Events occurred after a mean time of 3.0 ± 2.2 years in group 1 and 3.7 ± 2.0 years in group 2 (p = 0.35). Sixteen (18.8%) patients in group 1 and 23 (27.4%) patients in group 2 suffered from MACE without a significant difference between the two groups (p = 0.33). In group 2, one cardiac death (1.2%), seven non-fatal MI (8.3%), 15 PCI (17.9%), and one CABG (1.2%) occurred. Conclusion: The findings of this pilot study suggest that long-term outcomes in a real-world patient cohort with known severe and moderate coronary artery stenosis but without inducible ischemia were similar. Stress CMR may provide valuable risk stratification in patients with angiographically significant but hemodynamically non-obstructive coronary lesions.

Real-World Evidence on Disparities on the Initiation of Ticagrelor Versus Prasugrel in Patients With Acute Coronary Syndrome.

Background Management of patients with non-ST-segment-elevation acute coronary syndrome (NSTE-ACS) is based on 2020 European Society of Cardiology guidelines, which recommend the preferential use of prasugrel over ticagrelor. Because the selection of the respective P2Y12 inhibitor has to consider label restrictions, we sought to evaluate the proportion of patients qualifying for either ticagrelor or prasugrel and reasons for noneligibility in an unselected cohort of patients with acute coronary syndrome. Methods and Results In this retrospective observational study, patients with ST-segment-elevation myocardial infarction (STEMI) or NSTE-ACS presenting consecutively during a 24-month period were enrolled. The eligibility of patients for a dual antiplatelet therapy option was assessed retrospectively. A total of 1502 patients had confirmed acute coronary syndrome (287 STEMI and 1215 NSTE-ACS). Eligibility for ticagrelor and full-dose prasugrel differed significantly for STEMI and NSTE-ACS (93% versus 51%, P<0.0001 versus 80% versus 31%, P<0.0001). Eligibility remained significantly lower (STEMI 78% versus NSTE-ACS 52%) if low-dose prasugrel was considered. Patients eligible for full-dose prasugrel had lower ischemic risk per GRACE (Global Registry of Acute Coronary Events) score (109 points [90-129 points] versus 121 points [98-146 points], P<0.0001) and lower bleeding risk (14 points [13-15 points] versus 20 points [12-29 points], P<0.0001) per PRECISE-DAPT (Predicting Bleeding Complications in Patients Undergoing Stent Implantation and Subsequent Dual Antiplatelet Therapy) score. Conclusions In real life, eligibility for prasugrel in patients requiring dual antiplatelet therapy is considerably lower than for ticagrelor, even in a cohort with high rates of coronary angiography and percutaneous coronary interventions. The recommended use of prasugrel over ticagrelor in current acute coronary syndrome guidelines contrasts with our observations of a substantial disparity on the eligibility. This important aspect has not received appropriate attention yet. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT05774431.

A network medicine approach to study comorbidities in heart failure with preserved ejection fraction.

BACKGROUND: Comorbidities are expected to impact the pathophysiology of heart failure (HF) with preserved ejection fraction (HFpEF). However, comorbidity profiles are usually reduced to a few comorbid disorders. Systems medicine approaches can model phenome-wide comorbidity profiles to improve our understanding of HFpEF and infer associated genetic profiles. METHODS: We retrospectively explored 569 comorbidities in 29,047 HF patients, including 8062 HFpEF and 6585 HF with reduced ejection fraction (HFrEF) patients from a German university hospital. We assessed differences in comorbidity profiles between HF subtypes via multiple correspondence analysis. Then, we used machine learning classifiers to identify distinctive comorbidity profiles of HFpEF and HFrEF patients. Moreover, we built a comorbidity network (HFnet) to identify the main disease clusters that summarized the phenome-wide comorbidity. Lastly, we predicted novel gene candidates for HFpEF by linking the HFnet to a multilayer gene network, integrating multiple databases. To corroborate HFpEF candidate genes, we collected transcriptomic data in a murine HFpEF model. We compared predicted genes with the murine disease signature as well as with the literature. RESULTS: We found a high degree of variance between the comorbidity profiles of HFpEF and HFrEF, while each was more similar to HFmrEF. The comorbidities present in HFpEF patients were more diverse than those in HFrEF and included neoplastic, osteologic and rheumatoid disorders. Disease communities in the HFnet captured important comorbidity concepts of HF patients which could be assigned to HF subtypes, age groups, and sex. Based on the HFpEF comorbidity profile, we predicted and recovered gene candidates, including genes involved in fibrosis (COL3A1, LOX, SMAD9, PTHL), hypertrophy (GATA5, MYH7), oxidative stress (NOS1, GSST1, XDH), and endoplasmic reticulum stress (ATF6). Finally, predicted genes were significantly overrepresented in the murine transcriptomic disease signature providing additional plausibility for their relevance. CONCLUSIONS: We applied systems medicine concepts to analyze comorbidity profiles in a HF patient cohort. We were able to identify disease clusters that helped to characterize HF patients. We derived a distinct comorbidity profile for HFpEF, which was leveraged to suggest novel candidate genes via network propagation. The identification of distinctive comorbidity profiles and candidate genes from routine clinical data provides insights that may be leveraged to improve diagnosis and identify treatment targets for HFpEF patients.

Software-Tool Support for Collaborative, Virtual, Multi-Site Molecular Tumor Boards.

The availability of high-throughput molecular diagnostics builds the foundation for Molecular Tumor Boards (MTBs). Although more fine-grained data is expected to support decision making of oncologists, assessment of data is complex and time-consuming slowing down the implementation of MTBs, e.g., due to retrieval of the latest medical publications, assessment of clinical evidence, or linkage to the latest clinical guidelines. We share our findings from analysis of existing tumor board processes and defininion of clinical processes for the adoption of MTBs. Building on our findings, we have developed a real-world software prototype together with oncologists and medical professionals, which supports the preparation and conduct of MTBs and enables collaboration between medical experts by sharing medical knowledge even across the hospital locations. We worked in interdisciplinary teams of clinicians, oncologists, medical experts, medical informaticians, and software engineers using design thinking methodology. With their input, we identified challenges and limitations of the current MTB approaches, derived clinical process models using Business Process and Modeling Notation (BMPN), and defined personas, functional and non-functional requirements for software tool support. Based on it, we developed software prototypes and evaluated them with clinical experts from major university hospitals across Germany. We extended the Kanban methodology enabling holistic tracking of patient cases from "backlog" to "follow-up" in our app. The feedback from interviewed medical professionals showed that our clinical process models and software prototype provide suitable process support for the preparation and conduction of molecular tumor boards. The combination of oncology knowledge across hospitals and the documentation of treatment decision can be used to form a unique medical knowledge base by oncologists for oncologists. Due to the high heterogeneity of tumor diseases and the spread of the latest medical knowledge, a cooperative decision-making process including insights from similar patient cases was considered as a very valuable feature. The ability to transform prepared case data into a screen presentation was recognized as an essential feature speeding up the preparation process. Oncologists require special software tool support to incorporate and assess molecular data for the decision-making process. In particular, the need for linkage to the latest medical knowledge, clinical evidence, and collaborative tools to discuss individual cases were named to be of importance. With the experiences from the COVID-19 pandemic, the acceptance of online tools and collaborative working is expected to grow. Our virtual multi-site approach proved to allow a collaborative decision-making process for the first time, which we consider to have a positive impact on the overall treatment quality.

No Transfer Without Validation: A Data Sharing Framework Use Case.

Availability and accessibility are important preconditions for using real-world patient data across organizations. To facilitate and enable the analysis of data collected at a large number of independent healthcare providers, syntactic- and semantic uniformity need to be achieved and verified. With this paper, we present a data transfer process implemented using the Data Sharing Framework to ensure only valid and pseudonymized data is transferred to a central research repository and feedback on success or failure is provided. Our implementation is used within the CODEX project of the German Network University Medicine to validate COVID-19 datasets at patient enrolling organizations and securely transfer them as FHIR resources to a central repository.

Monitoring Distributed Business Processes in Biomedical Research.

In biomedical research, business processes, such as data-sharing or feasibility queries, span across several healthcare organizations. Due to the growing number of data-sharing projects and connected organizations, the management of distributed processes gets more complex over time. This leads to an increased need for administrating, orchestrating, and monitoring all distributed processes of a single organization. A proof of concept for a decentralized and use case agnostic monitoring dashboard was developed for the Data Sharing Framework, which most German university hospitals have deployed. The implemented dashboard can handle current, changing, and upcoming processes using only information for cross-organizational communication. This differentiates our approach from other existing use case specific content visualizations. The presented dashboard is a promising solution to provide administrators with an overview of the status of their distributed process instances. Therefore, this concept will be further developed in upcoming releases.

Safety of Stress Cardiac Magnetic Resonance in Patients With Moderate to Severe Aortic Valve Stenosis.

BACKGROUND: Dobutamine and adenosine stress cardiac magnetic resonance (CMR) imaging is relatively contraindicated in patients with moderate to severe aortic valve stenosis (AS). We aimed to determine the safety of dobutamine and adenosine stress CMR in patients with moderate to severe AS. METHODS: In this retrospective study patients with AS who underwent either dobutamine or adenosine stress CMR for exclusion of obstructive coronary artery disease were enrolled. We recorded clinical data, CMR and echocardiography findings, and complications as well as minor symptoms. Patients with AS were compared to matched individuals without AS. RESULTS: A total of 187 patients with AS were identified and compared to age-, gender- and body mass index-matched 187 patients without AS. No severe complications were reported in the study nor the control group. The reported frequency of non-severe complications and minor symptoms were similar between the study and the control groups. Nineteen patients with AS experienced non-severe complications or minor symptoms during dobutamine stress CMR compared to eighteen patients without AS (p = 0.855). One patient with AS and two patients without AS undergoing adenosine stress CMR experienced minor symptoms (p = 0.562). Four examinations were aborted because of chest pain, paroxysmal atrial fibrillation and third-degree atrioventricular block. Inducible ischaemia, prior coronary artery bypass grafting, prior stroke and age were associated with a higher incidence of complications and minor symptoms. CONCLUSIONS: Moderate to severe AS was not associated with complications during CMR stress test. The incidence of non-severe complications and minor symptoms was greater with dobutamine.

Coronary artery disease, left ventricular function and cardiac biomarkers determine all-cause mortality in cancer patients-a large monocenter cohort study.

Cancer patients are at risk of suffering from cardiovascular diseases (CVD). Nevertheless, the impact of cardiovascular comorbidity on all-cause mortality (ACM) in large clinical cohorts is not well investigated. In this retrospective cohort study, we collected data from 40,329 patients who were subjected to cardiac catherization from 01/2006 to 12/2017 at University Hospital Heidelberg. The study population included 3666 patients with a diagnosis of cancer prior to catherization and 3666 propensity-score matched non-cancer patients according to age, gender, diabetes and hypertension. 5-year ACM in cancer patients was higher with a reduced left ventricular function (LVEF < 50%; 68.0% vs 50.9%) or cardiac biomarker elevation (high-sensitivity cardiac troponin T (hs-cTnT; 64.6% vs 44.6%) and N-terminal brain natriuretic peptide (NT-proBNP; 62.9% vs 41.4%) compared to cancer patients without cardiac risk. Compared to non-cancer patients, NT-proBNP was found to be significantly higher (median NT-proBNP cancer: 881 ng/L, IQR [254; 3983 ng/L] vs non-cancer: 668 ng/L, IQR [179; 2704 ng/L]; p < 0.001, Wilcoxon-rank sum test) and turned out to predict ACM more accurately than hs-cTnT (NT-proBNP: AUC: 0.74; hs-cTnT: AUC: 0.63; p < 0.001, DeLong's test) in cancer patients. Risk factors for atherosclerosis, such as diabetes and age (> 65 years) were significant predictors for increased ACM in cancer patients in a multivariate analysis (OR diabetes: 1.96 (1.39-2.75); p < 0.001; OR age > 65 years: 2.95 (1.68-5.4); p < 0.001, logistic regression). Our data support the notion, that overall outcome in cancer patients who underwent cardiac catherization depends on cardiovascular comorbidities. Therefore, particularly cancer patients may benefit from standardized cardiac care.

A FHIR has been lit on gICS: facilitating the standardised exchange of informed consent in a large network of university medicine.

BACKGROUND: The Federal Ministry of Education and Research of Germany (BMBF) funds a network of university medicines (NUM) to support COVID-19 and pandemic research at national level. The "COVID-19 Data Exchange Platform" (CODEX) as part of NUM establishes a harmonised infrastructure that supports research use of COVID-19 datasets. The broad consent (BC) of the Medical Informatics Initiative (MII) is agreed by all German federal states and forms the legal base for data processing. All 34 participating university hospitals (NUM sites) work upon a harmonised infrastructural as well as legal basis for their data protection-compliant collection and transfer of their research dataset to the central CODEX platform. Each NUM site ensures that the exchanged consent information conforms to the already-balloted HL7 FHIR consent profiles and the interoperability concept of the MII Task Force "Consent Implementation" (TFCI). The Independent Trusted Third-Party (TTP) of the University Medicine Greifswald supports data protection-compliant data processing and provides the consent management solutions gICS. METHODS: Based on a stakeholder dialogue a required set of FHIR-functionalities was identified and technically specified supported by official FHIR experts. Next, a "TTP-FHIR Gateway" for the HL7 FHIR-compliant exchange of consent information using gICS was implemented. A last step included external integration tests and the development of a pre-configured consent template for the BC for the NUM sites. RESULTS: A FHIR-compliant gICS-release and a corresponding consent template for the BC were provided to all NUM sites in June 2021. All FHIR functionalities comply with the already-balloted FHIR consent profiles of the HL7 Working Group Consent Management. The consent template simplifies the technical BC rollout and the corresponding implementation of the TFCI interoperability concept at the NUM sites. CONCLUSIONS: This article shows that a HL7 FHIR-compliant and interoperable nationwide exchange of consent information could be built using of the consent management software gICS and the provided TTP-FHIR Gateway. The initial functional scope of the solution covers the requirements identified in the NUM-CODEX setting. The semantic correctness of these functionalities was validated by project-partners from the Ludwig-Maximilian University in Munich. The production rollout of the solution package to all NUM sites has started successfully.

Secure Multi-Party Computation Based Distributed Feasibility Queries - A HiGHmed Use Case.

The integration of routine medical care data into research endeavors promises great value. However, access to this extra-domain data is constrained by numerous technical and legal requirements. The German Medical Informatics Initiative (MII) - initiated by the Federal Ministry of Research and Education (BMBF) - is making progress in setting up Medical Data Integration Centers to consolidate data stored in clinical primary information systems. Unfortunately, for many research questions cross-organizational data sources are required, as one organization's data is insufficient, especially in rare disease research. A first step, for research projects exploring possible multi-centric study designs, is to perform a feasibility query, i.e., a cohort size calculation transcending organizational boundaries. Existing solutions for this problem, like the previously introduced feasibility process for the MII's HiGHmed consortium, perform well for most use cases. However, there exist use cases where neither centralized data repositories, nor Trusted Third Parties are acceptable for data aggregation. Based on open standards, such as BPMN 2.0 and HL7 FHIR R4, as well as the cryptographic techniques of secure Multi-Party Computation, we introduce a fully automated, decentral feasibility query process without any central component or Trusted Third Party. The open source implementation of the proposed solution is intended as a plugin process to the HiGHmed Data Sharing Framework. The process's concept and underlying algorithms can also be used independently.

The COVID-19 Data Exchange Platform of the German University Medicine.

COVID-19 has challenged the healthcare systems worldwide. To quickly identify successful diagnostic and therapeutic approaches large data sharing approaches are inevitable. Though organizational clinical data are abundant, many of them are available only in isolated silos and largely inaccessible to external researchers. To overcome and tackle this challenge the university medicine network (comprising all 36 German university hospitals) has been founded in April 2020 to coordinate COVID-19 action plans, diagnostic and therapeutic strategies and collaborative research activities. 13 projects were initiated from which the CODEX project, aiming at the development of a Germany-wide Covid-19 Data Exchange Platform, is presented in this publication. We illustrate the conceptual design, the stepwise development and deployment, first results and the current status.

Data Sharing in Distributed Architectures - Concept and Implementation in HiGHmed.

Medical routine data has the potential to benefit research. However, transferring this data into a research context is difficult. For this reason Medical Data Integration Centers are being established in German university hospitals to consolidate data from primary information systems in a single location. But, small data-sets from one organization can be insufficient to answer a research question adequately. In order to obtain larger data-sets, attempts to merge and provide data-sets across institutional boundaries are made. Therefore, this paper proposes a possible process that can extract, merge, pseudonymize and provide distributed data-sets from several organizations conforming to privacy regulations. This process is executed according to the open standard BPMN 2.0, the underlying process data model is based on HL7 FHIR R4. The proposed solution is currently being deployed at eight university hospitals and one Trusted Third Party in the HiGHmed consortium.

High-sensitivity cardiac troponin T determines all-cause mortality in cancer patients: a single-centre cohort study.

AIMS: Cardio-oncology is a growing interdisciplinary field which aims to improve cardiological care for cancer patients in order to reduce morbidity and mortality. The impact of cardiac biomarkers, echocardiographic parameters, and cardiological assessment regarding risk stratification is still unclear. We aimed to identify potential parameters that allow an early risk stratification of cancer patients. METHODS AND RESULTS: In this cohort study, we evaluated 930 patients that were admitted to the cardio-oncology outpatient clinic of the University Hospital Heidelberg from January 2016 to January 2019. We performed echocardiography, including Global Longitudinal Strain (GLS) analysis and measured cardiac biomarkers including N-terminal pro brain-type natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin T levels (hs-cTnT). Most patients were suffering from breast cancer (n = 450, 48.4%), upper gastrointestinal carcinoma (n = 99, 10.6%) or multiple myeloma (n = 51, 5.5%). At the initial visit, we observed 86.7% of patients having a preserved left ventricular ejection fraction (LVEF >50%). At the second follow up, still 78.9% of patients showed a preserved LVEF. Echocardiographic parameters or elevation of NT-proBNP did not significantly correlate with all-cause mortality (ACM) (logistic regression LVEF <50%: P = 0.46, NT-proBNP: P = 0.16) and failed to identify high-risk patients. In contrast, hs-cTnT above the median (≥7 ng/L) was an independent marker to determine ACM (multivariant logistic regression, OR: 2.21, P = 0.0038) among all included patients. In particular, hs-cTnT levels before start of a chemotherapy were predictive for ACM. CONCLUSIONS: Based on our non-selected cohort of cardio-oncological patients, hs-cTnT was able to identify patients with high mortality by using a low cutoff of 7 ng/L. We conclude that measurement of hs-cTnT is an important tool to stratify the risk for mortality of cancer patients before starting chemotherapy.

Executing Distributed Healthcare and Research Processes - The HiGHmed Data Sharing Framework.

Several standards and frameworks have been described in existing literature and technical manuals that contribute to solving the interoperability problem. Their data models usually focus on clinical data and only support healthcare delivery processes. Research processes including cross organizational cohort size estimation, approvals and reviews of research proposals, consent checks, record linkage and pseudonymization need to be supported within the HiGHmed medical informatics consortium. The open source HiGHmed Data Sharing Framework implements a distributed business process engine for executing arbitrary biomedical research and healthcare processes modeled and executed using BPMN 2.0 while exchanging information using FHIR R4 resources. The proposed reference implementation is currently being rolled out to eight university hospitals in Germany as well as a trusted third party and available open source under the Apache 2.0 license.

Feasibility Queries in Distributed Architectures - Concept and Implementation in HiGHmed.

Medical routine data promises to add value for research. However, the transfer of this data into a research context is difficult. Therefore, Medical Data Integration Centers are being set up to merge data from primary information systems in a central repository. But, data from one organization is rarely sufficient to answer a research question. The data must be merged beyond institutional boundaries. In order to use this data in a specific research project, a researcher must have the possibility to query available cohort sizes across institutions. A possible solution for this requirement is presented in this paper, using a process for fully automated and distributed feasibility queries (i.e. cohort size estimations). This process is executed according to the open standard BPMN 2.0, the underlying process data model is based on HL7 FHIR R4 resources. The proposed solution is currently being deployed at eight university hospitals and one trusted third party across Germany.

A Federated Record Linkage Algorithm for Secure Medical Data Sharing.

The process of consolidating medical records from multiple institutions into one data set makes privacy-preserving record linkage (PPRL) a necessity. Most PPRL approaches, however, are only designed to link records from two institutions, and existing multi-party approaches tend to discard non-matching records, leading to incomplete result sets. In this paper, we propose a new algorithm for federated record linkage between multiple parties by a trusted third party using record-level bloom filters to preserve patient data privacy. We conduct a study to find optimal weights for linkage-relevant data fields and are able to achieve 99.5% linkage accuracy testing on the Febrl record linkage dataset. This approach is integrated into an end-to-end pseudonymization framework for medical data sharing.

Presence of contractile impairment appears crucial for structural remodeling in idiopathic left bundle-branch block.

BACKGROUND: To differentiate effects of ventricular asynchrony from an underlying hypocontractile cardiomyopathy this study aimed to enhance the understanding of functional impairment and structural remodeling in idiopathic left bundle-branch block (LBBB). We hypothesize, that functional asynchrony with septal flash volume effects alone might not entirely explain the degree of functional impairment. Hence, we suggest the presence of a superimposed contractile cardiomyopathy. METHODS: In this retrospective study, 53 patients with idiopathic LBBB were identified and matched to controls with and without cardiovascular risk factors. Cardiovascular magnetic resonance (CMR) was used to evaluate cardiac function, volumes and myocardial fibrosis using native T1 mapping and late gadolinium enhancement (LGE). Septal flash volume was assessed by CMR volumetric measurements and allowed to stratify patients with systolic dysfunction solely due to isolated ventricular asynchrony or superimposed contractile impairment. RESULTS: Reduced systolic LV-function, increased LV-volumes and septal myocardial fibrosis were found in patients with idiopathic LBBB compared to healthy controls. LV-volumes increased and systolic LV-function declined with prolonged QRS duration. Fibrosis was typically located at the right ventricular insertion points. Subgroups with superimposed contractile impairment appeared with pronounced LV dilation and increased fibrotic remodeling compared to individuals with isolated ventricular asynchrony. CONCLUSIONS: The presence of superimposed contractile impairment in idiopathic LBBB is crucial to identify patients with enhanced structural remodeling. This finding suggests an underlying cardiomyopathy. Future studies are needed to assess a possible prognostic impact of this entity and the development of heart failure. TRIAL REGISTRATION: This study was retrospectively registered.