Anti-Spike IgG antibodies as correlates of protection against SARS-CoV-2 infection in the pre-Omicron and Omicron era.

Anti-Spike IgG antibodies against SARS-CoV-2, which are elicited by vaccination and infection, are correlates of protection against infection with pre-Omicron variants. Whether this association can be generalized to infections with Omicron variants is unclear. We conducted a retrospective cohort study with 8457 blood donors in Tyrol, Austria, analyzing 15,340 anti-Spike IgG antibody measurements from March 2021 to December 2022 assessed by Abbott SARS-CoV-2 IgG II chemiluminescent microparticle immunoassay. Using a Bayesian joint model, we estimated antibody trajectories and adjusted hazard ratios for incident SARS-CoV-2 infection ascertained by self-report or seroconversion of anti-Nucleocapsid antibodies. At the time of their earliest available anti-Spike IgG antibody measurement (median November 23, 2021), participants had a median age of 46.0 years (IQR 32.8-55.2), with 45.3% being female, 41.3% having a prior SARS-CoV-2 infection, and 75.5% having received at least one dose of a COVID-19 vaccine. Among 6159 participants with endpoint data, 3700 incident SARS-CoV-2 infections with predominantly Omicron sublineages were recorded over a median of 8.8 months (IQR 5.7-12.4). The age- and sex-adjusted hazard ratio for SARS-CoV-2 associated with having twice the anti-Spike IgG antibody titer was 0.875 (95% credible interval 0.868-0.881) overall, 0.842 (0.827-0.856) during 2021, and 0.884 (0.877-0.891) during 2022 (all p < 0.001). The associations were similar in females and males (Pinteraction = 0.673) and across age (Pinteraction = 0.590). Higher anti-Spike IgG antibody titers were associated with reduced risk of incident SARS-CoV-2 infection across the entire observation period. While the magnitude of association was slightly weakened in the Omicron era, anti-Spike IgG antibody continues to be a suitable correlate of protection against newer SARS-CoV-2 variants.

Penetrance, cancer incidence and survival in HFE haemochromatosis-A population-based cohort study.

BACKGROUND AND AIMS: Haemochromatosis is characterized by progressive iron overload affecting the liver and can cause cirrhosis and hepatocellular carcinoma. Most haemochromatosis patients are homozygous for p.C282Y in HFE, but only a minority of individuals with this genotype will develop the disease. The aim was to assess the penetrance of iron overload, fibrosis, hepatocellular carcinoma and life expectancy. METHODS: A total of 8839 individuals from the Austrian region of Tyrol were genotyped for the p.C282Y variant between 1997 and 2021. Demographic, laboratory parameters and causes of death were assessed from health records. Penetrance, survival, and cancer incidence were ascertained from diagnosed cases, insurance- and cancer registry data. Outcomes were compared with a propensity score-matched control population. RESULTS: Median age at diagnosis in 542 p.C282Y homozygous individuals was 47.8 years (64% male). At genotyping, the prevalence of iron overload was 55%. The cumulative penetrance of haemochromatosis defined as the presence of provisional iron overload was 24.2% in males and 10.5% in females aged 60 years or younger. Among p.C282Y homozygotes of the same ages, the cumulative proportion of individuals without fibrosis (FIB-4 score < 1.3) was 92.8% in males and 96.7% in females. Median life expectancy was reduced by 6.8 years in individuals homozygous for p.C282Y when compared with population-matched controls (p = .001). Hepatocellular carcinoma incidence was not significantly higher in p.C282Y homozygotes than in controls matched for age and sex. CONCLUSION: Reduced survival and the observed age-dependent increase in penetrance among p.C282Y homozygotes call for earlier diagnosis of haemochromatosis to prevent complications.

Can virtual care reduce treatment burden in pediatric leukemia? A retrospective cost analysis.

We conducted a retrospective analysis to determine the potential reduction in treatment burden through the expansion of virtual care among children with leukemia (n = 152). Patients living in urban areas traveled median distances of 1555 km compared with 7536 km for patients living in rural areas (p < .05). For the latter group, a median reduction in travel distance of 3560 km (interquartile range [IQR], 2136-5787 km), travel time of 51 h (IQR, 26-78 h), and CO2 emissions of 623 kg (IQR, 374-1013 kg) was estimated, if every second visit was replaced by video consultations.

Distinct smell and taste disorder phenotype of post-acute COVID-19 sequelae.

PURPOSE: Olfactory dysfunction (OD) commonly accompanies coronavirus disease 2019 (COVID-19). We investigated the kinetics of OD resolution following SARS-CoV-2 infection (wild-type and alpha variant) and its impact on quality of life, physical and mental health. METHODS: OD prevalence was assessed in an ambulatory COVID-19 survey (n = 906, ≥ 90 days follow-up) and an observational cohort of ambulatory and hospitalized individuals (n = 108, 360 days follow-up). Co-occurrence of OD with other symptoms and effects on quality of life, physical and mental health were analyzed by multi-dimensional scaling, association rule mining and semi-supervised clustering. RESULTS: Both in the ambulatory COVID-19 survey study (72%) and the observational ambulatory and hospitalized cohort (41%) self-reported OD was frequent during acute COVID-19. Recovery from self-reported OD was slow (survey: median 28 days, observational cohort: 90 days). By clustering of the survey data, we identified a predominantly young, female, comorbidity-free group of convalescents with persistent OD and taste disorders (median recovery: 90 days) but low frequency of post-acute fatigue, respiratory or neurocognitive symptoms. This smell and taste disorder cluster was characterized by a high rating of physical performance, mental health, and quality of life as compared with convalescents affected by prolonged fatigue or neurocognitive complaints. CONCLUSION: Our results underline the heterogeneity of post-acute COVID-19 sequelae calling for tailored management strategies. The persistent smell and taste disorder phenotype is characterized by good clinical, physical, and mental recovery and may pose a minor challenge for public health. STUDY REGISTRATION: ClinicalTrials.gov: NCT04661462 (survey study), NCT04416100 (observational cohort).

Universal gestational diabetes screening and antepartum stillbirth rates in Austria-A population-based study.

INTRODUCTION: Occult or untreated gestational diabetes (GDM) is a well-known risk factor for adverse perinatal outcomes and may contribute to antepartum stillbirth. We assessed the impact of screening for GDM on the rate of antepartum stillbirths in non-anomalous pregnancies by conducting a population-based study in 974 889 women in Austria. MATERIAL AND METHODS: Our database was derived from the Austrian Birth Registry. Inclusion criteria were singleton live births and antepartum stillbirths ≥24+0 gestational weeks, excluding fetal congenital malformations, terminations of pregnancy and women with pre-existing type 1 or 2 diabetes. Main outcome measures were (a) overall stillbirth rates and (b) stillbirth rates in women at high risk of GDM (i.e., women with a body mass index ≥30 kg/m2 , history of previous intrauterine fetal death, GDM, previous macrosomic offspring) before (2008-2010, "phase I") and after (2011-2019, "phase II") the national implementation of universal GDM screening with a 75 g oral glucose tolerance test in Austrian pregnant women by 2011. RESULTS: In total, 940 373 pregnancies were included between 2008 and 2019, of which 2579 resulted in intrauterine fetal deaths at 33.51 ± 5.10 gestational weeks. After implementation of the GDM screening, a statistically significant reduction in antepartum stillbirth rates among non-anomalous singletons was observed only in women at high risk for GDM (4.10‰ [95% confidence interval (CI) 3.09-5.43] in phase I vs. 2.96‰ [95% CI 2.57-3.41] in phase II; p = 0.043) but not in the general population (2.76‰ [95% CI 2.55-2.99] in phase I vs. 2.74‰ [95% CI 2.62-2.86] in phase II; p = 0.845). The number needed to screen with the oral glucose tolerance test to subsequently prevent one case of (non-anomalous) intrauterine fetal death was 880 in the high-risk and 40 000 in the general population. CONCLUSIONS: The implementation of a universal GDM screening program in Austria in 2011 has not led to any significant reduction in antenatal stillbirths among non-anomalous singletons in the general population. More international data are needed to strengthen our findings.

Wastewater surveillance of SARS-CoV-2 in Austria: development, implementation, and operation of the Tyrolean wastewater monitoring program.

Wastewater-based epidemiology (WBE) is an effective approach for tracking information on spatial distribution and temporal trends of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at the community level. Herein, the development, implementation, and operation of the wastewater monitoring program serving Tyrol - a federal province of Austria - are described. The development of this program was initiated by Tyrolean health authorities at the end of the first phase of the Coronavirus disease 2019 (COVID-19) pandemic (May 2020). In close co-operation with the water sector and academic institutions, efficient and effective workflows and processes for wastewater surveillance were established. The monitoring program went into operation in November 2020. By the end of July 2021, a total of 5,270 wastewater influent samples collected at 43 sites were analyzed. The monitoring program provided valuable insights into the development of the pandemic situation in Tyrol and fulfilled several tasks that are of importance in different phases of the pandemic. It represented an early-warning system, provided independent confirmation of temporal trends in COVID-19 prevalence, enabled the assessment of the effectiveness of measures, alerted about bursts of disease activity, and provided evidence for the absence of COVID-19. These findings underline the importance of establishing national wastewater monitoring programs as a complementary source of information for efficient and effective pandemic management.

Medial unicondylar knee arthroplasty should be reserved for patients with complete joint space collapse.

PURPOSE: To determine whether preoperative radiologic joint space width (JSW) is related to the outcome of medial unicondylar knee arthroplasty (UKA) (primary hypothesis). METHODS: A retrospective comparative analysis was performed. One group was comprised of UKA patients with preoperative JSW 0-1 mm. Another group was made up of patients with preoperative JSW ≥ 2 mm (range 0-4 mm). The JSW was measured from preoperative weight-bearing Schuss-view radiographs. The clinical outcome was determined with the Western Ontario and MacMaster Universities (WOMAC) Osteoarthritis Index score preoperatively and 1 year after medial UKA. Implant survival data were obtained from the arthroplasty register of Tyrol. RESULTS: There were 80 patients with a preoperative JSW 0-1 mm (age 66, BMI 27.8) and 70 patients with a preoperative JSW ≥ 2 mm (age 64, IQR 15, BMI 28.1). WOMAC total was 10 ± 10 in patients with 0-1 mm JSW and 25 ± 47 in patients with ≥ 2 mm JSW at 1 year postoperative (p = 0.052). WOMAC pain at 1 year postoperative was 7 ± 16 in patients with 0-1 mm JSW and 18 ± 46 in patients with ≥ 2 mm JSW (p = 0.047). WOMAC function at 1 year postoperative was 10 ± 9 in patients with 0-1 mm JSW and 17 ± 51 in patients with ≥ 2 mm JSW (p = 0.048). In patients with 0-1 mm JSW 5 year prosthesis survival was 92.3% and in patients with ≥ 2 mm JSW, it was 81.1% (p = 0.016). CONCLUSIONS: In patients with preoperative complete joint space collapse (0-1 mm JSW), clinical outcome was superior to that of patients with incomplete joint space collapse. This was true for both 1 year postoperative WOMAC pain and WOMAC function and for 5 year implant survival rates. On the basis of our findings, it is recommended that 'complete joint space collapse' especially be used to achieve best clinical outcome in medial UKA surgery. LEVEL OF EVIDENCE: IV.

Cesarean delivery after non-medically indicated induction of labor: A population-based study using different definitions of expectant management.

INTRODUCTION: Most observational studies found that non-medically indicated induction of labor (IOL) is not associated with an increased risk of cesarean delivery compared with expectant management, defined as all births at a later gestation. However, given the higher rate of cesarean delivery at late term, this definition of the expectant management group might bias the results of observational studies in favor of IOL at early or full term when estimating the risk of short-term (eg up to 1 week) expectant management. MATERIAL AND METHODS: We conducted a retrospective cohort study including 447 066 singleton term and post-term hospital births that occurred in Austria between 2008 and 2016. Multivariate logistic regression was used to test the association of IOL and cesarean delivery at each week of gestation from 37-41. Expectant management was either defined as all births at "next week or beyond" or "at next week". RESULTS: Non-medically indicated IOL was associated with increased odds for cesarean delivery at 37 and 38 weeks, and reduced odds at 40 and 41 weeks. At 39 weeks, IOL resulted in comparable cesarean rates compared with expectant management defined as "next week or beyond" (17.2% vs 16.2%; adjusted odds ratio [OR] 0.93; 95% confidence interval [CI] 0.86-1.00; P = .059). However, when defined as births "at the next week", expectant management was associated with significantly reduced odds for cesarean delivery (13.6%; adjusted OR 0.76; 95% CI 0.70-0.82; P < .001). Comparison of the cesarean delivery rates for the two definitions of expectant management showed that the "next week and beyond" model underestimates the benefit of short-term expectant management by up to 1 week, particularly for IOL at weeks 38 and 39. CONCLUSIONS: Our findings demonstrate that the definition of the expectant management group has a significant impact when analyzing the outcome of IOL in retrospective cohort studies. Non-medically indicated IOL is not an all-or-none choice between "elective" induction and indefinite expectant management. Thus, to define the control group as all births at the next week could be useful for clinical decision-making, as it allows to estimate the risks of expectant management until the next appointment compared with immediate IOL.

Non-invasive imaging of cardiac electrophysiology in a cardiac resynchronization therapy defibrillator patient with a quadripolar left ventricular lead.

AIMS: The present study was aimed to assess epi- and endocardial ventricular electroanatomical activation during cardiac resynchronization therapy (CRT) by means of non-invasive imaging of cardiac electrophysiology (NICE) in a patient with a novel quadripolar LV lead. METHODS AND RESULTS: Non-invasive imaging of cardiac electrophysiology is a novel imaging tool which works by fusing data from high-resolution electrocardiogram (ECG) mapping with a model of the patient's individual cardiothoracic anatomy created from magnetic resonance imaging. This was performed in a cardiac resynchronization therapy defribrillator (CRT-D) patient with a quadripolar left ventricular (LV) lead. Beat-to-beat endocardial and epicardial ventricular activation sequences were computed using NICE during intrinsic conduction as well as during different pacing modes with different LV and biventricular (biV) pacing vectors. The spatial resolution of NICE enabled discrimination of the different pacing vectors during LV and biV pacing. Biventricular pacing resulted in a marked shortening of the total activation duration (TAD) of both ventricles when compared with intrinsic conduction and RV and LV pacing. CONCLUSION: Non-invasive imaging of cardiac electrophysiology facilitates non-invasive imaging of ventricular activation, which may be useful in CRT patients to locate the area of latest ventricular activation as the target area for LV lead placement. Moreover, especially in non-responders to CRT NICE may be further useful to determine the best electrical repositioning option.

Exploring Opportunities for Clinical Data Warehouse Enhancement Through Data Catalog Integration.

Secondary use of clinical health data implies a prior integration of mostly heterogenous and multidimensional data sets. A clinical data warehouse addresses the technological and organizational framework conditions required for this, by making any data available for analysis. However, users of a data warehouse often do not have a comprehensive overview of all available data and only know about their own data in their own systems - a situation which is also referred to as 'data siloed state'. This problem can be addressed and ultimately solved by implementation of a data catalog. Its core function is a search engine, which allows for searching the metadata collected from different data sources and thereby accessing all data there is. With this in mind, we conducted an explorative online market survey followed by vendor comparison as a pre-requisite for system selection of a data catalog. Assessment of vendor performance was based on seven predetermined and weighted selection criteria. Although three vendors achieved the highest score, results were lying closely together. Detailed investigations and test installations are needed for further narrowing down the selection process.

Unveiling the Surge: A Comprehensive Analysis of the Stimulating Impact of the Covid-19 Pandemic on Telemedicine and Its Academic Landscape.

The Covid-19 pandemic spurred an unprecedented shift towards digitalization, prompting a surge in telehealth practices. This paper explores the impact of the pandemic on telemedicine through a comprehensive analysis of scientific publications. Utilizing a bibliometric approach, the study examines trends in telemedicine research before and after the onset of Covid-19. The systematic search in PubMed yielded 8,454 pre-Covid-19 publications (2016-2019) and 16,633 post-Covid-19 publications (2020-2023). A total of 21,989 distinct keywords were extracted. Co-occurrence maps reveal evolving thematic clusters, with "mhealth" and "ehealth" dominating pre-Covid-19, while "Covid-19" emerges as a top keyword post-pandemic. The Top-10 keywords shift post-Covid-19, reflecting dynamic research priorities. The bibliometric approach illuminates a heightened exploration of telehealth solutions post-pandemic, emphasizing the enduring impact of the crisis on academic discourse. Changes in key terms and shifts in key term ranking indicate dynamic research priorities and a broader consideration of multidimensional healthcare challenges. Acknowledging study limitations, the analysis offers a high-level perspective, focusing on authors' keywords. Despite challenges, the study provides a systematic overview, revealing the emergence of new telemedicine application domains and the need for further in-depth analyses. Future research directions may explore the ecological impact of telemedicine applications and other intriguing aspects, contributing to a comprehensive understanding of telemedicine's scholarly trajectory.

Visualizing Nursing Narratives: An Evaluation of Latent Dirichlet Allocation Topic Modeling for Care Reports.

The increasing volume of unstructured textual data in healthcare, particularly in nursing care reports, presents both challenges and opportunities for enhancing patient care and operational efficiency. This study explores the application of Latent Dirichlet Allocation (LDA) topic modeling to analyze free-text nursing narratives from inpatient stays in three different clinics, aiming to uncover the latent thematic structures within. Utilizing the R programming environment and the visualization tool LDAvis, we identified three main themes: "Patient Well-being," "Patient Mobility and Care Activities," and "Treatment and Pain Management," the latter combining two closely related but initially distinct topics due to their overlapping content. Our findings demonstrate the potential of LDA topic modeling in extracting meaningful insights from nursing narratives, which could inform patient care strategies and healthcare practices. However, the study also highlights significant challenges associated with the method, including the sensitivity to parameter settings, the lack of updates for key software packages, and concerns about reproducibility. These issues highlight the need for meticulous parameter validation and the exploration of alternative text analysis methodologies for future research. By addressing these methodological challenges and emphasizing the importance of comparative method analysis, this study contributes to the advancement of text analytics in healthcare. It opens avenues for further research aimed at developing more robust, efficient, and accessible tools for analyzing free-text data, thereby enhancing the ability of healthcare professionals to use unstructured data to improve decision making and patient outcomes.

Understanding IT in Healthcare: Relevance and Training Needs of IT in Private Medical Practice.

BACKGROUND: The integration of Information Technology (IT) into private medical practice is crucial in modern healthcare. Physicians managing office-related IT without proper knowledge risk operational inefficiencies and security. OBJECTIVES: This study determines the relevance of specific IT topics in medical practice and identifies the training needs of physicians for enhancing IT competencies in healthcare. METHODS: In March 2023 a cross-sectional online survey was conducted with physicians comprising nine IT-related topics in Tyrol, Austria. RESULTS: The survey results highlighted a strong perceived relevance and high demand for IT education among physicians working in their medical practice, especially in areas of core medical IT and security. The majority of responses indicated high relevance (76.7%) and high demand (69.7%) for IT topics in medical practice. CONCLUSION: The findings underscore a significant need for targeted IT training and support in medical practices, particularly in areas related to the medical practice and security. Addressing these needs could lead to improved healthcare delivery and better management of technological resources in the healthcare sector.

Quality and Effectiveness of AI Tools for Students and Researchers for Scientific Literature Review and Analysis.

This study scrutinizes free AI tools tailored for supporting literature review and analysis in academic research, emphasizing their response to direct inquiries. Through a targeted keyword search, we cataloged relevant AI tools and evaluated their output variation and source validity. Our results reveal a spectrum of response qualities, with some tools integrating non-academic sources and others depending on outdated information. Notably, most tools showed a lack of transparency in source selection. Our study highlights two key limitations: the exclusion of commercial AI tools and the focus solely on tools that accept direct research queries. This raises questions about the potential capabilities of paid tools and the efficacy of combining various AI tools for enhanced research outcomes. Future research should explore the integration of diverse AI tools, assess the impact of commercial tools, and investigate the algorithms behind response variability. This study contributes to a better understanding of AI's role in academic research, emphasizing the importance of careful selection and critical evaluation of these tools in academic endeavors.

Anti-SARS-CoV-2 IgG Seroprevalence in Tyrol, Austria, among 28,768 Blood Donors between May 2022 and March 2023.

BACKGROUND: To provide updated estimates on SARS-CoV-2 antibody seroprevalence and average antibody titres for Central Europe. METHODS: In repeat cross-sectional investigations (1 May 2022 to 9 March 2023) involving 28,768 blood donors in the Federal State of Tyrol, Austria (participation rate: 87.0%), we measured Spike receptor-binding domain (RBD) and Nucleocapsid IgG antibodies (37,065 and 12,645 samples), and estimated monthly seroprevalences and geometric mean titres. RESULTS: Median age of participants was 45.4 years (range 18-70); 43.2% were female. Spike RBD IgG antibody seroprevalence was 96.3% (95% CI: 95.6-96.9%) in May 2022, 97.4% (96.7-98.0%) in December 2022, and 97.9% (96.4-98.8%) in March 2023. Among seropositive participants, geometric mean titres increased from 1400 BAU/mL (95% CI: 1333-1471) in May 2022 to 1821 BAU/mL (1717-1932) in December 2022, and dropped to 1559 BAU/mL (1405-1729) by March 2023. Furthermore, titres differed markedly by vaccination status and history of infection, with being the highest in participants with booster vaccination and prior infection. In autumn 2022, Nucleocapsid IgG antibody seroprevalence ranged from 36.5% (35.0-38.1) in September to 39.2% (37.2-41.2) in December 2022. CONCLUSION: Seroprevalence of SARS-CoV-2 antibodies in blood donors from Tyrol, Austria, was remarkably stable from May 2022 to March 2023. In contrast, average Spike RBD IgG antibody titres peaked in December 2022.

CareNet Tyrol - Information System Success Assessment for Case & Care Management Service.

BACKGROUND: CareNet is the IT-based tool for Case and Care Management (CCM) in Tyrol, which facilitates standardised documentation of CCM activities. OBJECTIVES: Analysing the pilot usage of CareNet Tyrol. METHODS: Evaluation of the success and user experience of CareNet, expert interviews and a questionnaire-based assessment. RESULTS: Feedback from users in both phases indicated that the CareNet platform provides general benefits, but falls short of fully supporting the daily work of CCM experts and avoiding the need for parallel use of different documentation tools. CONCLUSION: This paper provides an insight into the ongoing transition to digital documentation for CCM at LIV Tyrol. While user feedback highlights areas for improvement, digital documentation is proved to be beneficial for the CCM team.

HerzMobil Tirol PreOp - A Multidisciplinary Telemonitoring Project for Heart Failure Patients Prior to Cardiac Surgery.

BACKGROUND: Patients with heart failure are at risk of perioperative complications with elective cardiac surgery. OBJECTIVES: Conception of a multidisciplinary telemedicine-assisted optimisation project for high-risk patients prior to elective cardiac surgery. METHODS: Multidisciplinary concept design. RESULTS: A pilot-project for 30 patients was developed. CONCLUSION: Design of the first preoperative telemonitoring-assisted optimisation project for high-risk patients undergoing cardiac surgery.

Telemedicine for Ketogenic Dietary Treatment in Refractory Epilepsy and Inherited Metabolic Disease: State of Play and Future Perspectives.

Ketogenic dietary therapies (KDT) are diets that induce a metabolic condition comparable to fasting. All types of KDT comprise a reduction in carbohydrates whilst dietary fat is increased up to 90% of daily energy expenditure. The amount of protein is normal or slightly increased. KDT are effective, well studied and established as non-pharmacological treatments for pediatric patients with refractory epilepsy and specific inherited metabolic diseases such as Glucose Transporter Type 1 Deficiency Syndrome. Patients and caregivers have to contribute actively to their day-to-day care especially in terms of (self-) calculation and (self-) provision of dietary treatment as well as (self-) measurement of blood glucose and ketones for therapy monitoring. In addition, patients often have to deal with ever-changing drug treatment plans and need to document occurring seizures on a regular basis. With this review, we aim to identify existing tools and features of telemedicine used in the KDT context and further aim to derive implications for further research and development.

Smart FOX - Enabling Citizen-Based Donation of EHR-Standardised Data for Clinical Research in Austria.

Access to healthcare data for secondary use in clinical research is often restricted due to privacy concerns or business interests, hindering comprehensive analysis across patient pathways. The Smart FOX project seeks to address this challenge by developing concepts, methods, and tools to facilitate citizen/patient-driven donations of health data for clinical research. Leveraging the groundwork, laid by the national Electronic Health Record implementation in Austria (called ELGA), Smart FOX aims to harness structured datasets from ELGA for research purposes through an opt-in approach. With funding secured from the Austrian Research Promotion Agency, the project embarks on innovative solutions encompassing governance frameworks, community engagement, and technical infrastructure. The Smart FOX consortium, comprising key stakeholders across various healthcare-associated domains, will evaluate these efforts through demonstrators focusing on clinical registries, patient-generated data, and recruitment services. The project targets to accompany the development of future data donation infrastructure while ultimately advancing clinical research efficiency and bolstering Austria's preparedness for the European Health Data Space. This paper presents the first systematic evaluation of the technical concept and proposal for the federated system architecture of the Austrian Health Data Donation Space, which is the socio-technical goal of Smart FOX.

Health data space nodes for privacy-preserving linkage of medical data to support collaborative secondary analyses.

Introduction: The potential for secondary use of health data to improve healthcare is currently not fully exploited. Health data is largely kept in isolated data silos and key infrastructure to aggregate these silos into standardized bodies of knowledge is underdeveloped. We describe the development, implementation, and evaluation of a federated infrastructure to facilitate versatile secondary use of health data based on Health Data Space nodes. Materials and methods: Our proposed nodes are self-contained units that digest data through an extract-transform-load framework that pseudonymizes and links data with privacy-preserving record linkage and harmonizes into a common data model (OMOP CDM). To support collaborative analyses a multi-level feature store is also implemented. A feasibility experiment was conducted to test the infrastructures potential for machine learning operations and deployment of other apps (e.g., visualization). Nodes can be operated in a network at different levels of sharing according to the level of trust within the network. Results: In a proof-of-concept study, a privacy-preserving registry for heart failure patients has been implemented as a real-world showcase for Health Data Space nodes at the highest trust level, linking multiple data sources including (a) electronical medical records from hospitals, (b) patient data from a telemonitoring system, and (c) data from Austria's national register of deaths. The registry is deployed at the tirol kliniken, a hospital carrier in the Austrian state of Tyrol, and currently includes 5,004 patients, with over 2.9 million measurements, over 574,000 observations, more than 63,000 clinical free text notes, and in total over 5.2 million data points. Data curation and harmonization processes are executed semi-automatically at each individual node according to data sharing policies to ensure data sovereignty, scalability, and privacy. As a feasibility test, a natural language processing model for classification of clinical notes was deployed and tested. Discussion: The presented Health Data Space node infrastructure has proven to be practicable in a real-world implementation in a live and productive registry for heart failure. The present work was inspired by the European Health Data Space initiative and its spirit to interconnect health data silos for versatile secondary use of health data.