Has the COVID-19 pandemic changed existing patterns of non-COVID-19 health care utilization? A retrospective analysis of six regions in Europe.

BACKGROUND: Resilience of national health systems in Europe remains a major concern in times of multiple crises and as more evidence is emerging relating to the indirect effects of the COVID-19 pandemic on health care utilization (HCU), resulting from de-prioritization of regular, non-pandemic healthcare services. Most extant studies focus on regional, disease specific or early pandemic HCU creating difficulties in comparing across multiple countries. We provide a comparatively broad definition of HCU across multiple countries, with potential to expand across regions and timeframes. METHODS: Using a cross-country federated research infrastructure (FRI), we examined HCU for acute cardiovascular events, elective surgeries and serious trauma. Aggregated data were used in forecast modelling to identify changes from predicted European age-standardized counts via fitted regressions (2017-19), compared against post-pandemic data. RESULTS: We found that elective surgeries were most affected, universally falling below predicted levels in 2020. For cardiovascular HCU, we found lower-than-expected cases in every region for heart attacks and displayed large sex differences. Serious trauma was the least impacted by the COVID-19 pandemic. CONCLUSION: The strength of this study comes from the use of the European Population Health Information Research Infrastructure's (PHIRI) FRI, allowing for rapid analysis of regional differences to assess indirect impacts of events such as pandemics. There are marked differences in the capacity of services to return to normal in terms of elective surgery; additionally, we found considerable differences between men and women which requires further research on potential sex or gender patterns of HCU during crises.

Federated causal inference based on real-world observational data sources: application to a SARS-CoV-2 vaccine effectiveness assessment.

INTRODUCTION: Causal inference helps researchers and policy-makers to evaluate public health interventions. When comparing interventions or public health programs by leveraging observational sensitive individual-level data from populations crossing jurisdictional borders, a federated approach (as opposed to a pooling data approach) can be used. Approaching causal inference by re-using routinely collected observational data across different regions in a federated manner, is challenging and guidance is currently lacking. With the aim of filling this gap and allowing a rapid response in the case of a next pandemic, a methodological framework to develop studies attempting causal inference using federated cross-national sensitive observational data, is described and showcased within the European BeYond-COVID project. METHODS: A framework for approaching federated causal inference by re-using routinely collected observational data across different regions, based on principles of legal, organizational, semantic and technical interoperability, is proposed. The framework includes step-by-step guidance, from defining a research question, to establishing a causal model, identifying and specifying data requirements in a common data model, generating synthetic data, and developing an interoperable and reproducible analytical pipeline for distributed deployment. The conceptual and instrumental phase of the framework was demonstrated and an analytical pipeline implementing federated causal inference was prototyped using open-source software in preparation for the assessment of real-world effectiveness of SARS-CoV-2 primary vaccination in preventing infection in populations spanning different countries, integrating a data quality assessment, imputation of missing values, matching of exposed to unexposed individuals based on confounders identified in the causal model and a survival analysis within the matched population. RESULTS: The conceptual and instrumental phase of the proposed methodological framework was successfully demonstrated within the BY-COVID project. Different Findable, Accessible, Interoperable and Reusable (FAIR) research objects were produced, such as a study protocol, a data management plan, a common data model, a synthetic dataset and an interoperable analytical pipeline. CONCLUSIONS: The framework provides a systematic approach to address federated cross-national policy-relevant causal research questions based on sensitive population, health and care data in a privacy-preserving and interoperable way. The methodology and derived research objects can be re-used and contribute to pandemic preparedness.

Monitoring of intracranial pressure in patients with severe traumatic brain injury: an Austrian prospective multicenter study.

OBJECTIVE: The goals of this study were to elucidate reasons why patients did or did not receive intracranial pressure (ICP) monitoring and to describe factors influencing hospital mortality after severe traumatic brain injury (TBI). DESIGN: Prospective multicenter cohort study. PATIENTS AND PARTICIPANTS: 88,274 patients consecutively admitted to 32 medical, surgical and mixed Austrian ICUs between 1998 and 2004. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: 1,856 patients (2.1% of all ICU admissions) exhibited severe TBI (GCS < 9); of these, 1,031 (56%) had ICP monitoring. The "worst" and the "best" cases were both less likely to receive ICP monitoring. Younger patients, female patients, and patients with isolated TBI were more likely to receive ICP monitoring. Compared with large centers ICP was monitored more frequently [odds ratio (OR) 3.09, CI 2.42-3.94] in medium-sized centers. The 20% of patients with the highest likelihood to receive ICP monitoring were monitored in 91% of cases, and had the lowest hospital mortality (31%, OR 0.78, CI 0.37-1.64). Multivariate analysis revealed that severity of illness, TBI severity, isolated TBI, and the number of cases treated per year were associated with hospital outcome. Compared with the large centers, ORs for hospital mortality were 1.85 (CI 1.42-2.40) for patients from medium-sized centers and 1.91 (CI 1.24-2.93) for patients from small centers. CONCLUSIONS: ICP monitoring may possibly have some beneficial effects, but this needs further evaluation. Patients with severe TBI should be admitted to experienced centers with high patient volumes since this might improve hospital mortality rates.