Learning for Sustainable Organisational Interoperability

Weichhart, Georg

doi:10.3182/20140824-6-za-1003.01590

Cited by 6 publications

(2 citation statements)

References 22 publications

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“…To achieve organizational interoperability and reach common goals, organizations should define and align responsibilities, processes, and expectations [ 63 , 64 ]. A diversity of theoretical backgrounds of researchers in the federated network was observed, resulting in the need for building a common ground.…”

Section: Discussionmentioning

confidence: 99%

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

Meurisse,

Estupiñán-Romero,

González-Galindo

et al. 2023

BMC Med Res Methodol

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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.

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Section: Discussionmentioning

confidence: 99%

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

Meurisse,

Estupiñán-Romero,

González-Galindo

et al. 2023

BMC Med Res Methodol

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“…This allows for integration of platforms already established as means for collaboration and communication in an organization and does not enforce using "yet another" platform. To be able to process information from other applications contributing to the DOBK, an interopera- bility platform is researched (Weichhart 2014). Technically based on a well-established and simple-to-use REST API approach, the platform provides an enhanced enterprise-service-bus-like environment.…”

Section: Manipulationmentioning

confidence: 99%

Putting the Framework to Operation: Enabling Organizational Development Through Learning

Oppl

Stary

2019

Designing Digital Work

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This chapter instantiates the proposed framework for developing consensually shared workflow designs. It shows how the framework can be put to operation using instruments that have been successfully deployed in practice. These instruments enable articulation and alignment of work process knowledge, allow its representation and transfer within organizations, and facilitate acting on these representations for validation and implementation in diverse organizational settings. We here adopt an organizational learning perspective and situate the presented socio-technical instruments along a multi-perspective learning chain informed by the components of the framework. It thus offers instruments supporting the articulation and alignment of work process knowledge, its multi-faceted representation and flexible manipulation, as well as support for processing the resulting models for validation and refinement. Using the framework as a coherent lens on the requirements on support and the respective features of the instruments allows to offer an integrated view, which demonstrates digital work design support in organizational practice.

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Case Studies

Oppl¹,

Stary²

2019

Designing Digital Work

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This chapter demonstrates the use of the proposed framework and the embedded methods. It shows their interplay and describes the impacts that could be observed in real-world cases. This chapter is practiceoriented and could provide students and practitioners with anchors to reflect on the proposed methods and underlying theories from a "doing" point of view.The first case (Sect. 8.1) demonstrates how meaningful work-model entities can develop in the course of articulation and guide aligned restructuring of work. It stems from a complex setting, namely, planning in clinical health treatment requiring the structured elicitation of contextual knowledge from all stakeholders involved to develop working procedures in time-critical situations. Sharing expert knowledge from doctors, nurses, technicians, administration, and patients was supported by collaborate development of instruments and tools.The CoMPArE/WP (Collaborative Model Articulation and Elicitation of Work Processes)-case (Sect. 8.2) has its focus on alignment when bridging from intuitive or semi-structured models to techno-centric (formal) models that can be executable for some workflow engine. It demonstrates effective stakeholder participation while eliciting and consolidating Case Studies 8

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Learning for Sustainable Organisational Interoperability

Cited by 6 publications

References 22 publications

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

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

Putting the Framework to Operation: Enabling Organizational Development Through Learning

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