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<p>Routine data from healthcare are gaining importance for evidence generation. In Germany, new structures have been established in recent years to support their use. As part of the Medical Informatics Initiative (MII), data integration centres (DIZ) have been set up at all university hospitals, where patient data are made available in a&#xa0;pseudonymized, standardized and operationalized form. Since routine data, unlike primary data, are collected for healthcare purposes, aspects of the original data collection must be considered when formulating the research question, planning and analysing the study, and interpreting the results.</p><p>The EVAluation research based on data from routine clinical care 4&#xa0;the MII (EVA4MII) project supports researchers in analysing nationwide clinical routine data, for example through training programs and a&#xa0;central advisory service. This support is provided by an interdisciplinary team with methodological-statistical, data-technical, and clinical-epidemiological expertise in close coordination with data-providing institutions. The service covers the entire research process, from study planning and formal requirements to implementation, analysis, evaluation, and publication, and is available to projects within the MII and beyond.</p><p>The aim of this article is to highlight the importance of methodological support in the analysis of clinical routine data and to identify key stages in the research process where such support is particularly relevant. Finally, an outlook on future advisory needs is provided, including the potential role of artificial intelligence as a&#xa0;supportive tool.</p>

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Evidenzgenerierung und methodische Beratung durch das Projekt „EVAluationsforschung auf der Grundlage von Daten aus der klinischen Routineversorgung für die Medizininformatik-Initiative“ (EVA4MII)

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月4日

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  • Michelle Pfaffenlehner,
  • Miriam Kesselmeier,
  • Kai Günther,
  • Kathrin Ungethüm,
  • Viktoria Rücker,
  • Flavia Remo,
  • Harald Binder,
  • André Scherag,
  • Peter Heuschmann,
  • Nadine Binder

摘要

Routine data from healthcare are gaining importance for evidence generation. In Germany, new structures have been established in recent years to support their use. As part of the Medical Informatics Initiative (MII), data integration centres (DIZ) have been set up at all university hospitals, where patient data are made available in a pseudonymized, standardized and operationalized form. Since routine data, unlike primary data, are collected for healthcare purposes, aspects of the original data collection must be considered when formulating the research question, planning and analysing the study, and interpreting the results.

The EVAluation research based on data from routine clinical care 4 the MII (EVA4MII) project supports researchers in analysing nationwide clinical routine data, for example through training programs and a central advisory service. This support is provided by an interdisciplinary team with methodological-statistical, data-technical, and clinical-epidemiological expertise in close coordination with data-providing institutions. The service covers the entire research process, from study planning and formal requirements to implementation, analysis, evaluation, and publication, and is available to projects within the MII and beyond.

The aim of this article is to highlight the importance of methodological support in the analysis of clinical routine data and to identify key stages in the research process where such support is particularly relevant. Finally, an outlook on future advisory needs is provided, including the potential role of artificial intelligence as a supportive tool.