Learning Health System: Experiences in Accessing and Curating Complex Routine Data from a Hospital Group to Improve Implant Surgery Outcomes...36th Medical Informatics Europe (MIE) Conference, May 25-28, 2026, Genoa, Italy.

This study explores the development of a Learning Health System (LHS) to enhance implant surgery outcomes at Klinikum Region Hannover (KRH), Germany. Using the cross-industry standard process for data mining (CRISP-DM) framework, routine clinical data from multiple hospital systems, focusing on hip,...

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Publicado en:Studies in Health Technology & Informatics Vol. 336; pp. 695 - 700
Autores principales: HASSMANN, Jörg, KRÖNER, Saskia, HAMMER, Jonas, PRZYSUCHA, Mareike, STACHE, Martin, TEUTEBERG, Frank, HÜBNER, Ursula
Formato: proceedings research tables/charts Journal Article
Publicado: Sage Publications Inc. 2026
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Learning Health System: Experiences in Accessing and Curating Complex Routine Data from a Hospital Group to Improve Implant Surgery Outcomes...36th Medical Informatics Europe (MIE) Conference, May 25-28, 2026, Genoa, Italy.
      aug:
        au:
          HASSMANN, Jörg
          KRÖNER, Saskia
          HAMMER, Jonas
          PRZYSUCHA, Mareike
          STACHE, Martin
          TEUTEBERG, Frank
          HÜBNER, Ursula
        affil: Research Centre of Health & Social Informatics, University AS Osnabrück, Germany.
      sug:
        subj:
          Learning Health System Administration
          Electronic Health Records Administration
          Data Mining
          Prostheses and Implants
          Treatment Outcomes
          Quality Improvement
          Congresses and Conferences Italy
          Italy
          Human
          Hip Surgery
          Knee Surgery
          Shoulder Surgery
          Germany
          Data Quality
          Data Curation
          Funding Source
      ab: This study explores the development of a Learning Health System (LHS) to enhance implant surgery outcomes at Klinikum Region Hannover (KRH), Germany. Using the cross-industry standard process for data mining (CRISP-DM) framework, routine clinical data from multiple hospital systems, focusing on hip, knee and shoulder implants were accessed and curated. Data integration involved 35 tables and 1,702 variables. Key steps included data cleaning, standardization, and validation to improve access, accuracy, completeness, and consistency. Data access and curation experience showed that building an LHS using complex data under real-world conditions is still a cumbersome undertaking.
      pubtype: Academic Journal
      doctype:
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        research
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      ougenre: Article
    language: English
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