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Identification of Outcome Relevant Indicators in Routine Data

NCT04670744 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 1000000

Last updated 2026-01-21

No results posted yet for this study

Summary

The availability of electronic documentation systems in patient care means that large amounts of clinical routine data are available from which conclusions can be drawn for improving patient care. Compared to conventional research approaches, a data science-oriented approach offers the possibility of identifying patterns in routine data ("pattern recognition") that are relevant for patient-centered outcomes.

Numerous projects and sub-projects can be evaluated from this data set.

Conditions

  • Anesthesiological Risk Reduction
  • Intensive Care Risk Reduction

Sponsors & Collaborators

  • Charite University, Berlin, Germany

    lead OTHER

Principal Investigators

  • Claudia Spies, MD Prof. · Charite University, Berlin, Germany

Eligibility

Max Age
120 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-12-03
Primary Completion
2026-12-31
Completion
2026-12-31

Countries

  • Germany

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04670744 on ClinicalTrials.gov