Clincosm LogoSign in Get a demo

Identification of Outcome Relevant Indicators in Routine Data

Sponsor
Charite University, Berlin, Germany (Other)
Overall Status
Recruiting
CT.gov ID
NCT04670744
Collaborator
(none)
1,000,000
Enrollment
2
Locations
59.9
Anticipated Duration (Months)
500000
Patients Per Site
8343.6
Patients Per Site Per Month

Study Details

Study Description

Brief 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.

Condition or Disease Intervention/Treatment Phase

    Detailed Description

    The patterns that are relevant for patient-centered outcomes can be combinations of different parameters (e.g. vital signs, laboratory values, previous illnesses), which in themselves do not necessarily have a pathogenic effect, but in a specific combination may have a high relevance for the patient-centered outcome.

    This project pursues as research goal the anesthesiological and intensive care risk reduction. To this end, the existing data sets of routine care are to be used to identify outcome-relevant patterns in order to derive recommendations for improving treatment in line with the patient's wishes. Standard Operating Procedures (SOPs) and Quality Indicators (QIs) in combination with the data of routine clinical care will be used as a basis. The approach outlined is closely linked to the development of quality-based treatment structures. In order to be able to offer medical treatment at a high level, associated processes must be known and operationalized, i.e. measurable. QIs (quality indicators) are an established instrument for measuring individual dimensions of treatment quality, and our clinic is a leading participant in this process at both national and international level (see Spies et al. Guidelines for Delirium, Analgesia and Sedation). The mapping of quality-based treatment structures as SOPs (Standard Operating Procedures) is also essential in this context (see Spies et al. SOPs in Anesthesiology and Pain Therapy, Thieme Verlag). By applying data science-based methods, this study pursues the overall goal of supporting the transfer of evidence-based findings in the form of QIs and SOPs into patient care.

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

    Study Design

    Study Type:
    Observational
    Anticipated Enrollment :
    1000000 participants
    Observational Model:
    Cohort
    Time Perspective:
    Retrospective
    Official Title:
    Retrospective Analysis for the Identification of Outcome Relevant Indicators ("Patterns") in Routine Data and Investigation of the Influence on Patient-centered Outcome for a Data-driven Improvement of Quality-based Treatment of Perioperative and Intensive Care Patients
    Actual Study Start Date :
    Dec 3, 2020
    Anticipated Primary Completion Date :
    Dec 1, 2024
    Anticipated Study Completion Date :
    Dec 1, 2025

    Outcome Measures

    Primary Outcome Measures

    1. Functional status [01.01.2016-31.12.2024]

      The functional status of the patient is measured by routine score data. The scores, which measure physical, role, and social functioning, and mobility reflect worse/better outcome depending on the score construction.

    Secondary Outcome Measures

    1. Morbidity [01.01.2016-31.12.2024]

      Morbidity is evaluated by International Classification of Diseases (ICD) (10th version). /Operation codes (OPS)

    2. Mortality I [01.01.2016-31.12.2024]

      Mortality is measured by inhouse mortality

    3. Mortality II [01.01.2016-31.12.2025]

      Mortality is measured by long-term mortality (1 year)

    4. Accounting data [01.01.2016-31.12.2024]

      Accounting data are providid by the controlling department

    Eligibility Criteria

    Criteria

    Ages Eligible for Study:
    N/A to 120 Years
    Sexes Eligible for Study:
    All
    Accepts Healthy Volunteers:
    No
    Inclusion Criteria:

    • Age: 0 to 120 years

    • Gender: female, male, diverse

    • Electronically documented anesthesiological or intensive care treatment in the HIS (Hospital Information System) and PDMS (Patient Data Management System) of the Charité (Dep. for Anesthesiology with focus on operative intensive care, CCM/CVK/CBF) since 2006

    Exclusion Criteria:

    -none

    Contacts and Locations

    Locations

    Site City State Country Postal Code
    1 Department of Anesthesiology and Intensive Care Medicine Campus Charité Mitte and Campus Virchow-Klinikum, Charité - Universitaetsmedizin Berlin Berlin, Berlin Germany 10117
    2 Department of Anesthesiology and Operative Intensive Care Medicine (CBF), Charité - Universitätsmedizin Berlin Berlin Germany 12203

    Sponsors and Collaborators

    • Charite University, Berlin, Germany

    Investigators

    • Study Director: Claudia Spies, MD Prof., Charite University, Berlin, Germany

    Study Documents (Full-Text)

    None provided.

    More Information

    Publications

    None provided.
    Responsible Party:
    Claudia Spies, Head of the Department of Anesthesiology and Operative Intensive Care Medicine (CCM/CVK), Charite University, Berlin, Germany
    ClinicalTrials.gov Identifier:
    NCT04670744
    Other Study ID Numbers:
    • QUALIPATT
    First Posted:
    Dec 17, 2020
    Last Update Posted:
    Dec 23, 2020
    Last Verified:
    Dec 1, 2020
    Individual Participant Data (IPD) Sharing Statement:
    No
    Plan to Share IPD:
    No
    Studies a U.S. FDA-regulated Drug Product:
    No
    Studies a U.S. FDA-regulated Device Product:
    No

    Study Results

    No Results Posted as of Dec 23, 2020