Identification of Outcome Relevant Indicators in Routine Data

Anesthesiological Risk Reduction Clinical Trial

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

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04670744
• Other study ID #: QUALIPATT
• Status: Recruiting
• Start date: December 3, 2020
• Est. completion date: December 2025

Study information

• Verified date: December 2020
• Source: Charite University, Berlin, Germany
• Contact: Claudia Spies, MD, Prof.
• Phone: +49 30 450 55 11 02
• Email: claudia.spies[@]charite.de
• Is FDA regulated: No
• Study type: Observational

Clinical Trial 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.

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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 1000000
• Est. completion date: December 2025
• Est. primary completion date: December 2024
• Accepts healthy volunteers: No
• Gender: All
• Age group: N/A to 120 Years

Eligibility

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

Related Conditions & MeSH terms

• Anesthesiological Risk Reduction
• Intensive Care Risk Reduction

Locations

Country	Name	City	State
Germany	Department of Anesthesiology and Operative Intensive Care Medicine (CBF), Charité - Universitätsmedizin Berlin	Berlin
Germany	Department of Anesthesiology and Intensive Care Medicine Campus Charité Mitte and Campus Virchow-Klinikum, Charité - Universitaetsmedizin Berlin	Berlin,	Berlin

Sponsors (1)

Lead Sponsor	Collaborator
Charite University, Berlin, Germany

Country where clinical trial is conducted

Germany, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Functional status	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.	01.01.2016-31.12.2024
Secondary	Morbidity	Morbidity is evaluated by International Classification of Diseases (ICD) (10th version). /Operation codes (OPS)	01.01.2016-31.12.2024
Secondary	Mortality I	Mortality is measured by inhouse mortality	01.01.2016-31.12.2024
Secondary	Mortality II	Mortality is measured by long-term mortality (1 year)	01.01.2016-31.12.2025
Secondary	Accounting data	Accounting data are providid by the controlling department	01.01.2016-31.12.2024