Identification of Outcome Relevant Indicators in Routine Data
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 patter
| Condition(s) | Anesthesiological Risk Reduction, Intensive Care Risk Reduction |
|---|---|
| Status | Recruiting |
| Study type | Observational |
| 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. |
| Who can participate | 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 (Department of Anesthesiology and Intensive Care Medicine, CCM/CVK/CBF) since 2016 Exclusion Criteria: -none |
| Ages | 120 Years |
| Sex | All |
| Lead sponsor | Charite University, Berlin, Germany |
| Locations | Berlin, State of Berlin, Germany |
| Start date | 2020-12-03 |
| NCT ID | NCT04670744 |
| Official listing | https://clinicaltrials.gov/study/NCT04670744 |