Идёт набор NCT04670744

Identification of Outcome Relevant Indicators in Routine Data

— Наблюдательное Anesthesiological Risk Reduction Intensive Care Risk Reduction

Ориентир для пациента и семьи

Простыми словами

Автоматическая сводка по структурированным данным реестра. Она помогает сориентироваться, но не заменяет официальный протокол или оценку врача.

Что изучают: Это наблюдательное исследование: исследуемое лечение участникам по протоколу не назначают.
Кому может быть актуально: Состояния в реестре: Anesthesiological Risk Reduction, Intensive Care Risk Reduction. Базовые параметры: до 120 лет · Все.
Что важно проверить: Возраст, диагноз и пол — только базовые ориентиры. Предыдущее лечение, анализы и другие обязательные условия указаны ниже в критериях участия.
Где проводится: Германия
Следующий шаг: Сохраните исследование, покажите его лечащему врачу и уточните актуальный статус у исследовательского центра. Расходы, документы и поездка →

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Официальное название

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

Обзор

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.

Подробное описание

The patterns that are relevant for patient-centered outcomes (e.g. mortality) 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.

Первичные конечные точки

Mortality I [Срок оценки: 01.01.2016-30.04.2026]
Mortality II [Срок оценки: 01.01.2016-30.04.2026]

Вторичные конечные точки (4)

Morbidity [Срок оценки: 01.01.2016-30.04.2026]
Accounting data [Срок оценки: 01.01.2016-30.04.2026]
Functional status [Срок оценки: 01.01.2016-30.04.2026]
Post Intensive Care Syndrome (PICS) [Срок оценки: 01.01.2016-30.04.2026]

Критерии участия

Критерии включения

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