A5030395647- Data Quality and Management
- Electronic Health Records Systems
- Clinical practice guidelines implementation
- Privacy-Preserving Technologies in Data
- Biomedical Text Mining and Ontologies
- Lung Cancer Diagnosis and Treatment
- COVID-19 and healthcare impacts
- Ethics in Clinical Research
- Urological Disorders and Treatments
- Machine Learning in Healthcare
- Prostate Cancer Diagnosis and Treatment
- Chronic Disease Management Strategies
- Urinary Bladder and Prostate Research
- Medical Coding and Health Information
- Advances in Oncology and Radiotherapy
- Medical and Health Sciences Research
- Big Data Technologies and Applications
Heidelberg University
2019-2024
University Hospital Heidelberg
2019-2024
University Medical Centre Mannheim
2023
University of Mannheim
2019
Introduction: Data quality (DQ) is an important prerequisite for secondary use of electronic health record (EHR) data in clinical research, particularly with regards to progressing towards a learning system, one the MIRACUM consortium's goals. Following successful integration i2b2 research repository MIRACUM, we present standardized and generic DQ framework.
To assess the change in inpatient radiotherapy related to COVID-19 lockdown measures during first wave of pandemic 2020.
Health data from hospital information systems are valuable sources for medical research but have known issues in terms of quality. In a nationwide integration project Germany, health care all participating university hospitals being pooled and refined local centers. As there is currently no overarching agreement on how to deal with errors implausibilities, meetings were held discuss the current status need develop consensual measures at organizational technical levels. This paper analyzes...
The Demonstrator study aims to analyse comorbidities and rare diseases among patients from German university hospitals within the Medical Informatics Initiative. This work aimed design determine feasibility of a model assess quality claims data used in study. Several issues were identified affecting small amounts cases one participating sites. As next step an extension all sites is planned.
Background Leveraging electronic health record (EHR) data for clinical or research purposes heavily depends on fitness. However, there is a lack of standardized frameworks to evaluate EHR suitability, leading inconsistent quality in use projects (DUPs). This focuses the Medical Informatics Research and Care University Medicine (MIRACUM) Data Integration Centers (DICs) examines empirical practices assessing automating fitness-for-purpose German DIC settings. Objective The study aims (1)...
<sec> <title>BACKGROUND</title> Leveraging electronic health record (EHR) data for clinical or research purposes heavily depends on fitness. However, there is a lack of standardized frameworks to evaluate EHR suitability, leading inconsistent quality in use projects (DUPs). This focuses the Medical Informatics Research and Care University Medicine (MIRACUM) Data Integration Centers (DICs) examines empirical practices assessing automating fitness-for-purpose German DIC settings. </sec>...