Modern Health Data Management
Our data room solutions optimize the management of healthcare data, promote interoperability, and support hospitals and research institutions in their digital transformation.
Efficient Data Management in Healthcare
Our Health Data Management provides powerful solutions to optimize data flows, interoperability, and data integration for hospitals, research institutions and hospital networks.
In an increasingly digitalized healthcare landscape, the efficient integration and management of healthcare data is essential. Our Health Data Management solutions support both research projects and the entire clinical care pathway with a comprehensive healthcare management system—from Clinical Data Repository (CDR) and Interoperability Platform (IOP) to value-added services.
The Clinical Data Repository (CDR) enables centralized, vendor-neutral management of health data. The platform consolidates patient data from various IT systems such as HIS, LIS and PACS into a semantically standardized data structure. This provides a holistic view of patient data, optimizes research, and accelerates and optimizes care processes. In addition, the CDR increases data sovereignty by leveraging open standards such as openEHR and FHIR.
Our Interoperability Platform (IOP) ensures the seamless exchange of data between different IT systems and hospital networks. It uses open standards such as HL7, IHE and FHIR to ensure efficient and secure data harmonization. The platform also enables fast and accurate provision of healthcare data for research, care and decision-making processes.
Based on the customer-specific solution structure, CDR and IOP provide ideal foundations for a variety of value-added services across administrative, clinical-administrative, and medical areas—with the goal of creating a data ecosystem for medical controlling, quality assurance, research, and decision support in patient diagnosis and treatment processes.
A sophisticated and efficient health data management offers enormous potential for increasing value creation and driving digitalization in healthcare. It enables precise real-time analytics, meaningful reporting, and seamless data synchronization between all stakeholders in the healthcare system. In doing so, it plays a crucial role in providing better information and supporting well-founded decisions throughout the care process.
Open standards such as openEHR and FHIR, which are integrated into CDR/IOP solutions, ensure vendor-neutral (VNA) interoperability and give users full data sovereignty. A particular focus here is placed on maximum data security: separating demographic and medical data not only builds trust in research but also lays the foundation for the safe use of innovative technologies in artificial intelligence, such as machine learning (ML) and large language models (LLM).
In addition, centralized storage and structured processing of data enables fast access and precise analyses, boosting efficiency in everyday medical operation. Thanks to its flexible scalability and modern container technology, combined with deployment on the Open Telekom Cloud, this solution is ideally equipped to meet future requirements. Efficient health data management combines security, interoperability, and performance—forming the foundation for a connected, future-oriented healthcare system.
Health Data Management solutions are designed for various stakeholders in healthcare who want to benefit from centralized and efficient management of healthcare data. Hospitals and hospital networks benefit from a centralized solution that enables them to securely manage and effectively use patient data. Research institutions, on the other hand, benefit from consolidated access to structured data that is essential for clinical studies and research. Insurance and pharmaceutical companies can also benefit from these solutions, as healthcare management systems support precise data analysis that are essential for informed decisions and better planning.
What do
Health Data Management solutions offer?
Efficiently collecting, transforming, integrating, and validating health data from multiple sources: To acquire data, patient data can be collected from a wide range of sources, including electronic health records, laboratory data, and medical devices. This ensures a comprehensive and up-to-date database within health data management. The collected data is transformed into a standardized format to facilitate analysis and utilization. The transformation includes cleaning and standardizing the data to ensure its quality and consistency. Rigorous validation processes ensure that the health data is accurate and reliable. This is crucial for precise diagnoses and treatment decisions. A centralized view of aggregated data, for example through seamless integration into existing information systems, supports cross-divisional and cross-sector collaboration.
In a Clinical Data Repository (CDR), all patient-centered and medical data is modeled and stored. This health data is stored using international standards such as FHIR or openEHR. Since the data is retained in its original format, a CDR not only ensures future-proofing but also enables the use of health data independently of individual vendors. This guarantees centralized storage, structured processing, and real-time availability for other applications. As a result, hospitals, for example, are supported in building an interoperable, data-driven system landscape and working more efficiently in both healthcare and clinical research.
An interoperable use of electronic health data within a platform or for dedicated value-added services is enabled, for example, through the use of a FHIR facade or AQL queries. This allows the data to be leveraged for further applications such as machine learning (ML), research or patient portals, and clinical decision support systems (CDSS). The integration and exchange of health data—enabled by centralized storage, structured processing, and real-time availability—ensure better data utilization across various applications. This creates an interoperable, data-centric system landscape that supports more efficient work in both healthcare and research.
Our services—your Benefits
Health data management solutions such as CDR and IOP enable vendor-neutral digitalization and serve as the foundation for a connected digital transformation and innovation strategy.
Take a look at your benefits:
Implementing aggregated data management in healthcare can enable consolidated and persistent quality of patient data. This reduces existing data silos and minimizes the need for complex interfaces. Harmonizing and standardizing data sources creates a central, reliable database that can be used for various healthcare applications. This leads to improved data quality and facilitates access to relevant information, ultimately increasing the efficiency and effectiveness of healthcare.
Vendor neutrality and the separation of data storage and application not only reduce interface costs but also consolidate data sovereignty. This separation ensures that health data can be managed and stored independently of specific vendors, increasing flexibility and control over the data. This helps companies and organizations maintain their data sovereignty while improving the efficiency and security of their data processing systems.
Centralized, harmonized data storage and interoperable use in health data management contribute significantly in reducing inconsistencies in medical data and improving its quality. Standardizing data sources and creating a consolidated database ensures that all relevant information is consistent and reliable. This not only facilitates access to data but also enables more efficient and accurate analysis, ultimately leading to higher data quality. System interoperability ensures that data can be exchanged seamlessly between different applications and institutions, further improving the overall quality and availability of medical data.
Improved data consistency within a centralized storage system provides easier access to patient data and enables or facilitates patient involvement in care and research processes. Centralized storage keeps all relevant information consistent and reliable, simplifying access to these electronic health data for both patients and medical staff. This leads to more active patient engagement in their own healthcare and supports research by providing access to high-quality, consistent data.
What differs CDR from traditional data management systems?
The Clinical Data Repository (CDR) consolidates and aggregates data from different systems, vendor-neutral, and provides a central, unified view on healthcare data. This data health management facilitates its use for research and clinical applications within an interoperability platform (IOP) and/or specific value-added services.
Where do the solutions support clinical care?
Hospitals process highly sensitive data within inpatient care. Due to the large number of data sources and specialized departments within hospitals, IT applications and infrastructure often have a heterogeneous environment.
To meet future requirements for the use of artificial intelligence and to handle the increasing volume of data, IT resources must therefore become increasingly scalable. This is essential for supplying Clinical Decision Support Systems (CDSS) and supporting various clinical processes.
In this context, T-Systems' Health Data Management solutions help establish a modern, digital foundation for IT and healthcare applications by storing, enriching, and making health and process data available in a structured way.
By implementing a Clinical Data Repository (CDR), the necessary conditions can be created to consolidate relevant data across systems in one place—establishing a “single point of truth”.
Are there examples for value-added services?
The value-added services based on a CDR or IOP range from analytical KPI dashboards for clinical management, apps and reports for clinical staff, and business intelligence (BI) for controlling, to supplying portals, IoT solutions, and AI/ML-supported data pools.
In addition to horizontal added value such as analytics, dashboards, cockpits, and BI, CDR and IOP also offer the integration of vertical added value in the context of care, research, administration, and patient management. The spectrum ranges from clinical decision support systems (CDSS) and alert apps (e.g., sepsis) to feasibility checks and gap analyses for patient pools or data research sandboxes in research, to AI-supported translation of unstructured data into structured health data (e.g., medical histories, doctor's/discharge letters), and data utilization from wearables, RWD (real-world data), and ePRO (electronic patient record outcome).
What are the challenges for the future-proof data spaces in healthcare?
One of the biggest challenges for future-proof data spaces in healthcare is the lack of data connectivity. Electronic health data is often stored in different systems and formats, making its integration and use difficult. Furthermore, much data is poorly structured and semantically insufficiently prepared, which hinders or at least limits analysis and exchange. However, a more serious problem is the lack of data necessary for comprehensive analyses and decisions due to the lack of interfaces or the limited availability of data. In addition, delays in data availability can lead to important information not being accessible in time, which affects the efficiency and quality of healthcare.
Data protection insecurity also poses a major challenge: Strict regulations and concerns about data security make it difficult to use and share health data effectively. Finally, there is often no integrated use of pseudonymized healthcare data for research projects, which limits the potential for scientific discoveries and innovations in healthcare.