Judith SchultzeBusiness Development & Sales
DATA GOVERNANCE
Health Data Governance – strategic data management
An average hospital produces at least 50 petabytes of data every year. Most of this data is unstructured, which means that it must be normalized and standardized to be machine-readable. The successive use of HL7 /FHIR means that an increasing amount of structured data is available that can be transferred between actors and systems without media discontinuity.
Together with you, we develop a solid health data governance that can handle these challenges and manage data securely in strategic and organizational terms throughout its entire life cycle. Our core competence lies in process optimization: clear workflows for capturing, storing, processing and cleansing data. This process orientation is a basis for efficient and secure data use.
The large number of players and systems involved in healthcare, as well as the networking of the various IT components, gives rise to dependencies and security risks. That is why data security and compliance (GDPR 2.0; critical infrastructure protection) are particularly important.
A solid data governance strategy provides a basis for better patient care by enabling more accurate diagnoses and treatments, providing data for research and innovation, reducing duplication of effort and data inconsistencies, and building trust with patients and partners to share (health) data digitally.
Topic overview
Why is digital data governance worthwhile?
- Role and rights management
- Clear definition of who can access which data.
- Minimization of unauthorized access and security breaches.
- Types of data collected
- Determining which data may and should be collected.
- Taking legal and ethical standards into account.
- Ensuring data quality
- Use and maintenance of meta data for better organization.
- Ensuring that data is up to date and accurate.
- Consistency checks to avoid redundancy and errors.
- Standardized data models
- Definition of and adherence to standardized data formats (e.g. HL7, FHIR).
- Promotion of interoperability between systems and actors.
- Compliance and data protection
- Compliance with legal requirements (e.g. GDPR, KRITIS).
- Protection of sensitive health data from misuse.
- Efficient process design
- Optimization of workflows for data collection, storage and processing.
- Ensuring seamless communication between stakeholders.
Digital Health: our data governance services at a glance
- Data governance consulting
- Development of individual data management strategies across the entire lifecycle.
- Consultancy on role and rights concepts, data quality standards and the introduction of HL7/FHIR.
- Support in meeting compliance requirements (e.g. GDPR, KRITIS).
- Process analysis and optimization
- Analysis of existing data processes and identification of weak points.
- Development and implementation of optimized workflows for data collection, processing and use.
- Recommendations for the integration of interoperability standards.
- Operating data governance platforms
- Hosting and management of data platforms and their interfaces.
- Ensuring smooth operation, including monitoring, security and updates.
- Provision of support services for ongoing operations.
- Training and education
- Training employees on topics such as data quality, use of tools, compliance and data protection.
- Development of customized training programs for IT and business departments.
- Workshops to raise awareness and provide skills in data governance processes, such as data governance processes in the healthcare sector.
- Change management and implementation support.
- Support with the introduction of new data governance structures and technologies.
- Change management programs to promote acceptance in the organization.
- Support from pilot projects to full-scale implementation.
- Efficient process design
- Optimization of workflows for data collection, storage and processing.
- Ensuring seamless communication between stakeholders.
Digital Health: Governance Examples
- Requirement
- Centralized data management: The hospital needed a unified strategy to structure and make data usable.
- Interoperability: Improving data exchange between different IT systems (e.g. patient management, laboratory data, research).
- Compliance: Ensuring compliance with GDPR and KRITIS requirements when processing sensitive patient data.
- Quality assurance: Introducing processes to continuously review and improve data quality.
- Solutions
- Strategy development: Development of a data governance strategy with clearly defined roles, rights and responsibilities.
- Technical implementation: Introduction of a data platform based on HL7/FHIR to standardize and harmonize data.
- Training: Provision of training for IT and specialist staff on data protection, compliance and the use of the new platform.
- Operations: Takeover of continuous operation and monitoring of the platform with regular security and quality checks.
- Your benefits
- More efficient processes: Accelerated and seamless data exchange between departments and systems.
- Improved data quality: Consistent and up-to-date data for more precise diagnoses, treatments and research.
- Compliance security: Adherence to legal requirements, reduction of liability risks.
- Trust and acceptance: Adoption of processes by employees and use of tools
Advantages of health data governance
- Increased efficiency: Optimized workflows and smooth data exchange between systems and stakeholders.
- Higher data quality: Consistent, up-to-date and usable data for better decisions and analyses.
- Compliance security: Compliance with legal requirements (e.g. GDPR, KRITIS) and minimization of liability risks.
- Interoperability: Seamless integration and communication between different IT systems.
- Trust and transparency: Promoting acceptance by patients and employees through transparent and secure data management.
Karina SchäferBusiness Development & Sales
YOUR DATA GOVERNANCE STRATEGY
With an efficient health data governance strategy, you can optimize operational processes. Together, we can create the basis for future-oriented and data-driven healthcare.
