HEALTH CARE
TOPICS THAT MOVE
In this industry, the focus is on managing patient data and health information. Data protection, interoperability between different healthcare organizations, data quality and the use of data analytics for improved patient care are the main concerns. Innovative technologies such as electronic health records and telemedicine are shaping the industry to enable high-quality, efficient and patient-centered care.
Analytics
and big data
Effectively leveraging big data to improve patient care, research and operational efficiency is a major challenge. The ability to extract, analyze, and transform data from diverse sources into valuable insights requires advanced analytical tools and expertise.
Data quality
and standardization
Insufficient data quality and lack of standardization can lead to misdiagnosis and inefficient patient care. It is important that data is accurate, up-to-date and in a standardized format that is understood by all healthcare stakeholders.
Interoperability
of data
Health data is often stored in siled systems, making it difficult to merge and share information between different healthcare organizations. This affects continuity of patient care and the ability to maintain comprehensive medical records.
Data protection and
Compliance
Patient data is some of the most sensitive information there is. Protecting this data from unauthorized access and complying with strict data protection regulations such as HIPAA in the US or GDPR in the EU are key challenges.
ANALYTICS AND BIG DATA
In the healthcare sector, an implemented data management system can revolutionise comprehensive analytics and the handling of big data:
SOLUTION
DATA INTEGRATION
The system can integrate data from various sources such as electronic medical records, laboratory systems and wearables to create a holistic data landscape.
SOLUTION
ADVANCED ANALYTICS
Using advanced analytics tools powered by artificial intelligence and machine learning to identify patterns critical to patient care and diagnosis.
SOLUTION
DATA PROTECTION
The system ensures that all data is processed and analyzed in compliance with strict data protection standards, such as those set by HIPAA.
ADVANTAGE
RISK
MINIMIZATION
Deeper insights into patient data can improve treatment outcomes and develop personalized therapeutic approaches.
ADVANTAGE
PREDICTION AND
PREVENTION
Big data analytics make it possible to predict disease trends and improve preventive measures.
ADVANTAGE
IMPROVED
CARE
Optimizing healthcare operations leads to cost reductions and improved patient services.
ADVANTAGE
RESEARCH AND
DEVELOPMENT
Analysing large amounts of data can advance medical research and contribute to the development of new drugs and therapies.
INTEROPERABILITY
OF DATA
An effective healthcare data management system can significantly improve data interoperability, meaning information systems and software applications can seamlessly exchange and make sense of data:
SOLUTION
STANDARDIZED
FORMATS
The system supports established health information standards such as HL7, FHIR or DICOM, which facilitate the exchange of health data between different IT systems.
SOLUTION
APIs FOR THIRD PARTY SYSTEMS
By providing APIs, data can be securely exchanged between different healthcare facilities, such as hospitals, surgeries and pharmacies, as well as with centralised healthcare databases.
SOLUTION
DATA
CONSILIDATION
It enables the consolidation of patient data from various sources into a unified electronic patient record.
ADVANTAGE
IMPROVED
PATIENT ACCESS
Patients can gain better access to their health data and share it between different providers.
ADVANTAGE
MORE EFFICIENT
CARE
Interoperability facilitates fast and accurate communication between different healthcare providers, which improves the coordination of patient care.
ADVANTAGE
REDUCTION OF
REDUNDANCIES
Avoiding duplicate examinations and testing by making existing data easier to access.
ADVANTAGE
MORE FOUNDED
BASE
Doctors and nurses can access a more complete data history, leading to better-informed decisions about patient care.
DATA QUALITY AND STANDARDIZATION
A healthcare data management system focused on data quality and standardization can provide significant solutions and benefits:
SOLUTION
MECHANISMS FOR
QUALITY ASSURANCE
The system carries out continuous quality checks to ensure that the health data is correct, complete and up-to-date.
SOLUTION
STANDARDIZATION
PROTOCOLS
It leverages healthcare-specific data standards such as HL7, LOINC and SNOMED CT to unify data structuring and classification.
SOLUTION
VALIDATION
PROCESSES
Integration of strict validation processes during data entry to minimise errors and increase data integrity.
ADVANTAGE
SIMPLIFIED
DATA EXCHANGE
Standardized data facilitates exchange between different healthcare systems and ensures consistent information.
ADVANTAGE
HIGHER
PRECISION
Improved data quality allows healthcare providers to make more accurate diagnoses and plan more effective treatments.
ADVANTAGE
EFFICIENT CLINICAL WORK PROCESSES
Consistent, high-quality data leads to optimized clinical workflows and reduced administrative effort.
ADVANTAGE
BETTER
BASIS
High-quality, standardized data is an essential basis for clinical research and studies that can contribute to improving patient care.
PRIVACY AND COMPLIANCE
OF REGULATIONS
A data management system implemented in healthcare can make a difference in improving data protection and compliance:
SOLUTION
STRICT
ACCESS CONTROLS
The system ensures that sensitive patient data can only be viewed by authorized personnel, thereby protecting patient privacy.
SOLUTION
ENCRYPTION
SENSITIVE DATA
Encrypting patient information both in transit and at rest ensures that data remains inaccessible in the event of a potential security incident.
SOLUTION
INTEGRATION OF COMPLIANCE MODULES
The system integrates modules that automatically monitor compliance with legal regulations such as HIPAA in the USA or the GDPR in the EU.
ADVANTAGE
PROTECTION AGAINST
DATA BREACHES
Implementing best practice security measures reduces the risk of data leaks and cyberattacks.
ADVANTAGE
AVOIDANCE
OF PENALTIES
Strict compliance with data protection laws prevents costly penalties and protects the institution's reputation.
ADVANTAGE
TRUST OF THE
PATIENTS
A robust data protection system strengthens patients' trust in the healthcare facility and promotes willingness to share data for treatment.
ADVANTAGE
IMPROVE THE
RISK MANAGEMENT
Regular reviews and updates of the system with regard to current data protection regulations improve the organization's risk management.
OUR KEY FEATURES.
YOUR INDIVIDUAL SOLUTION.
We offer a variety of functionalities that are just waiting to be put together for your individual use. Take advantage of our flexibility in building data models and taking your very individual processes into account. Experience with us, without much programming,
how we can get the best potential out of your data!
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Classification manager
ableX's Classification Manager is a powerful tool that allows users to automatically categorize and organize their data. It uses algorithms and predefined rules to organize data into structured groups, enabling systematic analysis and easier discovery of information. Users can define their own categories tailored to their specific requirements and processes, creating a personalized data structure. This feature supports compliance with data standards, facilitates reporting, and improves the overall efficiency of data management by automating sorting of large data sets, saving time and increasing accuracy.
DQR Editor
The "DQR Editor" (Data Quality Rules Editor) is a specialized feature within ableX that allows users to implement detailed data quality guidelines and precisely control their application. This tool provides a user-friendly interface to set specific parameters for data validation, such as format checks, value range restrictions, and dependency rules between data fields. The editor allows these rules to be applied to records to identify and correct inconsistencies, duplicates and errors. This allows organizations to proactively manage and continually improve the quality of their data, resulting in trustworthy data and informed business decisions.
Data field mapping
The "Datafield Mapping" feature in ableX is a critical tool that gives users the ability to meaningfully map data fields from a variety of data sources. This feature creates compatibility between heterogeneous data formats, which is essential for synchronizing information across different systems and platforms. With data field mapping, corresponding data fields are identified and linked, which creates a homogeneous data view. This is particularly advantageous when data from different systems such as CRM, ERP or external third-party databases need to be consolidated. It plays a central role in data migration, data import or data merging, for example by ensuring that 'customer number' in one database is correctly linked to 'client ID' in the other.
Referencing
The "Referencing" feature in ableX is a crucial tool for structuring and meaningfully connecting database content. It allows users to create unique references between records that serve as references. These references are essential for establishing relationships between different data elements, such as between customer and order data in a sales database. Referencing is also important when importing and exporting data between different systems, as it helps ensure the correct mapping between different fields Ensuring data sources. It plays a central role in ensuring data quality, especially in complex systems where the accuracy and reliability of information is critical for operational decisions, reporting and analytics.
