Business-driven validations for health and care data repositories with Better Advanced Validation Services

In the realm of health and care data management, ensuring accuracy, security, and compliance of data within repositories is of great importance. Validation services are instrumental in enforcing data integrity and compliance throughout the lifecycle of health and care data.

The importance of a validation layer in digital health platforms cannot be overstated, as it plays a critical role in validating and managing data before it reaches the repository. By implementing robust validation processes across repositories, organisations can enhance data quality, mitigate risks associated with incorrect or incomplete information, and ensure regulatory compliance in dynamic healthcare environments.

Understanding the depth of validation

In a typical setup, the data layer consists of several repositories, each catering to specific domains such as clinical data, operational data/demographics, workflows, and reporting metrics. To maintain consistency and validity across these repositories, a robust business-driven validation service becomes indispensable. This service not only ensures data quality but also improves clinical decision-making and, consequently, patient care outcomes. By integrating a validation layer, healthcare organisations can effectively enforce business validation rules, restrict access to unsupported resources, manage conditional requests, and modify request and response bodies, thus optimising the reliability and accuracy of their data. These services are organised into three layers of validation:

  • Layer 1: Semantic validation: Foundational in nature, this layer makes sure data complies with standardised models such as openEHR and FHIR, fostering interoperability and consistency across healthcare systems.
  • Layer 2: Access control: Moving beyond semantics, access control safeguards sensitive information, ensuring it is accessible only to authorised personnel or systems. This layer regulates data access based on privacy and security policies, thereby protecting sensitive information and ensuring compliance. Moreover, it protects data entry so that only authorised personnel can create or update data.
  • Layer 3: Business-driven validation: The most intricate layer revolves around business-specific rules and logic, validating data against operational and regulatory requirements unique to the healthcare sector. This includes clinical decisions, clinical protocols, adherence to quality metrics, and other related capabilities.

Together, these validation layers uphold data reliability, security, and interoperability, thus facilitating improved patient care outcomes and organisational efficiencies in healthcare.

Business-driven validation

Implementing business-driven validation rules in healthcare data management is essential for maintaining data integrity and providing accurate clinical information across diverse applications. Validating data within each repository enforces custom rules on data flowing in and out, ensuring consistency and reliability.

Let's consider how business-driven validation can be applied using a practical scenario, such as restricting diagnoses based on patient demographics. For example, in a healthcare application, we might want to enforce a rule that allows recording a diagnosis of "Type 2 Diabetes" only for patients aged 18 years or older. This validation process integrates specific checks into the data entry process, automatically verifying the patient's age against predefined criteria to ensure alignment with demographic profiles.

Integrating patient history is vital to prevent duplicate or inaccurate entries. The system can query stored medical histories to identify existing diagnoses, alerting users to potential duplications and maintaining data consistency.

Business-driven validation extends beyond demographics to include clinical data validation, making sure diagnoses align with medical histories and current conditions. Furthermore, leveraging external data sources through APIs enhances validation capabilities by integrating with national health databases or insurance records, guaranteeing comprehensive and accurate patient information.

Implementing business-driven validations with Better Advanced Validation Service

While our main products, EHR Server (openEHR Clinical Data Repository) and Demographics Server (FHIR-based Operational Data Repository) already validate data on ingress against the standards (openEHR reference model and FHIR resource definitions) and models (openEHR archetypes and templates and FHIR profiles and implementation guides), these validations often lack functionality in real-world projects, and no cross-validation can be done between different data points. Examples include taking other existing compositions into account when validating a new one, using demographic information to verify whether the new clinical information makes sense, consulting external services such as catalogues, workflow management systems, or non-openEHR clinical applications, and much more.

Better Advanced Validation Service is a central service for business rules validation on data ingestion. It installs as a gateway to actual repositories and applies validation to all incoming data. Our Validator Server uses validation scripts that can be written in a well-documented DSL (domain-specific language) and deployed to the project ecosystems. Validation rules are written in simple and easy to use validation scripts, managed through a REST API. They can be used to validate:

  • clinical data based on patient demographics (such as age, gender, etc.),

  • clinical data based on data already present in the patient history (existing conditions, vaccination iterations, etc.),

  • demographic data based on encounters, related persons, etc.,

  • clinical and demographic data based on national entitlement APIs,

  • any other validation case requiring data across services or from external APIs.

With an external and central validation service, business rules are no longer scattered acrossapplications where they are difficult to manage and control. This allows for complete control over the incoming data and validation of the most complex cases.


How it works and is used

The Validation Script Definition feature enables healthcare applications to create custom validation logic using Kotlin scripts. This feature ensures data accuracy and compliance by executing business rules against Electronic Health Record (EHR) data, FHIR resources, and remote APIs. The 'validate' method supports different types of data, such as single EHR entries, lists of EHR entries, and various FHIR resource types. Developers can query and validate data using specific tools ('withEhr', 'withFhirR4', 'withFhirR5', 'withRemoteApi') that interact with EHR, FHIR (R4 or R5), and remote APIs. These tools facilitate data management tasks, such as retrieving metadata, executing queries, handling compositions for EHR data, reading, searching, and managing FHIR resources, and remote server interactions. Additionally, they offer data extraction and conversion capabilities to ensure the data is in the required format.

Key takeaways

Implementing business-driven validation in healthcare applications offers several key benefits. First, it allows for customisable validation rules tailored to specific healthcare data scenarios, enabling the definition of complex rules that ensure data accuracy and relevance.

Second, it facilitates seamless integration with Electronic Health Records (EHRs), Fast Healthcare Interoperability Resources (FHIR) servers, and external APIs, allowing validation across diverse data sources to enhance data comprehensiveness.

Better Platform Validator Server includes customisable validation, allowing for the definition of complex rules tailored to healthcare data scenarios: data source integration, enabling interaction with EHRs, FHIR servers, and external APIs for validation, and error reporting, which efficiently handles and resolves data validation issues within healthcare applications.

Lastly, efficient error reporting capabilities enable the prompt identification and resolution of data validation issues within healthcare applications, ensuring data integrity and reliability throughout the system. These benefits collectively contribute to improved data quality and decision-making in healthcare settings, providing improved patient care outcomes and operational efficiency within healthcare systems.

In summary, Better Advanced Validation Service supports sophisticated validation logic within healthcare apps, enhancing data quality, compliance, and reliability across diverse data sources and APIs.

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