DATE: 12-11-2024 STATUS: FOR REVIEW

 

Open

Roles Health-RI ecosystem

Data holder

Data holder; is a collection of roles that make health data sources available to the Health-RI ecosystem in a consistent and standardized way.

• Data producer; produces, creates and manages the health data source on the basis of agreements and guidelines for, among other things, storage of data, ownership, intellectual property, terms of use, selection and retention. The data producer does this based on a data management plan and preferably with

  • Context information

  • Conditions

  • Coding and modeling according to unity of language

  • Quality and usability characteristics

  • Version control

For data sources, where the user does not have the basis to know personally sensitive information, the original health data is pseudonymized or anonymized.

• Data Preparator; separates, based on the data-centric principle, the original health data from the original application and prepares the original health data, where necessary, for multiple use (including for use for research and innovation) in a persistent data platform.

  • If the data producer has not made the data sufficiently FAIR, the Data Preparator will, where possible, further provide it with (additional)

    1. Coding (using the correct coding and modeling according to unit of language determined by the data governance committee) and context information,

    2. Terms of use according to the applicable data policy of the data holder,

    3. Review from the Terms of use service

    4. Quality and usability characteristics

    5. Where necessary, provided with version control

  • If the data producer has made the data sufficiently FAIR, the Data Preparator will implement the data-centric principle from a persistent data platform, which acts as a transport layer towards the data provider.

• Data provider; set up the delivery process of the dataset based on the terms of use of the Data Preparator and the target transformation. This includes:

  • Register and publish the metadata by a FAIR Data Point

  • Registering the used data repository (a FAIR data point) with a FAIR Data Point Registry

  • Handling data research request;

    1. Request from the Research data request service is received

    2. Application is tested against the terms of use of the Data Preparator

    3. Tested application will be assessed by Local review committee data providings

    4. Result assessment is returned to Research data request service

  • Receive (meta) data action request; requests can come from different data user roles on the (meta)data, such as

    1. Request metadata for data guide

    2. Request data for central analysis processing environment

    3. Request data for the benefit of the federated analysis operator on behalf of the applicant

  • Determine terms of use; an applicant registers with authentic identity, with an approved data research application. This is checked regarding the terms of use of the Data Preparator. It determines the conditions under which (purpose transformation, licensing, etc.) the requested data may be offered to the data user.

  • Execute (meta) data action; Data is offered according to certain terms of use, including any pseudonymization or minimization.

• Local review committee data providing:

  • Determines user conditions in advance for the provision of the original health data, preferably recorded with the data producer, or otherwise with the Data Preparator.

  • Performs local review of data research request for the original data source.

• Data archiver: Archiving data, in order to guarantee continuity of data provision in the event of potential termination of the original data source of a data producer.

• Federated analysis performer: Assignment of applicant federated analysis is carried out locally at data holder, by performing these actions:

  • Request action on (meta)data from data provider

  • Receive data from data provider within environment data holder

  • Calculate data using computing power within environment data holder

  • Return results calculation to applicant federated analysis.

     

Data user

Collection of roles that use health data from the Health-RI ecosystem for research and innovation.

• Researcher; can perform the following tasks within data user environment:

  • Identify and authenticate; Researcher registers and can log in with the local identification, authentication and authorization service of the data user environment.

  • Request to start research; With the Research data request service, the researcher asks the local review committee of the organization to which the researcher is affiliated whether research is allowed to start.

  • Prepare data management plan; From the start of research, researchers are facilitated to maintain a data management plan, with which the new research data and the research results are made suitable for reuse.

  • Generate new research data; The researcher can select and apply tools from the Tool provider, with which new research data can be created. The data creation tool thus becomes a data producer at a desired data holder.

  • Find and discover existing health data; Researchers can use the Health-RI (or similar) data guide to find and further discover existing health data for the research.

  • Request existing health data; With the Research data request service, the researcher can ask data providers(s) whether the researcher may use data from the relevant data holder(s) for the research

  • Executing feasibility study; The researcher can safely try out whether the data is suitable for the research

  • Collect data centrally; The researcher can collect data (from various sources, including self-generated research data) in a secure central analysis processing environment by

    • Request to submit to the data provider(s) to copy data to the secure central analysis processing environment in this request Refers researcher to the previously obtained consent of the existing health data process

      • Indicates to which secure central analysis processing environment should be copied

      • Data provider assesses request, addresses desired secure central analysis processing environment with the addressing service and copies the data to the secure central analysis processing environment

    • Optimize research data; The researcher can apply tools from the Tool provider in the secure central analysis processing environment to make the data more suitable for research

  • Configure analysis tooling; The researcher can use the Tool provider to apply tools in the secure central analysis processing environment to analyze the data.

  • Analysis; The researcher performs the analysis on the optimized collected health datasets in the secure central analysis processing environment with the configured analysis tools.

  • Request federated analysis; with Request federated analysis service, the researcher can commission the Federated analysis performer(s) to perform a local analysis calculation at the data holder and produce research results; The researcher receives tools from the Tool provider to further develop the research, which leads to reusable research results

  • Publish research results; The researcher receives tools from the Tool provider to publish research at the data holder of the organization, to which the researcher is affiliated.

  • Receiving support; The researcher can receive support on various aspects of conducting the research

• Innovator; Is an specific researcher who produces reusable research results and algorithms for data users who want to have simplified access to health data, such as healthcare professionals, policy makers and citizens. Tasks that an innovator performs are

  • Research;

  • Certify MDR;

  • Publish Algorithms ;

• Healthcare professional, policy maker, citizen
  In this role one has a:

  • Research facility; a specialized user interface with which healthcare professionals, policy makers and citizens can apply health data themselves, to form their own opinion.

  • Algorithms Facility; special form of applying health data, with which proven and MDR certified algorithms can be found and executed

• Local identification, authentication and authorization service; The data holder environment consists of various applications, services and sources. For the researcher, these work as an integrated whole. The local identification, authentication, and authorization service of a data user environment

  • Captures the authentic identity of the users, applications, services, and resources

  • Captures the authorization of the users on the applications, services, and resources

  • Respond to authorization requests from users to use applications, services, and resources.

• Local review committee launch research; The organization to which the researcher is affiliated has a review committee, that determines whether studies that affiliated researchers want to start can be assessed on ethical and legal grounds.

• Data guide; performs services that allow researchers to find existing health data, that can be used for the research, with the features

  • Acquire decentralized metadata; with Find and discover existing health data action, data guide requests the latest state from all FAIR Data Points that are registered in the FAIR Data Point Registry.

  • Publish metadata

  • Meta data traceability

• Tool provider;

  • Tools repository;

  • GovernTerms of use;

  • Govern Service Level Agreements;

  • Licensing;

  • Support;

  • Learning;

• Federated analysis coordinator; The federated analysis coordinator provides the tooling to submit the analysis question and ensures that the analysis question reaches the data holders and that the results are collected.

Generic features

The nodes from the Health-RI ecosystem use Generic features. Preferably, these Generic features are also used in healthcare itself (primary use).This promotes transparency and consistency of the application of these services and avoids unnecessary multiple costs for implementing and managing the features.

The following Generic features are provided to the nodes of the Health-RI ecosystem:

• Addressing; Generic feature, both for healthcare itself (primary use) and for research & innovation (secondary use), which indicates which parties participate in which functions and how to address them.

• Application overview; Generic feature, both for healthcare itself (primary use) and for research & innovation (secondary use), which provides an overview of who has done what with personal health data

• Central data provider review committee; Generic feature, both for healthcare itself (primary use) and for research & innovation (secondary use), responsible for:

  • Creating and managing generic terms of use

  • Testing (cross-source) data request for traceability of personal data

  • Keeping track of case law

• Data broker: Generic service responsible for:

  • Data storage for research datasets that are published for multiple studies from different institutions
    and optional for:

  • Organize Trusted third party

  • Ensure national cooperation agreements at study level / research project level

  • Facilitate Data Access Committee

  • Providing a service for pseudonymization of datasets across institutions

  • Key management

  • Secure processing agreements.

  • Facilitate/encourage data delivery in accordance with standards

  • Owner and director of rural architecture building blocks

• Data Governance Committee; Each disease-specific domain has its own processes with associated data; The data that occurs in almost all diseases is called the generic data. From the sunflower metaphor it can be said that in the heart of the sunflower is the generic data and the sunflower petals represent the different condition specific domains. Both for the care itself (primary use) and for research & innovation (secondary use) there should be a Data Governance Committee per sunflower leaf and the heart of the sunflower; they determine and manage:

  • Standardized treatment process and protocols

  • Minimal dataset with associated metadata set

  • Unity of language for the relevant dataset (coding and modeling); whereby the relevant data governance committee is the mouthpiece to the (international) standard holders to implement possible harmonization adjustments, in order to prevent quality loss in data transformation as much as possible.

  • FAIR metadata templates

  • Mapping definitions between different target groups within unit of language.

• FAIR Data Point Registry; Generic service where you can register FAIR Data Points to be included in a catalogue.

• Identity repositories; Different target groups use the Health-RI ecosystem. These different target groups each have specific roles and attributes. The NEN standard is currently looking at identification and authentication of healthcare professionals, which also faces the challenge that not all diverse groups of healthcare professionals fall under the UZI identification register. The Health-RI Foundation advocates a national approach or standardization of identity registers, in which the design of roles and attributes is looked at across domains and internationally. This also makes it easier to combine socio-economic information from ODISSEI with health data from the Health-RI ecosystem for prevention purposes. The target groups that we distinguish for the Health-RI ecosystem are:

  • Health care professionals

  • Researchers

  • Policymakers

  • Citizens

• Mapping service; Generic feature, both for healthcare itself (primary use) and for research & innovation (secondary use), which ensures that data is consistently translated between the different target groups of data holders and data users. In case of change in coding and modeling of standards within the unit of language, it is implemented once here.

• MDR Notified Body; Generic feature, both for healthcare itself (primary use) and for research & innovation (secondary use), which grants Medical Device Registry (MDR) certification.

• Pseudomizing service; Generic feature, both for healthcare itself (primary use) and for research & innovation (secondary use), in order to be able to combine data from a person or participant in a study across different sources (Data linking), there must be a Generic feature that consistently pseudonymizes data across organizations and manages keys, so that these keys can be applied across organizations for de-pseudonymization to be able to link data.

• Research data request service; Generic feature, specific for research & innovation (secondary use), responsible for:

  • Determining the identity and authenticity of the researcher

  • Determining permission to start research

  • Recording data research request and environment

  • Sending data research request

  • Administering data research request

• Secure Processing Environment: a secure processing environment meets the requirements of the Health-RI ecosystem. It can be used for analyses but also for data preparation (e.g. creating a multicenter dataset where data from multiple sources (jointly) needs to be processed to meet set standards before publishing/making it available. A secure processing environment provides the following services:

  • Processing facility

  • Providing secure data storage

  • Applying tools

  • Linking data from different sources

  • Performing analysis calculations

  • Cleaning up the secure processing environment according to agreements made or applicable

• System Administrator Health-RI; Is a Health-RI ecosystem specific Generic feature that provides services such as

  • Manage contract template repository; To prevent consistency and reinvention, proven real-world examples are centrally tracked and shared.

  • Authorization Policy;

  • Architecture governance; managing the Health-RI ecosystem architecture, through this Wiki with accompanying consultation cycle.

• Terms of Use service; Generic feature, both for healthcare itself (primary use) and for research & innovation (secondary use), which determines the preference of a citizen who is allowed to do what with the health data of the citizen concerned.