Secure data access for external parties

Our solutions for anonymisation, pseudonymisation and governance can help you avoid a broad range of risks and difficulties.

New technologies are creating unprecedented opportunities in healthcare, helping to speed up the development of more targeted medicines, to make diagnoses, to optimise clinical care paths, and much more. But to reap the benefits, enormous amounts of clinical data must be collected and exchanged.

Governments also need more and more data, to develop coherent health policies. And there are numerous situations in which hospitals must provide data to external parties, including other healthcare institutions and patients.

This personal, patient data is highly sensitive, so it is critical to avoid any problems related to privacy or data security. Anonymisation and pseudonymisation can be key techniques for reducing the risks.

Let us handle it

Anonymising and/or pseudonymising data places a lot of demands on your facility, both technically and administratively. Time-consuming and complex processes require a variety of approaches, depending on the type of document or specialty.

Amaron offers a broad range of products and services to help you manage this procedure and enable secure access to medical data.

Our robust algorithms allow you to anonymise or pseudonymise data with minimal effort, regardless of whether the data is structured or non-structured.
We support you to manage the data exchange (or governance) process—from the request to the completion of the project—entirely in accordance with HIPAA recommendations.
And we can assist you to ensure the carefree exchange of data with colleagues in other hospitals as well as with patients.

Frequently asked questions

Which application areas can Amaron solutions support?

We offer interfaces for a wide variety of applications:

Application area	Type patiëntendata	Uitwisseling met
Scientific research/ Clinical studies	Anonymised data	Registries such HealthData.be and the Belgian Cancer Register Pharmaceutical industry
Diagnostics (AI) and data exploitation	Pseudonymised data	Suppliers of AI services, such as HeartFlow, Icometrix, Zimmer, LynxCare, Awell, IQVIA, Cascador etc.
Making data (administrative and medical) centrally available to: the government other care providers (hospitals, laboratories, general practitioners, home care, etc.) suppliers of healthcare applications	Relevant data by name	ehealth platforms, such as the eHealth initiative of the Belgian Government (eBirth, Recip-e, etc.), COVID platforms, etc. Hospital care portal
Communication with patients	Relevant data by name	Patient portal PREM & PROM Health apps

Which components does the Amaron solution provide?

Pseudonymisation:
Our robust algorithms enable you to pseudonymise structured and unstructured data with minimal effort.Importantly, patients receive a different pseudo-ID for each external party. This prevents data from being linked in the event of a data leak.
In addition to an API, we also provide a screen (UI) that the physician or another party can use to search for a patient with a pseudo-ID, in order to provide additional information to the external party.
Anonymisation:
With our algorithms, you can quickly and securely anonymise patient data, then export it to government agencies, pharmaceutical companies or other organisations that use it for scientific research.
Governance:
In addition to the actual data anonymisation and pseudonymisation, we can also set up a governance layer, including the approval of the hospital’s Ethics Committee or DPO, to streamline data exchange. This service comes with an easy-to-use user interface.
Interfaces with external parties:
We can establish an interface for each external vendor or agency, using web services.
Connectivity across hospital systems:
You can also turn to us to connect the various sub-systems within your hospital (HIS, EPR, RIS, LIS, PACS etc.).

What is the difference between anonymised and pseudonymised data?

In the care sector, medical research relies on anonymous data. This data is also used as statistical input for developing healthcare policies. A typical example of this is the anonymised data that the Belgian healthcare institutions provide to Sciensano/Healthdata for epidemiological monitoring.

When you anonymise data, it is no longer possible to trace the person who is the source of the data. However, there is still some risk of identification. For example, it would not be difficult to use the date of birth of a 100-year-old patient to uncover their identity.

Combining two (or more) data sets may create some risk of identification. It is always good practice to carefully consider, in advance, which and how much data you will exchange, even if it is anonymised.

In certain situations, however, you may need to make data available to a third party, but then want to enable re-identification afterwards under strict conditions. Here, anonymisation is not an option.

One example could be radiology images that you have analysed in the cloud using an AI algorithm for triage or other purposes. Or an external algorithm that uses patient data to calculate which components are needed to perform a knee replacement. Or text and unstructured reports that you make available to a software application that processes and analyses the data in order to optimise care paths.

In order to share medical data safely and responsibly in such situations, you can pseudonymise it. This security measure involves deleting any personal data that can be traced back to the patient (name, date of birth, patient number, etc.) and/or replacing it. For example, you might replace date of birth with age, and municipality with region. The data is then linked to a code that can only be used in the hospital to identify the patient.

How does Amaron help hospitals to share data?

Amaron is the market leader and a trusted partner in Belgium in the field of connectivity between various subsystems within hospitals. For example, electronic patient records that retrieve information about patient movements and appointments from the hospital information system, or that exchange orders and results with laboratory information and medical imaging platforms etc. In the Netherlands and France too, more and more hospitals and service providers in the healthcare sector are seeing the advantages of Amaron.

Why Amaron?

KENNIS & EXPERTISE

Je hebt met Amaron een partner die doorheen de jaren bijzonder veel expertise en kennis heeft opgebouwd inzake interoperabiliteit en procesondersteuning. De veilige uitwisseling van data – zowel intern als extern – is nu eenmaal waar we goed in zijn.

CORRECTE AFSPRAKEN

Je kunt erop rekenen dat enkel de strikt noodzakelijke data worden gedeeld. We maken hierover de juiste afspraken met het ziekenhuis en alle andere betrokken partijen.

INZICHT

Alles verloopt transparant. De Amaron-tools geven je inzicht in de diverse datastromen. Een eventuele afwijking wordt direct gesignaleerd zodat je indien nodig onmiddellijk actie kunt ondernemen.

CONTROLE

Jij behoudt de controle en blijft de eigenaar van alle data. Samen met jou doen we er alles aan om te verhinderen dat de data worden gebruikt voor onrechtmatige doeleinden.

GOVERNANCE

Amaron ondersteunt je niet alleen bij het technische aspect van de ontsluiting van data, maar helpt je ook het administratieve proces op het gebied van governance een stuk lichter te maken.

We staan pas aan het begin van de mogelijkheden. Nieuwe toepassingen en de data die ze genereren, kunnen ons helpen om meer in te zetten op preventie en om het ziekteverloop beter te voorspellen. Die informatie laat ons toe om sneller en gerichter in te grijpen wat de zorgkwaliteit ten goede komt.

Data spelen eveneens een rol bij het operationeel management en administratieve vereenvoudiging. We zullen er ook op grotere schaal gebruik van moeten maken, willen we de zorg betaalbaar houden.

Tip: Veilig data ontsluiten, hoe begin je eraan?

Wanneer je data deelt met externe partijen, definieer dan als eerste stap duidelijk wat de precieze scope is.
Met dit doel voor ogen bepaal je welke informatie je beschikbaar maakt en over welke periode het gaat. Beperk de data die je vrijgeeft tot het absolute minimum.
Evalueer het proces op gezette tijdstippen en stuur zo nodig bij.