How to support trustworthy data sharing: Checklist

Setting up and supporting trustworthy data sharing systems is a complex process. Here is a checklist that will help you consider all of the important elements as you embark on a healthcare project that will be collecting, using or sharing data, including:

• Defining the data to be collected, used and shared

• Mapping the health data ecosystem

• Align data use with legislation, regulations, and cultural values

• Managing risk around personal data

• Setting up successful data sharing partnerships

• Making sure data is interoperable

• Selecting the most appropriate data sharing methods

1. Define the data to be collected, used and shared

Establishing strong data governance within your project can create efficiencies, foster collaboration, build trust, optimise resource use, and enhance research. To get started, it is useful to conduct an inventory of the data assets and infrastructure you will draw on.

Key actions to take:

• Define the data you will be collecting, using and sharing

• Define who will be involved and what role they will play

• Assess data policies and processes related to this assets

• Identify data standards and data models being used (or planned) to access, use and share this data

2. Map the health data ecosystem

Throughout a data governance project, you will need to engage with various people and organisations and enlist their support. It can be helpful to visualise this to consider priority relationships to build.

Key actions to take:

• Map the current state of the health data ecosystem: who are the people and organisations and where are the current data and value exchanges between them?

• Map the desired state: how will relationships, data and value exchange look when the data ecosystem is matured in the way you are working towards?

3. Consider legislation, regulations, and cultural values for sharing health data

As a health data governance project leader, you will need to make sure all data being accessed, used and prepared for sharing is permitted under data privacy, intellectual p[roperty, and other legislation. Data use should also match community expectations and norms related to societal values around the use and sharing of health data.

Key actions to take:

• Consider the legal, regulatory and policy context

4. Manage risks around personal data

If the data assets you plan to collect, use and share contain personal data you will need to consider how to maximise its use while protecting the rights of individuals and avoiding harmful impacts.There are particular concerns that need to be addressed when handling health data, as it often contains personal and sensitive information about individuals. The play on identifying and managing risks with personal data will help you to do this.

Key actions to take:

• Assess whether the data you are using has personally identifiable information

• Identify data protection officers in your organisation with expertise on how to manage personal data

• Assess the potential negative impacts from using health data

• Think of actions to minimise the risk of personal data exposure (e.g. through techniques like data minimisation and data anonymisation)

5. Set up successful data sharing partnerships

When deciding on sharing data with other people and organisations in the health data ecosystem, a variety of agreements and approaches can be used, depending on the nature of the relationship.

Key actions to take:

• Define what you want to achieve by sharing data

• Identify which principles will guide data sharing

• Define how you will communicate with data sharing partners

6. Make sure data is interoperable

To enable greater reuse and sharing of data, it is important to ensure that data is integrated and can be exchanged through systems and platforms. This means that, when data is collected and managed, it is best if it is organised in a way that enables interoperability. Internally, this can help make better use of data in various contexts, but when preparing data for potential external use, it becomes essential.

Key actions to take:

• Identify standards and data models that have been used to define the dataset and data fields

• If data is not standardised, evaluate which techniques could be used to standardise data to a single format

7. Select the most appropriate data sharing methods

Finally, with this understanding of the ecosystem, the data, and the partnership arrangements, it is possible to select the best methods for establishing data sharing agreements and choose the technology platforms that can facilitate data sharing.

Key actions to take:

• Identify the data sharing partnership already in place

• Assess what types of data agreements support this type of partnership

• Evaluate whether you can use a standard agreement or do you need to create a bespoke one

• Identify the platform in which data will be stored and made available

• Define what types of functionalities data partners will need for accessing and using the shared data