Designing with data using a life-course approach

Using examples from our work at NHS England, the national custodian for health data, we explore the advantages and limitations of treating data as users and following their journey through time, namely a ‘life-course’ approach, when designing services for data-focused organisations.

We conclude by discussing how this approach might be useful beyond mapping and understanding data as complex entities and provide a framework that can help us apply the lens of ethical design when working with machine-intelligence and automated decision-making.

---
One of the cornerstones of user-centred design is the principle of centring thoughts and artefacts around people instead of things. We write user needs, for example, by defining a person using our product or service and by using verbs that represent their tasks, goals, and ambitions.

When crafting user needs, we carefully avoid introducing things as objects of desire to prevent our thoughts being driven by prescriptive solutions instead of a problem that can be creatively solved in multiple ways. People need to do something, to achieve a goal, they do not need the mere means to achieve it. Verbs are in, nouns are out.

This approach shaped our thinking of what we did as an organisation through the lens of what journey the data experienced as much as of the people who interacted with it. It has informed things like organisational thinking, influenced our operating model, and shaped discussions and communication strategies.

Participant Takeaways:

• Ways of conceptualising data that cater to their complexity as processes rather than things, with its advantages and limitations.
• Examples of how user-centred approaches, generally geared towards prioritising people, has been used to prioritise things Insights about health data and the complexities of creating, managing and using them.
• Exposure to a possible framework that can helps us think of ethical design and design-for-good when dealing with automated decision-making and machine intelligence services and products.

Themes:
Metrics, data, ROI, health, design approach, ethical design, automation.