Designing Data Services
Summary
Cross-disciplinary collaboration is key to tackling large scale change in hypertension rates (Margins of Victory) in underserved communities (Innovation at the Margins). Low income minoritized populations have shown to have a high prevalence of hypertension but a low treatment rate . There are many factors that play a role in these statistics many of them which are historical and systemic. In order to design a hypertension study for these populations, co-design methods that emphasize collective good must be employed by a comprehensive team. Our process to build this study focused on sharing power with members of the community to decentralize the designer and build design capability with the participants. We prioritized building relationships to combat mistrust of healthcare professionals and address difficult topics like social determinants of health (healthcare access, housing challenges, employment, etc) – both key factors in high hypertension rates. This presentation will bring together the collaborative team that built the Pressure Check study. First, a Yale cardiologist who is an expert in this space and acknowledges the influence and perspective that the design process can provide. The second speaker is a design research and strategy professional who defined an inclusive and relational protocol that tapped into the deepest needs of the study community and translated them into the study materials. The third, is a visual designer who incorporated the learnings into patient education and study tools to overcome deeply ingrained perspectives on healthcare. This team and the outputs demonstrate how critical it is to have a team that brings in shared and lived experiences into service design.
Key Insights
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Lack of interoperability between healthcare IT systems causes delays and disrupted patient care, as seen in John’s genomic test example.
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Genomics England moved from a research project to an integrated platform supporting NHS routine care with genomic data.
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Modular data services using common data standards enable flexible, reusable technical components for multiple healthcare applications.
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Service designers at Genomics England work alongside engineers and bioinformaticians early to ensure technical infrastructure serves real-world needs.
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Service maps help identify data transformation patterns to create standalone data service modules usable across different use cases.
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Designing data services focuses on developers as primary users, enabling them to build clinician-facing services like cascade testing or trial selection.
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Comprehensive documentation, developer tooling, and support channels are critical to developer adoption of data services.
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Framing data services through patient and clinician perspectives helps stakeholders make informed decisions and fosters broader inclusion.
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Service design applied at the technical data layer can have exponential impact by aligning infrastructure with business objectives and user needs.
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Collaboration and curiosity enable service designers to overcome intimidation by technical layers and build shared language with developers.
Notable Quotes
"The lack of consistency between healthcare IT systems causes critical information delays and interrupted care."
"Data standards are like selecting English as the common language, even if systems natively speak Portuguese or Spanish."
"Service designers embedded in leadership can preempt strategic directions and influence technical projects early."
"We are designing data services for developers, not final clinician-facing experiences."
"APIs need to provide capabilities like verifying patient identity to ensure data access is accurate and secure."
"Imagine data capabilities as Lego bricks versus a box set with instructions to build specific models."
"Developer experience hinges on clear documentation, sandboxes, sample data, and responsive support."
"Speculative use cases connect technical components to human impact and help prioritize work into slices of value."
"Don't shy away from technical conversations; service designers should map data journeys like user journeys."
"The impact of service design at the data service level is exponential, making infrastructure more human scale."
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