Sensemaking Through Making: Developing Clinical Domain Knowledge by Crafting Synthetic Datasets and Prototyping System Architectures

TL;DR

This paper presents a making-oriented approach for designers to understand complex healthcare systems by crafting synthetic datasets and prototyping, enabling sensemaking despite limited access to real-world data and systems.

Contribution

It introduces a novel process combining observation, synthetic data creation, and prototyping to facilitate healthcare domain understanding for designers.

Findings

Synthetic datasets aid in understanding healthcare data complexities

Prototyping helps balance system realism and abstraction

Hands-on data interaction supports designer sensemaking

Abstract

Designers have ample opportunities to impact the healthcare domain. However, hospitals are often closed ecosystems that pose challenges in engaging clinical stakeholders, developing domain knowledge, and accessing relevant systems and data. In this paper, we introduce a making-oriented approach to help designers understand the intricacies of their target healthcare context. Using Remote Patient Monitoring (RPM) as a case study, we explore how manually crafting synthetic datasets based on real-world observations enables designers to learn about complex data-driven healthcare systems. Our process involves observing and modeling the real-world RPM context, crafting synthetic datasets, and iteratively prototyping a simplified RPM system that balances contextual richness and intentional abstraction. Through this iterative process of sensemaking through making, designers can still develop context familiarity when direct access to the actual healthcare system is limited. Our approach emphasizes the value of hands-on interaction with data structures to support designers in understanding opaque healthcare systems.