# How do medical institutions co-create artificial intelligence solutions with commercial startups?

## TL;DR

This paper explores how medical institutions and AI startups can work together to develop AI solutions for radiology that meet clinical needs and improve workflows.

## Contribution

The paper introduces a relational framework to monitor, assess, and guide co-creation processes between medical and technological parties.

## Key findings

- A co-creation framework helps identify distinct collaboration journeys with varying outcomes.
- The framework enables stakeholders to adjust their collaboration based on resourcing, adaptation, and reconfiguration.
- Active involvement of radiology professionals leads to more clinically relevant AI solutions.

## Abstract

As many radiology departments embark on adopting artificial intelligence (AI) solutions in their clinical practice, they face the challenge that commercial applications often do not fit with their needs. As a result, they engage in a co-creation process with technology companies to collaboratively develop and implement AI solutions. Despite its importance, the process of co-creating AI solutions is under-researched, particularly regarding the range of challenges that may occur and how medical and technological parties can monitor, assess, and guide their co-creation process through an effective collaboration framework.

Drawing on the multi-case study of three co-creation projects at an academic medical center in the Netherlands, we examine how co-creation processes happen through different scenarios, depending on the extent to which the two parties engage in “resourcing,” “adaptation,” and “reconfiguration.”

We offer a relational framework that helps involved parties monitor, assess, and guide their collaborations in co-creating AI solutions. The framework allows them to discover novel use-cases and reconsider their established assumptions and practices for developing AI solutions, also for redesigning their technological systems, clinical workflow, and their legal and organizational arrangements. Using the proposed framework, we identified distinct co-creation journeys with varying outcomes, which could be mapped onto the framework to diagnose, monitor, and guide collaborations toward desired results.

The outcomes of co-creation can vary widely. The proposed framework enables medical institutions and technology companies to assess challenges and make adjustments. It can assist in steering their collaboration toward desired goals.

Question
How can medical institutions and AI startups effectively co-create AI solutions for radiology, ensuring alignment with clinical needs while steering collaboration effectively?

Findings
This study provides a co-creation framework allowing assessment of project progress, stakeholder engagement, as well as guidelines for radiology departments to steer co-creation of AI.

Clinical relevance
By actively involving radiology professionals in AI co-creation, this study demonstrates how co-creation helps bridge the gap between clinical needs and AI development, leading to clinically relevant, user-friendly solutions that enhance the radiology workflow.