I often get questions about the difference between user needs and requirements. Understanding this distinction is crucial for successfully bringing a software as a medical device (SaMD) to market. In this article, we'll dive into frequently asked questions, best practices, and examples to clarify the concepts of user needs and requirements.
Q: What's the difference between a user need and a requirement?
A: While related, user needs and requirements serve different purposes:
while there are a ton of nuances a simple rule of thumb is requirements must start with “software must” and user needs must start with “user needs to”
Q: Why is it important to distinguish between user needs and requirements?
A: Separating user needs from requirements allows you to:
Q: Who is responsible for defining user needs and requirements?
A: Defining user needs often involves input from end-users, clinical stakeholders, and the marketing team. Requirements are typically written by the product managers and engineers responsible for development, with input from clinical experts to ensure medical relevance and regulatory compliance.
Consider this scenario: You're developing an AI-based tool to automatically detect lung nodules on CT scans. Let's look at some best practices for defining user needs and requirements.
Start by understanding the problem from the users' perspective:
Notice each statement focuses on the user's goals, not the technical implementation.
Note that while the rest of the industry uses “shall”, I prefer “must” because it is clearer and more modern language.
Next, translate the user needs into clear, verifiable requirements:
Each requirement is specific, measurable, and linked to a user need.
Some other tips:
Defining clear user needs and requirements is a critical first step in developing successful AI/ML software for healthcare. User needs keep your efforts laser-focused on solving real problems for your clinical users. Requirements ensure you build a product that meets those needs in a robust, verifiable way. By understanding the distinction and interplay between the two, you'll be well on your way to creating SaMD that make a real difference in the practice of medicine.
Of course, this is just the tip of the iceberg when it comes to building SaMD that's clinically valuable and regulatory compliant. From data management to algorithm design to quality assurance, there are many other factors to consider. If you need expert guidance navigating the complex landscape of SaMD feel free to reach out. I'm always happy to share my experience and insights to help bring these transformative technologies to patients and providers.