How to Gather Clinical Requirements: A Practical Guide for Digital Health Projects

Clinical requirements are the backbone of every safe, usable and effective digital health solution. Whether you’re building a clinical dashboard, redesigning a workflow, evaluating a digital product or developing a new health tech tool, the quality of your clinical requirements determines the quality of your outcome.

Yet in many Australian healthcare organisations, requirements gathering is rushed, incomplete or driven by assumptions rather than real clinical needs. This results in systems that don’t fit workflows, dashboards clinicians don’t find useful, and products that fail to deliver value.

This guide breaks down a practical, clinician‑led approach to gathering clinical requirements that actually work.

Why Clinical Requirements Matter

Digital health and clinical analytics projects succeed or fail based on how well they reflect real clinical practice.

Good clinical requirements:

• Reduce clinical risk
• Improve usability and adoption
• Ensure workflows are safe and efficient
• Prevent costly redesigns later
• Strengthen governance and compliance
• Align digital tools with real‑world decision‑making

Without clear requirements, teams end up building what they think clinicians need — not what they actually need.

Step 1: Start With the Clinical Problem, Not the Solution

Many projects begin with a predetermined solution (“We need a dashboard” or “We need a new form”).
Instead, start with the clinical problem.

Ask:

• What clinical decision or workflow is breaking?
• What risk or inefficiency are we trying to reduce?
• What outcome should improve if we get this right?

This anchors the project in real clinical value.

Step 2: Identify the Right Clinical Stakeholders

Clinical requirements must come from the people who actually do the work and will use the solution. This usually includes:

• Frontline clinicians
• Senior clinicians or clinical leads
• Administrative staff involved in the workflow
• Quality and safety teams
• Data or BI teams (for feasibility)

Avoid relying solely on managers or project sponsors — they often have a different view of the workflow.

Step 3: Map the Current Digital Clinical Workflows

Before gathering requirements, you need to understand how things work today.

Document:

• Steps in the workflow
• Digital systems used
• Roles involved
• Decision points
• Pain points and risks
• Workarounds and shadow processes
• Data captured (or missing)

This creates a shared understanding and reveals hidden requirements.

Step 4: Define the Clinical Questions

Every digital tool should answer specific clinical questions.

Examples:

• “Which patients are at highest risk of falls today?”
• “Which patients have infectious diseases in my hospital?”
• “Where are delays occurring in the discharge process?”
  

These questions become the backbone of your requirements.

Step 5: Translate Clinical Needs Into Requirements

Now convert clinical insights into clear, actionable requirements.

Functional requirements 

What the system must do.
Examples:

• Display real‑time patient risk scores
• Allow clinicians to filter by ward or specialty
• Data needs to be as recent as possible

Non‑functional requirements

How the system must behave.
Examples:

• Easily add and remove users
• Use agreed colour scheme
• Refresh automatically

Safety requirements

Clinical safety is non‑negotiable.
Examples:

• Highlight abnormal values clearly
• Describe any biases in the data
• Advise in clinical decision support, not a clinical decision maker
   

Step 6: Validate Requirements With Clinicians

Validation prevents misunderstandings and incorrect assumptions.

Use:

• Walkthroughs
• Prototypes
• Mockups
• User testing sessions
  

Ask clinicians:

• Does this reflect your workflow?
• Would this help you make decisions?
• What’s missing?
• What could cause risk?
  

This step is where trust is built.

Step 7: Prioritise Requirements

Not everything can be delivered at once.
Prioritise based on:

• Clinical risk
• Workflow impact
  
• Feasibility
• Dependencies
• Value to end users

A simple “must‑have / should‑have / could‑have” model works well.

Step 8: Maintain Requirements Over Time

Clinical requirements are not static. Workflows change. Data changes. Policies change.

Establish:

• Governance
• Review cycles
• Change control
• Clinical ownership
  

This ensures the system stays safe and relevant.

Common Mistakes to Avoid

• Jumping straight to solutions
• Gathering requirements from the wrong people
• Ignoring workflow mapping
• Focusing only on data, not decisions
• Skipping validation
• Treating requirements as one‑off tasks

Avoid these, and your digital projects will run smoother and deliver more value.

Conclusion

Gathering clinical requirements is one of the most important — and most overlooked — steps in digital health. When done well, it ensures digital tools are safe, usable and aligned with real clinical practice.

When done poorly, it leads to frustration, risk and wasted investment.

A structured, clinician‑led approach is the difference between digital systems that work and digital systems that fail.