Modern pulmonary function labs are moving away from rigid, step-by-step protocols and toward intelligent, event-driven workflows that respond dynamically to what is actually happening in the lab. Instead of following a fixed checklist regardless of context, today's best-performing labs use conditional logic to route tasks, trigger actions, and adapt processes based on real-time inputs. This shift reduces errors, cuts delays, and frees respiratory scientists to focus on clinical judgment rather than administrative choreography.

TL;DR

• Static protocols treat every patient and every result the same. Event-driven workflows do not.

• Conditional logic allows lab systems to automatically route, escalate, or adapt based on specific triggers.

• This approach is well-established in IT operations and industrial automation, and is now reaching clinical physiology labs.

• Switching to event-driven workflow design does not require rebuilding from scratch. Modern platforms can layer this logic onto existing processes.

• Rezibase is built with this philosophy, enabling respiratory and sleep labs to automate intelligently rather than manually repeat.

What Is the Difference Between a Static Protocol and an Event-Driven Workflow?

A static protocol is a fixed sequence of steps that runs the same way every time, regardless of what the data shows or what has changed in the environment. A technician follows step one, then step two, then step three. There is no branching. There is no "if this, then that."

An event-driven workflow, by contrast, is triggered by something that happens. An abnormal result, a patient no-show, a referral arriving outside business hours. The system detects the event and responds accordingly, routing the next action based on predefined conditional logic.

According to Red Hat's resource on event-driven automation for IT operations, this approach is defined as "the process of responding automatically to changing conditions in an IT environment to help resolve issues faster and reduce routine, repetitive tasks." The same principle applies directly to clinical lab environments.

Why Do Static Protocols Fail in High-Volume Respiratory Labs?

Static protocols were designed for predictability. But pulmonary function labs are not predictable environments. Patient conditions vary. Equipment availability changes. Referral volumes spike. Results fall outside expected ranges.

When a static protocol meets an unexpected situation, one of two things happens: a human intervenes manually, or the process stalls. Both outcomes create inefficiency and clinical risk.

Key failure points of static protocols in respiratory labs:

• No branching for abnormal results: A static checklist does not automatically escalate a critically low FEV1 or flag an unexpected bronchodilator response.

• No response to scheduling disruptions: A patient cancellation does not trigger waitlist management or rebooking without manual action.

• No adaptive reporting: Every report follows the same template, even when the clinical picture calls for a different structure.

• Double data entry: Without event-driven import logic, data moves between systems manually, introducing transcription errors.

How Does Conditional Logic Work in a Lab Workflow Context?

Conditional logic is the "if this, then that" engine behind event-driven workflows. It evaluates a condition and executes a specific action based on whether that condition is true or false.

According to MindStudio's guide on building agentic workflows, conditional logic and branching paths allow systems to handle complex, multi-step decisions without human intervention at every junction. Applied to a respiratory lab, this might look like:

As Ademero's workflow automation best practices guide notes, "event-driven automation responds instantly to business events, eliminating delays between when something happens and when action is taken." In a lab context, that delay reduction can directly affect patient care timelines.

What Does Research Say About Event-Triggered Control Systems?

The academic case for event-driven systems is well established outside of healthcare and is beginning to inform clinical workflow design.

A 2025 paper published in Scientific Reports by W. Dong explored event-triggered fuzzy neural-network PID control for nonlinear gas-blending processes. The paper introduced an event-triggered mechanism into concentration control, finding that this approach could manage complex, variable conditions more effectively than fixed-interval control methods. While this research focuses on industrial gas processes rather than clinical workflows, the underlying principle is directly relevant: systems that respond to events outperform systems that operate on fixed schedules when the environment is variable.

Similarly, a 2023 paper by C. De Persis published in IEEE Transactions presented a data-based approach to designing event-triggered state-feedback controllers for unknown continuous-time linear systems. The research, cited by 81 subsequent papers, demonstrated that event-triggered designs reduce unnecessary processing while maintaining system responsiveness. The pattern is consistent: event-driven logic is more efficient than static, time-based logic when inputs are unpredictable.

How Should a Respiratory Lab Begin Transitioning to Event-Driven Workflows?

Transitioning does not mean discarding everything and starting over. It means identifying the highest-friction points in your current workflow and asking: what event should trigger this action, and what condition should determine which action is taken?

A practical starting framework:

1. Map your current workflow end to end, from referral receipt to report delivery.

2. Identify manual handoffs where a human is simply passing information from one place to another.

3. Define trigger events for each handoff. What causes this step to begin?

4. Write conditional rules for each trigger. What conditions change the outcome?

5. Select a platform that can execute those rules without requiring custom development for every scenario.

6. Test with a single workflow before scaling. Waitlist management or referral routing are good starting points.

According to MyShyft's guide on conditional workflow logic, event-driven architecture should "design workflows that respond instantly to triggering events such as employee call-outs, unexpected demand spikes, or equipment" changes. The same logic applies when a spirometry device goes offline or a scientist calls in sick.

How Does Rezibase Support Event-Driven Workflow Design?

Rezibase was built by respiratory scientists who understood that lab workflows are not linear. The platform's architecture reflects this. Its Magic Import function, for example, is an event-driven tool: when device data arrives, the system automatically extracts discrete data including flow-volume loops, without manual re-entry. The event is the data arriving. The action is automated extraction and population.

Rezibase's admin modules handle referrals, waitlist management, bookings, and rostering in ways that respond to what is actually happening in the lab, rather than requiring scientists to manually push information between systems. Its integration with Patient Administration Systems, EMR platforms, and Electronic Orders Systems means that events in one system can trigger actions in Rezibase, and vice versa.

Frequently Asked Questions

Does event-driven workflow design require custom software development?
Not necessarily. Modern platforms like Rezibase include configurable logic that labs can tailor without writing code.

Is this approach suitable for smaller labs?
Yes. Even a two-scientist lab benefits from automated referral routing and result flagging. The scale of automation adjusts to the size of the operation.

How does conditional logic reduce clinical risk?
By eliminating manual handoffs, it removes the opportunity for transcription errors and missed escalations.

Can existing workflows be migrated to an event-driven platform?
Yes. Most migrations involve mapping current processes and configuring the new system to replicate and improve them. Rezibase is designed to make this transition straightforward.

Does Rezibase work with equipment from multiple manufacturers?
Yes. Rezibase is vendor-neutral and manufacturer-agnostic, importing data from any device type.

What happens to historical data during a transition?
Data migration to Rezibase is a structured, supported process designed to be manageable and low-disruption for lab teams.

Is cloud-based workflow automation secure for patient data?
Rezibase is a cloud-based SaaS platform built for clinical environments, with enterprise-grade deployment options available for hospitals with specific requirements.

About Rezibase

Rezibase is Australia's most advanced cloud-based respiratory and sleep reporting platform, designed by respiratory scientists for respiratory scientists. Trusted by over 35 sites including NHS and NSW Health, Rezibase supports the full patient lifecycle from referral to report with no vendor lock-in, no local servers, and no unnecessary complexity. Learn more at rezibase.com.

References

• Red Hat. Event-driven automation for IT Ops. https://www.redhat.com/en/resources/event-driven-automation-it-ops

• Ademero. Workflow Automation Best Practices Guide. https://www.ademero.com/blog/workflow-automation-best-practices

• MindStudio. How to Build Agentic Workflows with Conditional Logic and Branching. https://www.mindstudio.ai/blog/build-agentic-workflows-conditional-logic-branching

• MyShyft. Automate Complex Scheduling With Conditional Workflow Logic. https://www.myshyft.com/blog/conditional-workflow-logic/

• Scientific Reports. Event-triggered fuzzy neural-network PID control for nonlinear gas-blending processes. https://www.nature.com/articles/s41598-025-23998-6

• IEEE Xplore. Data-based event-triggered state-feedback controllers (De Persis, 2023). https://ieeexplore.ieee.org/iel7/9/10541101/10323524.pdf