Qt for MedTech Pre- and Post-Market Surveillance

Industry Insights Blog Series

Roger Mazzella

Global Medical Industry Leader, Qt Group

Kimmo Leppälä

Director, Product Management, Qt Tooling

The growing prevalence of chronic diseases, the incorporation of digital technologies in healthcare, the emphasis on value-based care, and technological advancements collectively drive healthcare providers’ integration of remote patient monitoring (RPM).

Source: Gartner, Market Guide for Remote Patient Monitoring Solutions, Robert Potts, 10 February 2025. © Gartner, Inc. and/or its affiliates. All rights reserved.

In this new setting, the users of the medical technology become the most diverse, and to a large extent non-experts. For these reasons, the user experience has to be simple, intuitive, and responsive.

Read more about the importance of UI/UX in MedTech

Pre- and Post-Market Usability Requirements

In the tightly regulated healthcare sector, developers of digital health products, biosensors, and wearables face the challenge of meeting diverse global certifications and approvals. FDA’s primary guidance for usability is the 2016 document, “Applying Human Factors and Usability Engineering (HFE) to Medical Devices,” outlining the process for integrating HFE into device design and validation. Before a regulated Medtech device or application is allowed to be sold into the market, the following must be accomplished (pre-market):

1. Identify Intended Users, Use Environments, and Use Scenarios

2. Conduct Risk Analysis

3. Perform Design and Iterative Testing

4. Perform Summative Usability Testing (Validation)

5. Submit a Human Factors Engineering Report

Once a regulated medical product is on the market, the US and EU require post-market surveillance. Post-Market Surveillance (PMS) is a systematic process of monitoring and collecting data on the safety, performance, and effectiveness of a medical device after it has been placed on the market or put into use. PMS is required for as long as a medical device remains on the market in both the United States and the European Union and should drive continuous improvement to ensure that devices remain safe, effective, and compliant with regulatory requirements throughout their lifecycle. 

More on US & EU Regulations

Pre- and Post-Market Usability Studies: Methods and Best Practices

With such stringent international requirements for pre- and post-market usage monitoring, the question is “What methods and best practices should be followed when collecting usability data?”  

Supplementing traditional methods with real-time usage data provides more accurate usage information. However, obtaining such real-time device usage data has typically been the biggest challenge in both pre-market usability studies and post-market surveillance.

As per the Veeva Medtech article, TOSOH: Defining a Postmarket Surveillance Strategy to Drive Risk-Based Decisions

Collecting accurate, high-quality data remains a major PMS challenge. Traditional methods can fall short, producing inconsistent data that delays complaint investigations and hinders effective vigilance assessments. Manufacturers should focus on capturing more relevant and complete information to improve outcomes and enable better informed risk assessments.

Providing accurate, real-time usage data is exactly what Qt Insight Tracker does and in the next sections we'll see what type of data and how to integrate PMS into medical devices.

Turning Usage Data into Insight

Qt Insight Tracker uses an event-based model: clicks, screen navigations, workflow transitions and even custom application data can all be captured as events. But capturing is just the first step. The real value comes when routing these events through a data pipeline and making them visible to engineers, product managers, and compliance teams. By embedding device tracking directly into usage analytics:

1. Compliance teams gain continuous evidence that maintenance guidelines are being followed

2. Post-market surveillance reports can include real-world statistics on how devices are operated and serviced

3. Regulatory submissions can be backed by objective usage data, rather than assumptions or sparse reports

This approach transforms medical device tracking from a manual process into a continuous, data-driven compliance asset, helping manufacturers stay ahead of both maintenance issues and regulatory requirements.

From Events to Insights: Building the Pipeline

One straightforward way to achieve this is by deploying a Snowplow data pipeline to the cloud (AWS, GCP or Azure). With Terraform, one can set this up in a few hours. At a high level, here’s what gets deployed in AWS with the quickstart module:

• Collector: receives events from Qt Insight Tracker over HTTPS

• Iglu schema registry: ensures events follow your defined schema

• Enrichment: validates and processes events (adding context, optional geo info, etc.)

• Storage: PostgreSQL database (via RDS) or optionally a data lake in S3

• Visualization: AWS QuickSight dashboards for analysis

Image 1. Sample Analytics Pipeline with Snowplow and Amazon Services 

Image 1 - Learn More

Once this pipeline is in place, the data loop is complete:

• Engineers see where users struggle in real workflows

• Product managers get data-driven prioritization for improvements

• Compliance teams gain stronger evidence for FDA/EU post-market surveillance

• End-users ultimately get devices that are safer, easier to use, and more effective

With Qt Insight Tracker and a cloud data pipeline, real-world usability isn’t guesswork anymore; it’s measurable, visible, and actionable.

Visualizing Workflows with Diagrams

One powerful way to explore device usage is by visualizing state transitions in a Sankey diagram. In the example below, one can see how an infusion pump moves through different states—standby → configure → running → completed → standby.

The thickness of each flow represents how often users follow that path, making it easy to spot the most common workflows as well as less frequent, unexpected ones. Such diagrams can reveal:

• Whether users are following the intended workflow or skipping steps.

• If there are bottlenecks (e.g., devices stuck in “configure”).

• Patterns of premature termination (e.g., powerOff before “completed”).

This turns raw event data into actionable insight—engineers and PMs can instantly see where to focus improvements.

Tracking Consumables and Maintenance with Custom Data

Not all insights are about clicks and workflows. With Qt Insight Tracker, one can also capture custom application data that ties directly to device usage and maintenance. For example, in an infusion pump, one might want to know how many times a pump has been run before the consumables (like tubing or fluid) need replacement. By pushing a simple JSON payload with each run, the pipeline can parse this field and show it in QuickSight.

The table shows a run count per session, revealing how many times a particular device was operated. With this data in place, you can:

• Detect when a device is approaching its maintenance threshold

• Alert service teams proactively before consumables fail

• Track usage patterns per device to optimize replacement cycles

• Provide compliance evidence that consumables are maintained according to manufacturer or regulatory guidelines

If you need real-time usage analytics to enhance your medical products constantly or to achieve regulatory compliance more easily, contact us.

Learn more about Qt Group in the Medical sector.