Every ambulance rushing down the street is part of a bigger story: a neighbor in distress, a rapid response by skilled professionals, and a network working to save a life. Inside the medic unit, paramedics are not only treating patients, but at the same time documenting critical information about the patient’s status and care. This data holds the key to understanding how well our emergency systems are working and how we can save more lives in the future.
However, for many emergency medical services (EMS) agencies across the country, this valuable data often ends up locked away in software systems that make it difficult to see the big picture. Agencies struggle to access it and combine it with other data.
The Seattle Fire Department (SFD) faced this exact challenge. Inspired by conversations with other fire departments, SFD partnered with Seattle’s Innovation & Performance Team to build a solution.
Seattle’s EMS data pipeline brings together siloed emergency response and health records into one place, allowing for easy analysis across multiple steps in the system while protecting patient privacy. This is much more than a technical improvement—it directly supports life-saving work. Now, Seattle has made our solution public to help other agencies do the same.
The struggle to access life-saving information
The Seattle Fire Department relies on a platform called ESO to document patient care during a crisis. While the software is essential for recording what happens during an incident, getting that information back out for analysis was incredibly difficult. When this project began in 2022, the system required record-by-record downloads, making it nearly impossible to look at trends over time.
Even when bulk export features became available in 2025, a major piece of the puzzle was still missing. To really understand an emergency, you need to link the medical report with the initial 911 call and the dispatch data. You need to know what the dispatcher heard, how long it took the responders to arrive, and what happened on the scene. Without a way to connect these different systems, agencies were missing key ingredients for understanding performance, guiding policy, and improving survival outcomes.
Partnering to find solutions
Seattle realized we weren’t alone in this problem. Through conversations with leaders at Boise Fire and the Unified Fire Authority of Utah, it became clear that this was a shared struggle. These agencies were all hitting the same barriers with the same software.
Seattle’s Innovation & Performance team partnered with the Seattle Fire Department and the University of Washington School of Medicine to design a modern, automated data pipeline. Together, the team created a tool that can securely pull the data out, clean it up, and store it in a way that protects privacy and makes advanced analysis possible.
How the pipeline works
The team built this bridge as open-source technology, making the software code free for anyone to inspect, modify, and enhance. Here is a simple breakdown of the technical approach:
- Secure Connection: The system connects securely to the ESO platform.
- Automated Collection: Instead of a human manually downloading files, the system automatically pulls the incident and patient care records.
- Transformation: Data often comes in messy or in formats that are hard to read. The pipeline uses Python (a coding language) and Apache Spark to organize and standardize the information.
- Connecting the Dots: The system links the medical records with Computer-Aided Dispatch (CAD) data. Now, the medical outcome is connected to the 911 operational response.
- Ready for Analysis: Finally, the clean, connected data is loaded into a storage space where analysts can easily build charts, run studies, and find answers.
While Seattle uses Amazon Web Services (AWS) to host this tool, the code is written in Python. This makes it adaptable, so agencies using different cloud providers, like Azure or Google Cloud, can still use the logic to build their own versions.
Medical data is some of the most sensitive information that exists. Safeguards are built into the technology to ensure patient privacy at every step.
Turning data into better outcomes
This project was about giving EMS leaders the tools they need to improve survival rates and health outcomes for their residents. The impact of this new pipeline was immediate and profound.
Accelerating cardiac arrest research
In the world of pre-hospital emergency medicine, agencies track out of hospital cardiac arrests, measuring how often people survive sudden cardiac death outside of a hospital. Improving this survival rate requires deep study of every link in the chain of survival.
Before this data pipeline existed, assembling the data for a cardiac arrest survival study could take up to three months of staff time. The automated data pipeline has doubled the efficiency of this process, allowing researchers and medical directors to stop spending months wrestling with data and start spending that time analyzing it. They can identify training gaps, evaluate new CPR techniques, and implement community programs much faster.
Responding to the overdose crisis
Communities across the country are facing a rising tide of overdose emergencies. In these situations, speed is everything. Public health officials need to know where overdoses are happening in real-time to deploy resources and save lives.
The new pipeline enables faster, reliable access to overdose data. This helps the city:
- Track trends as they happen, rather than weeks later.
- See how specific interventions are working.
- Focus resources in the neighborhoods that need it most right now.
Sharing the code with the world
Many other EMS agencies have the same needs but lack the budget or technical staff to build a complex data pipeline from scratch. To help our peers, Seattle chose to release our solution as open-source software.
What is available?
The City of Seattle has published the Python code that powers this pipeline under the MIT License. This is a permissive free software license that allows other agencies to use, change, and build upon the work without having to pay licensing fees.
The package includes the code for extracting the data, the logic for cleaning it up, and examples of how to load it into a database. The goal is to give other municipalities a head-start on their data modernization journey, allowing them to skip months of trial-and-error.
Privacy first
The repository includes safeguards to help agencies protect sensitive medical data. It features “de-identification” patterns, which are methods for stripping away personal details so that data can be analyzed for trends without revealing the identity of any specific patient. Each agency is responsible for ensuring they use the code in a way that follows their local laws and HIPAA regulations.
How to access the repository
Because this code deals with sensitive EMS data systems, it isn’t completely open to the general public. Access is reserved for public safety agencies that use ESO or have similar needs. This ensures that the tools are put into the hands of the professionals who serve our communities.
To request access, agencies can email the City of Seattle Information Technology – Data Engineering team at ITD_eHR_Git_Code_Sharing@seattle.gov.
A future built on collaboration
This open-source data pipeline is a powerful example of what is possible when we work together. By sharing our work, Seattle hopes to help other communities avoid costly development cycles and focus on patient care. A breakthrough in one city can help save a life in another.
Some language in this post was generated using Jasper.ai. All content was edited and fact-checked by staff on the Innovation & Performance Team. Learn more about the City of Seattle’s AI Policy.