Predicting sepsis in cancer patients using technology and implementation science
Official title: SPOT-IT: Sepsis Prediction in Oncology Through Implementation Science and Technology
Funded at Oregon Health & Science University · NIH-11110349 · Data updated 2026-11-12
This study is working to help doctors spot and treat sepsis earlier in cancer patients by using advanced technology and health records, making it easier for healthcare teams to provide better care when it’s needed most.
Quick facts
| Grant type | Career grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Oregon Health & Science University NIH-funded |
| Lab location | 1 site (Portland, United States) |
| Project start | June 7, 2024 |
| Project end | May 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $283,359 |
| NIH project number | 5K08CA270383-02 |
| Project ID | NIH-11110349 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients currently undergoing treatment for cancer who are at risk of developing sepsis.
✕Less likely to help
Patients with non-cancer-related conditions or those not currently receiving cancer treatment may not benefit from this research.
What this research studies
This research aims to improve the early detection and treatment of sepsis in cancer patients, a serious condition that can lead to significant complications and death. By utilizing electronic health record (EHR) data and machine learning techniques, the project seeks to develop a specialized prediction model tailored for oncology patients. Additionally, it will focus on creating an effective implementation strategy to ensure that healthcare providers can easily use this model in clinical settings. The goal is to enhance patient care by ensuring timely and accurate recognition of sepsis in those undergoing cancer treatment.
Why it matters
Potential benefit: If successful, this research could lead to earlier detection and better management of sepsis in cancer patients, potentially reducing morbidity and mortality rates.
How similar studies have gone: Previous research has shown promise in using machine learning for sepsis prediction, but this specific approach tailored for oncology patients is relatively novel.
Where this research is happening
-
Oregon Health & Science University
Portland, United States Active
Researchers
- Principal investigator: Lyons, Patrick G — Oregon Health & Science University
- Study coordinator: Lyons, Patrick G
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.