Summer brings a spike in 911 calls for everything from heat-related emergencies and car accidents to fires and large public events. For EMS and fire crews, that means more pressure, tighter response times, and greater demand for accurate, fast documentation. But behind the scenes, a quiet shift is happening: artificial intelligence is stepping in to support first responders when every second counts.
Joe Graw, Chief Growth Officer at ImageTrend, says the biggest shift is that AI now supports real-time decision-making. It reduces time spent on paperwork, improves data quality, and allows responders to focus more on patient care. Tools like voice-to-text and smart image recognition are built around the realities of emergency response.
One example currently in action: Los Angeles County Fire is field-testing ImageTrend’s AI-assisted image capture to help crews more accurately and quickly document blood transfusions. Scanning a blood bag automatically logs critical details, such as unit number and expiration date. This information is vital for trauma patients and essential for downstream care coordination.
Agencies are also using real-time insights from the platform to make smarter decisions on the fly. They monitor call volume, incident type, and unit availability live across their systems, then adjust staffing, reroute units, or escalate care as needed, based on operational data rather than lagging reports.
This type of visibility also helps reduce pressure points. First responder burnout and hospital delays are ongoing challenges, but AI can help alleviate some of that burden. By automating repetitive documentation tasks and turning natural speech or scanned inputs into structured data, ImageTrend’s system reduces fatigue. Their Continuum solution also flags early signs of hospital offload delays and rising acuity levels, giving teams time to prepare and respond.
On the hospital side, the company’s Health Information Hub is closing long-standing gaps between field providers and emergency departments. Now, crews can pull up medication history and allergy information at the scene. Meanwhile, hospitals receive structured EMS data in real time, often before the patient even arrives.
Instead of layering on new complexity, ImageTrend focuses on building AI tools that fit how responders already work. AI Assist, for example, captures dictated narratives during transport or fills in fields from a quick photo of a medication list, designed with “human-in-the-loop” control and validated in real-world conditions.
Asked about one commonly overlooked metric, Graw points to refusal rates. Without real-time tracking, trends around patient refusals by provider, location, or incident type can go unseen. With visibility, that data can uncover care gaps, training needs, or early public health signals.
Looking forward, ImageTrend is preparing for what Graw calls the next frontier: connected intelligence. The goal is to link data across the entire response timeline from pre-incident planning to post-incident review and long-term outcomes. Investments are already underway in predictive analytics, continuous quality improvement tools, and natural language search.
AI might not be visible to the average person calling 911, but behind the scenes, it’s helping responders move faster, document smarter, and deliver safer care.
Spencer Hulse is the Editorial Director at Grit Daily. He is responsible for overseeing other editors and writers, day-to-day operations, and covering breaking news.
