When Canadian wildfire smoke drifted south into Ohio and Virginia in July 2026, the air turned dangerous fast. In Virginia, the air quality index climbed from Code Red to Code Purple in a matter of hours, a category severe enough that most people had never seen it called in their state. For someone living with asthma, COPD, or another respiratory condition, that kind of shift represents a medical emergency waiting to happen.

The response from Waymark’s care teams was underway before Code Purple was officially called. Care teams in Virginia were reaching out to patients by lunchtime. Ohio was moving in parallel. Same day, not same week.

“Being able to find and reach patients in hours was so powerful in terms of our ability to get things done,” said Jeffrey Tingen, one of Waymark’s clinical pharmacist leads. The alternative, as he described it, would have meant several days of pulling reports, cross-referencing patient rolls, and building call lists before anyone picked up a phone.

This is how we have always envisioned AI-first community care in action: care teams using advanced data science to identify patients at risk of a medical emergency due to declining air quality, then finding who would most benefit from early intervention. From there, those same care teams – who have built relationships with patients – can deliver interventions directly within the community 

1. Waymark Signal^TM identified the patients mostly likely to need support

Waymark Signal, our suite of proprietary targeting algorithms, continuously stratifies patients by risk, by who is most likely to benefit from any given intervention, and by the specific factors that make an environmental event acutely dangerous for that given patient. When air quality deteriorated, the team did not have to build a query from scratch. Signal had already flagged the population most likely to benefit from proactive outreach: patients with a documented history of asthma, COPD, and related respiratory conditions.

Using Signal's data alongside care team notes, plus prescription and diagnosis history, our care teams mobilized the existing care delivery model against a fast-moving environmental threat. Without a system like Signal, the same identification would have required manual chart review across thousands of patients, or an ad-hoc query built by a small analytics team. These manual processes would have extended the response timeline into weeks and months, far past the narrow window of opportunity to intervene early and prevent respiratory flare-ups in the targeted population.

2. Care team members who already knew each patient made the outreach

While signal identified patients to outreach, our community-based leveraged their established history and relationships with them to get in touch quickly and ensure they had the support they needed.

"Whoever the previous care team member had interactions with, that person was tasked with reaching out proactively," Jeffrey said. "It was an all hands on deck sort of situation. We all knew we needed to be aware of who was going to need help immediately and move really quickly to take care of them."

During an event where the need is "check on a patient before something happens," trust is what determines whether the patient is actually going to pick up the phone or answer the text, and  whether they say what they actually need. Community-based care teams, the community health workers, care coordinators, and clinical pharmacists who have already built relationships with these patients, deliver the intervention based on what Signal flags.

3. Pharmacy and PCP routing closed the loop in the same conversation

Patients who needed help got connected inside the same texting thread that opened the check-in. When a patient wrote back that they were running low on a rescue inhaler, the care team member routed them to Waymark's pharmacy team for a refill. When a patient needed a follow-up appointment, the care team member routed them back to their primary care provider.

More than one patient wrote back that they were running low on their rescue inhalers and needed support. The team moved to get refills in motion the same day.

Denise Rembert, Waymark's Ohio-based community health worker lead, described her team calling patients to talk through the days ahead: upcoming appointments, whether they needed to leave the house, whether they had a mask on hand. Many were already prepared. Some needed the reminder that the smoke was worth taking seriously.

"We had so many patients say they really appreciate those calls," Denise said. "We don't see a lot of wildfire smoke around here, and I'm really proud of my team for stepping up and understanding what the air quality issue meant for their patients and how to get them to understand that too."

Extending this playbook

The smoke dissipated, and whether the next similar concern arises around air quality, medication shortages, or something else, Waymark will continue to implement these same steps to replicate this rapid response:

1. Continuous risk stratification through Waymark Signal
2. Community-based teams with pre-existing patient relationships
3. The clinical infrastructure to close the loop from outreach to intervention in a single conversation.

Whether the fast-moving threat is wildfire smoke, a medication shortage, or a heat wave, Waymark’s care teams demonstrate what a coordinated response looks like when informed by data science and driven by personal relationships within their communities.