Pinal County, located between Phoenix and Tucson, has become one of Arizona’s fastest-growing regions, issuing more than 3,000 single-family permits in 2024 alone. This surge in developmen...
From Reactive to Predictive How Data Analytics is Improving Senior Living Care
Written by:
Date:
30 Jul 2025
Share via Facebook
Share via Linkedin
Share via X
Copy to clipboard
The senior living industry sits on a goldmine of resident data that has historically remained untapped. From daily activities and medication schedules to incident reports and behavioral observations, communities collect vast amounts of information required by state regulations, yet this data typically sits dormant in legacy systems, offering little operational value.
This disconnect between data collection and actionable insights represents a significant opportunity in an industry facing mounting pressures. As residents enter communities with higher acuity levels requiring more intensive care, operators must find ways to deliver better outcomes without proportionally increasing staffing costs.
Bennett Porson, CFO of Fynn.io, a data platform for senior living that emerged from Galerie Living’s operations, explains the fundamental challenge: “Senior living is becoming increasingly expensive to run, especially as residents continue to come into communities with higher acuity levels and multiple medications. You have to either have more staff in the building to watch those residents all the time, or you have to find ways to be more efficient with the data you have.”
The Clinical Model Shift
The industry is experiencing a notable change toward what Porson describes as a clinical model. “Senior living sits in this triangle of real estate, hospitality, and clinical care,” he notes. “What we’re seeing is this push and more investment toward the clinical side of senior living operations because of necessity.”
This shift stems from practical realities. Higher acuity residents require more sophisticated care, but operational benefits extend beyond immediate care needs. “If you’re better taking care of your residents and they’re living happier, healthier, longer, you’re closing your back door and your length of stay is increasing,” Porson explains.
The clinical model also addresses the complex web of stakeholders in senior care. A typical resident may interact with six to seven different care providers: primary care physicians, hospice services, rehabilitation companies, hospitals, pharmacies, family members, and the senior living community.
“When you compare senior living to the rest of those stakeholders, what they have that nobody else has is 24/7, 365-day watch over a resident, and they have the ability to capture data 24/7, 365,” Porson observes. “They can communicate it back to those other six people because each stakeholder in that care continuum is crucial.”
Building Solutions from the Inside Out
Fynn.io’s approach stemmed from direct operational experience. The platform was first developed within Galerie Living’s communities after unsuccessful market searches for suitable solutions.
“Our CEO and founders were trying to get players in the space to pivot toward this data-driven model,” Porson recalls. “After multiple years of not being able to see what he wanted in the industry, he said, ‘I’m going to build my own platform.'”
This internal development allowed two to three years of testing with care teams and operations staff before commercializing about 18 months ago.
The core functionality centers on an EHR (Electronic Health Record) and eMAR (Electronic Medication Administration Record) system, but the real value lies in turning dormant data into actionable insights for proactive care.
Predictive Analytics in Action
The platform’s most compelling application involves behavioral analysis to predict incidents before they occur. Working with clinicians at the Mayo Clinic, Fynn.io developed a “mini-mini mental health assessment” that caregivers complete using emoticons during routine charting.
“We take this over and over again, and we start to build up a resident behavioral health baseline,” Porson explains. “We start to understand how residents act and behave at certain times of the day, certain days of the week, with different types of caregivers.”
When algorithms detect deviations from a resident’s behavioral normal, the system flags them as “at risk.” According to Fynn.io’s analysis, these flagged residents are four times more likely to experience an incident within the next 24 hours.
The system then provides playbooks for care teams to assess and determine appropriate interventions. This addresses a common frustration among caregivers who notice changes but struggle to communicate concerns when managing many residents.
“We usually heard the same story from caregivers: ‘I could have told you this was going to happen. Miss Betty was acting differently for the last two or three days,'” Porson notes. “The problem is getting that information out of caregivers when they’re focused on delivering care day to day.”
Market Focus and Product Evolution
Fynn.io found its best product-market fit among mid-market operators, with 5 to 50 communities needing customizable platforms but not the complexity of larger operators.
“Our bread and butter is in the mid-size operators that have certain customizations they need, a care platform that can fit those configurations,” Porson explains. The target demographic includes communities focused on assisted living and memory care.
Fynn.io’s development included lessons about focus. Initially, the company attempted to build a comprehensive platform including CRM and staffing solutions, but found that focus on clinical care aligned best with its mission.
“We weren’t focusing on one thing that people really needed solved,” Porson reflects. “When we thought about our mission… we realized that lives in the clinical part.”
This led to a strategic pivot toward clinical care and partnerships with other platforms to create an integrated ecosystem. “Let’s get everything under one login, let’s have one source of truth, and let’s all share information back and forth,” Porson says.
Technology Integration and Future Development
Fynn.io is investing in two key areas: ecosystem integrations and enhanced data science. Integrations respond to requests for connections with call systems, CRMs, and medication dispensing programs.
“All of those people are playing nice in the sandbox, which is great for us,” Porson notes. “As we all innovate together, we can ultimately drive better resident care.”
The data science investment aims to improve proactive care using data such as medications, ADL history, pre-existing conditions, and weight changes. Future integrations with nurse call systems, fall detection, and autonomous vitals collection could further enhance predictive capabilities.
Industry Implications
Demographic trends, often called the “silver tsunami,” create both opportunities and pressures for the industry. While the growing population expands the market, it also intensifies the need for efficiency and quality improvements.
“There’s enough opportunity and need with the people in senior living today that the growing population is just another factor to add,” Porson observes.
For operators, the shift to data-driven care is both a necessity and a chance for differentiation. Communities demonstrating superior care through technology may gain advantages in resident attraction and retention.
Similar Articles
Explore similar articles from Our Team of Experts.
