With the rise of AI vendors entering the healthcare space, practice managers now face a difficult task: evaluating tools and choosing one that will best serve both operational efficiency and patient outcomes.
This decision-making process is further complicated by the fragmented state of healthcare data. As Dr. Steven Stack, former President of the American Medical Association, aptly put it: "The lack of interoperability is one of the major reasons why the promise of EHRs has not been fulfilled." In a landscape where electronic health records remain largely siloed, manually evaluating any AI scheduling tool requires tedious comparison between different softwares and individual call monitoring to piece together performance insights.
At EliseAI, we recognize that this time could be much better spent on patient care. To support this, we designed a metrics dashboard that integrates our internal data infrastructure with each practice's individualized EMR system, ensuring accurate, real-time insights tailored to their specific specialty.
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Scheduling and Actions Analysis
Practitioners need visibility into the actionable outcomes being generated from calls handled by our AI.
Our visualizations identify which tasks or patient cases the AI is successfully creating. This enables practices to understand where they can lean in further. The dashboard also shows the breakdown of scheduling-related actions, helping teams evaluate if Elise is driving more appointment volume and improving scheduling efficiency.
When practices see exactly what's being accomplished on every call—from new patient bookings to prescription refill requests—they can make informed decisions about staffing, workflow optimization, and where to expand AI support.
Call Frequency Breakdowns
To help practices better understand when and why their patient engagement peaks, our dashboard includes a call frequency heat map broken down by day.
This view highlights volume spikes to enable more informed staffing, triage planning, and scheduling optimizations. If Monday mornings consistently show the highest call volume, practices can adjust coverage accordingly. If Friday afternoons are quieter, teams can redirect focus to other patient care priorities.
At Elise, we believe in transparency with call transfer rates and the reasons behind them. By surfacing this information, we foster dialogue with our partners around the scheduling scenarios our AI can better support—so we can continue to refine our product together.
Key Summary Statistics
To synthesize impact, we highlight two essential metrics: time saved and return on investment (ROI).
Practices can now see the amount of call handling that has been off-loaded to AI. Our partners typically save between 10-14 hours per day in staff-handled calls, freeing clinical teams to focus on in-person care rather than repetitive phone tasks.
ROI is calculated by comparing the performance of our solution to equivalent staffing costs. It factors in salary averages, call capacity benchmarks, and overhead assumptions to give a sense of the financial value we're delivering to the practice. When operational efficiency translates to measurable dollars saved, decision-makers can confidently justify their investment.
Turning Data Into Action
Together, these metrics provide clear insight into the measurable value EliseAI is delivering for healthcare teams.
Our goal is to equip every practice with actionable, real-time data that supports smarter evaluation and encourages open dialogue with our partners. We don't just automate calls—we help practices understand the full scope of what's being accomplished, where improvements can be made, and how AI fits into their broader operational strategy.
In an industry where interoperability challenges make accurate measurement difficult, we've built a solution that cuts through the noise. Our dashboard doesn't require manual call reviews or cross-platform data exports. It simply shows you what's working, what's not, and where you can go next.