1. What inspired your journey in advancing patient and staff experience in healthcare, and why do you believe human experience is becoming a central priority for healthcare systems today?
My work starts with a truth I’ve watched play out in my own family and community: people delay or avoid healthcare not because they don’t value their health, but because they don’t trust the system. That’s not anecdotal. That’s a structural failure with a dollar figure attached.
Health inequities cost the U.S. healthcare system $320 billion annually. By 2040, that number reaches $1 trillion. Those aren’t just policy statistics. They represent people who are making decisions about care based on whether they believe the system is designed to work for them.
That’s what drives my work, closing the gap between a system’s stated commitment to patient care and the operational reality patients actually experience.
As for why human experience is becoming a priority now: the financial case has gotten too loud to ignore. Hospitals with excellent patient experience ratings achieve 4.7% operating margins. Those that don’t are at 1.8%. That 2.6x profitability gap isn’t explained by clinical quality alone, it’s explained by whether patients trust you enough to choose you, return to you, and refer others to you.
Value-based care is accelerating this shift. When reimbursement is tied to outcomes and quality rather than volume, patient engagement isn’t a service line, it’s the business model. You can’t achieve outcomes with patients who disengage, and you can’t retain patients who don’t trust you. Human experience is becoming a priority because the financial architecture of healthcare now demands it.
2. From your perspective, what are the most pressing challenges healthcare organizations face today when trying to improve both patient and staff experiences simultaneously?
The most underestimated challenge is what I call the provider capacity gap, and it directly affects patient experience in ways organizations aren’t measuring.
The research is clear: physician burnout scores and patient experience scores are significantly correlated. A Massachusetts General Hospital study found strong negative correlations between burnout and the HCAHPS measures executives care most about, access to appointments, provider knowing medical history, overall rating. When providers are depleted, the five operational signals that build trust all degrade. Not because the technology failed. Because the people delivering care don’t have capacity.
Clinicians spend two to three hours on administrative tasks for every hour of direct patient care. Over half report feeling overworked. And yet patient experience strategies are typically designed around what patients receive, without accounting for whether providers have the capacity to deliver it.
This is a blind spot in how trust is built. The Trust Algorithm I’ve developed measures five operational signals, Accessibility, Resolution, Continuity, Proactivity, and Recovery — but the honest question is: do the people responsible for delivering those signals have the tools, time, and support to do so? Provider enablement isn’t a separate initiative from patient experience. It’s the supply side of the same equation.
Organizations that understand this don’t ask “How do we improve patient experience?” and “How do we reduce burnout?” as two separate questions. They ask: “What does it take to build a system where both patients and providers can trust the experience?”
3. What innovative approaches, technologies, or strategies do you believe are transforming how healthcare organizations deliver more human-centered care?
The most important shift I’m seeing — and advocating for in my IPX session — is the move from reactive measurement to proactive intelligence.
HCAHPS scores arrive weeks after discharge. Response rates have dropped to 26%. By the time an organization sees that data, the patient has already decided whether to come back. What high-performing organizations are building instead are leading indicators, real-time operational signals that predict loyalty, NPS trajectory, and retention risk before survey results arrive.
That’s the foundation of the Trust Algorithm: five behavioral signals; Accessibility, Resolution, Continuity, Proactivity, and Recovery, measurable right now in your contact center, scheduling system, and billing operations. Not sentiment. Behavioral data. Leading indicators, not lagging ones.
In the contact center space specifically, where I specialize, the most transformative approach is what I call the Super Agent model. Most organizations approach AI as a replacement strategy, automate calls, reduce headcount. That misses the real opportunity. The Super Agent model maps the entire patient journey across human and AI touchpoints, designing each handoff intentionally. AI handles the structured, binary-outcome interactions. It surfaces patient history, flags sentiment, and delivers real-time guidance. The agent enters every conversation with context, confidence, and the cognitive space to focus on what humans do best: resolution and relationship.
This isn’t automation versus empathy. It’s a deliberate architecture where AI and humans are each doing the work they’re actually designed for, and the patient experiences a seamless, continuous journey rather than a fragmented series of transfers. That’s what my session at IPX unpacks: how to build that architecture, and how to measure whether it’s working.
4. How can healthcare leaders foster a culture where both patients and healthcare professionals feel heard, valued, and supported?
I think the organizations getting this right have figured out something that goes beyond DEI initiatives, beyond empathy training, beyond engagement surveys. They’ve built cultural competency as a competitive advantage.
Cultural competency, in the way I use it, isn’t a compliance checkbox. It’s the organizational capacity to understand who your employees are and who you serve deeply enough to design experiences that genuinely meet both where they are. That requires different tools, different data, and a different definition of what “excellent” looks like for different populations.
Patients who don’t see themselves reflected in how a system communicates, schedules, bills, or follows up — they don’t call it a cultural competency failure. They just leave. And the $320B health equity cost is, in large part, the accumulated financial consequence of systems that weren’t designed with their communities in mind.
For staff, the same principle applies. Organizations that invest in truly understanding their workforce, not just engagement scores, but how people work, what they value, what barriers exist to doing their best work — retain people longer and produce better patient outcomes. The research supports a bidirectional relationship between provider experience and patient experience that most organizations haven’t operationalized.
The leaders building real competitive advantage here aren’t just telling their teams to be empathetic. They’re giving them the tools, the context, and the structural support to actually be empathetic — for every patient, in every language, across every channel. That’s what it means to design for humans rather than processes.
5. Can you share an example or initiative that has made a meaningful impact on patient or staff experience in your organization or the wider healthcare ecosystem?
Rather than a single example, I’d point to a body of research that validates the methodology I’ve built — because what I’ve found is that the Trust Algorithm isn’t a new theory. It’s a framework that makes measurable what high-performing organizations have been doing operationally for years.
Intermountain Health deployed AI-assisted 24/7 access and achieved an 85% reduction in call abandonment. Steinberg Diagnostic extended access to 11pm using AI virtual agents and dropped abandonment from 10% to 3%. Both results map directly to the Accessibility signal, the foundational question of whether patients can reach you on their terms.
Houston Methodist built an architecture focused on complete, patient-confirmed resolution, not ticket closure, and achieved 91% of calls resolved without agent escalation. That’s the Resolution signal: the difference between a system deciding a problem is solved and a patient believing it is.
Baptist Health deployed AI-enabled operational efficiencies that freed capacity — and channeled that capacity into faster, more empathetic service recovery. That’s the Recovery signal: turning failures into loyalty moments rather than letting patients leave quietly.
What these organizations have in common isn’t a specific technology platform. It’s a strategic decision to measure trust as an operational output, not just satisfaction as a sentiment. That’s what I’m building toward with every health system I work with — the measurement infrastructure that makes these behaviors visible, scoreable, and improvable in real time.
6. Looking ahead, what does the future of human experience in healthcare look like to you, and what one change or action should healthcare organizations prioritize today to move in that direction?
The future I’m building toward is one where healthcare organizations design for outcomes and relationships simultaneously. Where “seen, heard, and understood” is not aspirational language but a measurable operational standard.
Value-based care makes this urgent. To hit quality metrics, reduce readmissions, and capture shared savings, patients have to stay engaged. They have to follow through on care plans. They have to come back. None of that happens reliably with patients who don’t trust you, and staff who don’t have the capacity to build that trust. The outcomes VBC demands require the experience infrastructure to support them.
That’s the premise of the Patient Experience Hub Model: a proactive operational architecture that puts outcomes and experience at the center of design rather than treating them as byproducts of efficiency. Instead of asking “how do we handle more volume?” the question becomes “how do we build a system where patients feel known, and where every interaction is a deposit in the organizational trust account?”
The Trust Algorithm makes that measurable — five signals, scored in real time, tied to the financial outcomes that matter to the C-suite: margin, retention, and loyalty.
The one change I’d prioritize: stop designing operations for efficiency and start designing them for relationships. That shift is not about spending more. It’s about measuring differently. When you measure trust — not just satisfaction, not just throughput — you start making different decisions about where AI should operate, where humans belong, and what “excellent” actually looks like. The technology to do this exists. The frameworks exist. What’s missing in most organizations is the strategic architecture that ties them together.
Satisfaction is transactional, experience is longitudinal.
