Clinical Workload in Cardiology

What "Workload" Actually Means

When we say "clinical workload," most people picture long hours. Nights on call. Weekend shifts.
But that's not what's breaking people.
Workload correlated with burnout across all healthcare worker groups, whereas feeling valued was related to lower burnout in most groups. Medical Economics

Translation: It's not how much work. It's what kind of work—and whether it feels meaningful.

Let me show you what a "typical" morning looks like for Maria, a cardiology nurse managing remote monitoring:

6:45 AM: Log into remote monitoring platform. 83 transmissions overnight.
7:00 AM: Triage transmissions. Which need immediate callback? Which can wait? Which are device errors? 45 minutes, 37 clinical decisions.
7:45 AM: Call back 6 patients. Three don't answer. Leave voicemails. Make notes to call again.
8:15 AM: Document everything in the EHR. Copy-paste from monitoring platform because the systems don't talk to each other.
8:45 AM: First scheduled patient arrives. Maria is already behind.
9:00 AM: She hasn't had coffee yet.

This is death by a thousand clicks. And none of it feels like nursing.

The Redistribution Problem

Here's what happened when healthcare "went digital":
We automated some tasks. Great. But we didn't eliminate the work—we redistributed it.

Before remote monitoring:

• Patients called when they had symptoms

• Nurses triaged phone calls

• High-urgency cases went to clinic or ER

After remote monitoring:

• Devices transmit continuously

• Nurses triage digital transmissions

• High-urgency cases still go to clinic or ER

• Plus: nurses now manage device connectivity, patient adherence, and data entry across multiple non-integrated systems

We added a whole layer of work and called it "efficiency."
Hospital-based specialties reported the lowest job satisfaction at 74.8%, driven by workload intensity, staffing constraints, and administrative burden. American Medical Association
The dissatisfaction isn't about patient care. It's about everything around patient care that prevents them from actually doing their jobs.

The Cognitive Load No One Measures

Hospitals measure FTEs (full-time equivalents). They measure patient-to-staff ratios. They measure throughput.
Nobody measures cognitive load.

Cognitive load is:

• The mental effort of deciding which of 47 alerts matters

• The context-switching between EHR, monitoring platform, phone, and pager

• The anxiety of knowing something might slip through the cracks

• The invisible burden of being the human safety net for imperfect systems

This is why clinicians describe feeling "exhausted but haven't done anything." The work isn't physical. It's cognitive. And it's relentless.
A 2024 study found that feeling valued was associated with lower burnout. But how valued can you feel when your job is mostly managing technology failures? Medical Economics

What Technology Gets Wrong About Workload

Most health tech companies measure success by what the technology can do.
"Our system monitors 47 parameters!" "We send real-time alerts!" "We integrate with your EHR!"
Nobody asks: Does this reduce the work humans have to do, or just change what that work looks like?

• Example: A remote monitoring system that "integrates" with the EHR but requires manual data entry to complete the integration. That's not integration. That's adding steps.

• Example: A dashboard that shows every patient's data in real-time. Sounds good, until you realize real-time monitoring requires someone to watch it in real-time. You haven't automated surveillance—you've just moved it from the patient's living room to the nurse's screen.

At Sensocor ML, we ask a different question: What work can we eliminate entirely?

Not optimize. Not redistribute. Eliminate.

Can AI triage transmissions before they reach human eyes? Yes. Can we filter device errors to technical support instead of clinical staff? Yes. Can we distinguish "needs attention today" from "monitor over the next week"? Yes.

That's not just better technology. That's technology that actually respects the finite capacity of healthcare workers.

What Actually Works

The solutions aren't mysterious. They're just hard to implement because they require rethinking assumptions:

• Assumption 1: More data is better. Reality: Actionable data is better. Raw data is just noise.

• Assumption 2: Clinicians should triage everything. Reality: AI should triage routine decisions. Humans should handle exceptions and nuance.

• Assumption 3: Technology should empower clinicians to do more. Reality: Technology should free clinicians to do less—less administrative work, less data entry, less context-switching—so they have bandwidth for complex decision-making.

The Path Forward

Here's what needs to happen:

Health systems must measure cognitive load. Not just patient ratios. Not just hours worked. Measure: How many systems do staff toggle between? How many decisions before first patient contact? How much time on documentation vs. patient care?
Technology vendors must prove workload reduction. Not "Here's what our system can do." But "Here's how many minutes per day this saves clinical staff." If you can't quantify that, your tech isn't ready.
Leadership must trust frontline staff. When a nurse says "This system creates more work," believe them. They're the ones living it. Design solutions with them, not for them.

Sources:

• Linzer M, et al. (2024). Work Environment, Burnout, and Intent to Leave Current Job Among Cardiologists and Cardiology Health Care Workers. Journal of the American Heart Association. DOI: 10.1161/JAHA.123.034527

• American Medical Association (2025). National Physician Comparison Report.

• Medical Economics (2025). Physician Burnout Declines Overall, But Gaps Persist Across Specialties.