Skip to content
← Back to Insights

Stop blaming people

Why blame cultures destroy healthcare organizations and how to build accountability instead.

John Sambrook ·

We’ve all felt it. You’re in a hospital, watching dedicated, brilliant, and caring professionals work themselves to exhaustion. Yet, the process is agonizingly slow. The cost is astronomical. Patients are stuck in beds waiting for discharge. Clinicians are burning out at record rates.

How can a system filled with such good-hearted, experienced professionals produce so much friction, waste, and frustration?

The Blame Game (Our Flawed Response)

Our default response is to find someone to blame.

  • “The hospital is just trying to pad its bill.”
  • “That health plan just denies everything.”
  • “The discharge team is dropping the ball.”
  • “Doctors are ordering too many tests.”
  • “Nurses aren’t being efficient.”

We blame people or organizations. We assume bad intent or incompetence. This is the “blame game,” and it’s why the problems never get solved.

The Real Problem: Good People in a Bad System

The problem is not the people; it’s the system’s design.

The friction in healthcare---the delays, the waste, the burnout---is the direct result of good people being trapped in systems with deep, unresolved, structural conflicts.

A structural conflict is a “no-win” scenario where two perfectly valid and necessary goals are in direct opposition.

This Conflict is the Root of Healthcare’s Biggest Crises

This single concept---unresolved structural conflicts---is the hidden root cause of healthcare’s most “intractable” problems.

On Clinician Burnout

The Problem: We see epidemic levels of burnout and moral injury, costing billions in turnover alone.

The Blame Game: We respond with individual “resilience training” or “mindfulness apps,” which is like blaming the worker for not being strong enough.

The Real Conflict: The system needs clinicians to “meet all patient care demands” AND “protect the workforce from harm.” But it gives them no tools to do both, expecting them to absorb unlimited psychological trauma in a way it would never allow with physical hazards like radiation.

Goal A: Meet all patient care demands

Goal B: Protect the workforce from harm

Lose-Lose Outcome: Epidemic burnout, massive turnover costs, and moral injury---while we blame clinicians for not being ‘resilient’ enough.

On Complex Discharge Delays

The Problem: We see hundreds of patients stuck in acute-care beds, costing the system billions and blocking access for new patients.

The Blame Game: We blame the post-acute facilities for not accepting patients or the hospital case managers for not working fast enough.

The Real Conflict: The system has stakeholders working at cross-purposes. The hospital’s metric is “medically ready” (speed), while the health plan’s metric is “avoidable days” (cost). These misaligned metrics and interdependent barriers force dedicated professionals into systemic gridlock.

Goal A: Discharge patients quickly when ‘medically ready’ (hospital metric)

Goal B: Minimize ‘avoidable days’ and control costs (health plan metric)

Lose-Lose Outcome: Patients stuck in expensive acute-care beds, blocked access for new patients, and frustrated staff---while we blame case managers and post-acute facilities.

The Path Forward: You Don’t Manage Conflicts, You Solve Them

Here’s the good news: These conflicts are not permanent. They are not laws of nature. They are the result of assumptions we’ve made about how the system must work.

And if you can identify those assumptions, you can challenge them---and make the conflict “evaporate.”

This isn’t just a theory. It’s a proven, practical method.

Next Up: The 10-Year Case Study

In our next post, we will break down an independent, 10-year academic case study of a public hospital that was plagued by these exact “no-win” scenarios.

We’ll show you how they used this systems-thinking approach to identify their core conflict… and how solving it resulted in dramatic improvements---all without adding staff or a bigger budget.

  • 87% --- Reduction in patient wait times
  • 67% --- Cut in nursing overtime
  • 37% --- Increase in production capacity

Don’t Miss Part 2

Subscribe to our newsletter to get the full case study delivered to your inbox, plus practical insights on systems thinking in healthcare.