Hospital leaders are under unprecedented pressure to deliver safe, high-quality care while navigating persistent clinician shortages, rising turnover, and shrinking margins. While traditional quality dashboards, safety event reporting, and Centers for Medicare & Medicaid Services (CMS) scores are essential, they are lagging indicators. They show problems after they have already affected patient care and operations.
At Atalan, we are exploring the relationship between clinician turnover patterns and quality and safety, to determine how these measures can predict risk before traditional outcomes are visible. While our research is still in its early stages, the initial findings are intriguing and suggest a connection worth examining across health systems.
Preliminary Observations
In an internal analysis 36 CMS-reported healthcare-associated infection (HAI) measures across 20 hospitals observed between 2022 and 2024, Atalan’s data shows a statistically significant pattern that raises important questions:
- Facilities performing better than the national average on HAIs had an average clinician turnover rate of 9.3%
- Facilities performing worse than the national benchmark on HAIs had an average turnover rate of 11%
While these results are preliminary, they suggest a signal worth investigating further: rising clinician turnover may precede shifts in quality metrics. Because turnover patterns are observable and predictable months before CMS quality scores are finalized, they may provide a leading indicator of emerging operational or clinical risk, long before traditional reporting captures the impact.
This aligns with a growing body of research exploring the relationship between clinician turnover and patient outcomes. For example:
- A nine-year study of 236,000 nurses, 41,800 physicians, and 8.1 million patients found that higher clinician turnover was associated with increased mortality. Each standard deviation increase in nurse turnover corresponded to a 0.035–0.052 percentage point rise in 30-day mortality, particularly in surgical and general medicine units.
- Research across 7,076 nurses in 161 hospitals indicated that workforce strain, more than staffing levels, was significantly associated with HAIs. Every 10% increase in strain was linked to additional patient safety events, illustrating the operational and clinical ripple effects of workforce instability.
- The financial implications are substantial: HAIs alone cost the U.S. healthcare system $28–$45 billion annually, directly affecting operating margins.
These studies demonstrate that clinician turnover is not just a workforce concern. It can be an early signal of clinical and operational risk. At Atalan, we are exploring how this signal can be detected before outcomes degrade, so health system leaders can intervene proactively.
Why This Matters
Even without drawing firm conclusions, these early insights raise important questions for health system leaders:
- Could clinician turnover be an early warning signal of operational or quality strain?
- Are there patterns in your own organization that mirror what we are seeing?
- What opportunities might exist to intervene proactively before patient care is affected?
Stable teams contribute to consistent workflows, knowledge retention, and care continuity. When clinicians resign unexpectedly, the operational impact can ripple across teams, affecting scheduling, coverage, and patient access. Exploring turnover as a system-level signal allows leaders to ask new, strategic questions about risk management.
Leading the Way by Asking the Right Questions
At Atalan, we are committed to the science of healthcare workforce dynamics. Our early work in this area is designed to open the conversation. We are exploring the relationship between turnover and quality at a level of detail no one else is examining at scale, integrating clinician, operational, and outcomes data.
We see this as a call to action for health systems: consider how your turnover patterns may relate to operational and quality outcomes, and what insights might be gained by examining these signals before they appear in lagging metrics.
We welcome the conversation: what do you see in your organization? Does it make sense that clinician turnover could signal emerging risks to patient care? By asking these questions, we hope to help leaders think differently about workforce stability, patient safety, and operational resilience.