Frequently Asked Questions

Overview

Atalan is the first Clinician Retention Intelligence (CRI) platform, helping health systems predict and prevent surprise clinician resignations up to 12 months in advance.

What does Atalan do?

Using real-time, objective data that health systems already have, Atalan’s machine learning models pinpoint at-risk clinicians, uncover the causes, and tailor proactive targeted actions that are seamless to implement.

Who typically uses Atalan?

Atalan is commonly used by operational and workforce leaders who are involved with retention, engagement, and productivity outcomes.

Service line and clinical operations leaders
HR and workforce strategy leaders
Quality, safety, and well-being leaders
Executive sponsors aligned to retention and access goals

“Status quo” questions

We do not have a turnover problem. Why would we need Atalan?

Turnover risk often builds silently months before a resignation. Atalan is designed to help organizations detect early patterns and prevent avoidable surprises, even when baseline turnover appears acceptable. Many of our health system partners have low turnover rates, but are seeking to maintain their advantage in a highly competitive labor market by maintaining their retention rates.

If turnover is low, what else can Atalan help with?

Atalan can support broader initiatives beyond retention that influence care delivery and clinician fulfillment, including engagement, burnout reduction, operational sustainability, and patient safety metrics linked to staffing stability.

Differentiation and existing approaches

We already use surveys to hotspot issues. How is Atalan different?

Surveys provide valuable perceptions, but they are often infrequent, anonymous, and affected by nonresponse bias, leaving “silent sufferers” undetected. Atalan adds objective, real-time signals from operational and workforce data to help detect early risk patterns before strain escalates to resignation.

How is Atalan different from Epic Signal Reports?

Signal Reports focus on EHR usage patterns and are designed to optimize EHR usage, not to identify turnover risk. Refer to KLAS 2023 study.

Atalan evaluates a broader set of leading indicators and drivers of strain and turnover risk across multiple domains, not only EHR usage.

We are rolling out ambient AI documentation tools (for example, DAX). Why would we need Atalan?

Ambient AI can reduce documentation burden, but turnover is typically multi-factorial. Atalan takes a systemic approach, analyzing 100+ operational and workforce triggers – workload, scheduling, clinical volume, tenure, and more. Documentation is only one of those factors, addressing a narrow slice of a much larger, complex picture that drives clinician retention.

Model, accuracy, and methodology

How does Atalan’s modeling work, and how accurate is it?

Atalan’s approach is evidence-based and validated in real-world deployments. Performance is measured using standard model evaluation methods. Atalan’s models accurately flag at-risk clinicians, with performance metrics considered strong in complex healthcare settings (AUC 0.7–0.8).

My organization is unique. How do we know it will be accurate here?

Atalan can run a retrospective analysis using your historical data to validate performance in your environment and align stakeholders on what “accurate and useful” means for your use case.

What are the 100+ departure triggers, and where do they come from?

The metric set is grounded in research on clinician strain and turnover. The specific departure triggers are organized by broader domains, such as compensation and benefits, workload and demand, experience and role context, EHR and administrative burden, and resource dynamics.

Does Atalan work across specialties and inpatient/outpatient environments?

Yes. Specialty workflows vary, so meaningful benchmarks should be specialty-aware. Atalan is designed to account for specialty and setting differences when evaluating patterns and flagging changes that matter.

How does the model account for individual differences?

Rather than applying one-size-fits-all thresholds, Atalan focuses on patterns over time and contextual signals relative to similar roles, specialties, and local norms, so risk signals remain relevant to the clinician’s operating context.

Action and outcomes

Do you only diagnose, or do you help us take action?

We do both. Atalan is designed to pair departure triggers with practical, evidence-based targeted actions that frontline leaders can implement. The goal is to move from insight to action and to make changes measurable over time.

Can we measure whether targeted actions or workflow changes are working?

Yes. Because Atalan refreshes on a recurring cadence, teams can compare pre- and post-action trends in key drivers and leading indicators, then correlate those shifts with downstream retention and operational outcomes.

ROI, pricing, and value justification

How do we justify the cost?

Our customers commonly evaluate the cost of our platform against the cost of preventable attrition, including protected revenue, avoided replacement effort, and improved access and continuity of care. Some deployments have reported multi-million-dollar annual savings and ROI figures that can exceed typical thresholds for workforce initiatives. Results vary and should be modeled using local assumptions.

Privacy, trust, and governance

Will clinicians view this as “Big Brother”?

Successful rollouts emphasize transparency and support. Atalan uses operational data already used for everyday management and positions insights as a way to remove structural stressors and improve work conditions, not to police individuals. Ultimately, the purpose is to help clinicians find greater fulfillment and create an environment where they want to stay.

Who can access sensitive provider data?

Access is configurable and restricted to approved organizational leaders based on your governance and privacy requirements. Data governance is a core part of implementation and ongoing operations.

How do you handle consent, compliance, and governance?

Atalan works within your existing governance frameworks and operational processes. Implementation is designed to minimize disruption and align with organizational policies and requirements.

Implementation and operational lift

How heavy is implementation for IT?

Atalan is designed for a modest IT lift. Typical deployments rely on existing workforce and clinical data feeds and are commonly measured in weeks rather than quarters. In all implementations, the IT effort has been reported as 80-100 total hours up front, with no hours needed on an ongoing basis.

How does Atalan stay relevant as healthcare workflows and technology change?

Atalan recalibrates based on refreshed data and evolving operational patterns, helping teams monitor new workflows and technology rollouts without losing visibility into emerging drivers of strain.

Labor environment considerations

Does Atalan work in unionized environments?

Yes. Because the focus is on structural drivers and data already collected by the organization, Atalan is also compatible with unionized settings. Alignment with labor agreements and stakeholder involvement should be addressed during implementation planning.

Getting started

How do we get started?

If you are evaluating Atalan, a typical next step is to align on goals, define success criteria, and determine the right scope for validation in your organization.

Common next steps:

Identify priority specialties or service lines
Align on outcomes and success criteria (retention, workload drivers, access, safety, etc.)
Review governance and access requirements
Validate assumptions with a retrospective analysis or scoped initial rollout plan