In this whitepaper, we break down the patterns behind nurse call-ins and what they could mean for a more predictive approach to staffing.

Inside you'll find:

• Why most call-ins leave staffing teams with limited time to respond, and which days and shift times carry greater risk
• How call-in risk varies across the workforce, including patterns by tenure, role, and concentration among more frequent callers
• Why a nurse's first shift back after time off is one of the strongest signals of elevated call-in risk
• What rejected swap requests can reveal about an upcoming shift before a coverage gap occurs
• Which seemingly intuitive factors, including overtime exposure, do not show higher observed call-in risk
• How health systems can bring these signals together to move from reactive coverage toward predictive staffing

Download the whitepaper to see what nearly 1.9 million nursing shifts reveal about call-in risk, and how those patterns can help health systems build staffing plans that are more likely to hold.

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