Recruitment & Retention: Predict & Hire for RN Attrition (ODW5045)-Predict and Hire for RN Attrition Presentation

Predict and Hire for RN Attrition Presentation

Pdf Summary

This presentation by Bill Lecher, DNP, MBA, RN, NE-BC, Director of Nursing at Health Carousel, addresses the critical issue of registered nurse (RN) attrition and offers a predictive hiring strategy to improve recruitment and retention. The national nursing workforce faces severe challenges: RN supply in 2021 fell nearly 200,000 below forecasts; hospital RN employment is at an all-time low; nursing school applications and enrollment are stagnating due to faculty shortages, with significant numbers of qualified applicants turned away annually (~65,000 in 2024). First-year RN turnover is high, around 20-30%, driven by mentorship gaps, burnout, work-life balance, and pay concerns. The cost of RN turnover is rising sharply, averaging $61,110 per nurse in 2025, including separation, hiring, training expenses, lost productivity, and increased use of costly overtime or contract labor.<br /><br />Hospitals currently mitigate shortages by increasing unlicensed assistive personnel (UAPs), overtime, workforce redesign (top-of-license practice, reintroducing LPNs, virtual nursing), flexible staffing with travel nurses, and hiring international nurses converting to full-time roles. However, these are mostly reactive measures.<br /><br />Lecher advocates for "hiring for attrition," a proactive staffing model that predicts RN separations (terminations, transfers, and promotions) based on historical data by unit. For example, Unit 5’s attrition trends indicate 2.4 RN full-time equivalents (FTEs) will need replacement next quarter, allowing advanced recruitment to avoid costly staffing gaps, premium pay, and increased patient ratios. This data-driven method is budget neutral and enhances staffing stability, manager satisfaction, and reduces reliance on expensive temporary staff.<br /><br />The five-step predictive attrition process includes tracking terminations, transfers, monthly historical attrition data, calculating expected separations, and acting with targeted recruitment. This approach also emphasizes accounting for inter-unit transfers and promotions, often overlooked yet significant for staffing needs.<br /><br />Lecher encourages dissemination of this model through webinars and organizational presentations to nursing, HR, and financial leaders to embed predictive hiring into workforce planning and retention strategies. This method offers a practical solution to stop the cycle of delayed hiring and nurse shortages—ultimately improving patient care, financial stability, and nurse job satisfaction.

Keywords

registered nurse attrition

predictive hiring strategy

nursing workforce shortage

RN turnover rate

nurse retention

staffing stability

healthcare recruitment

workforce planning

nurse burnout

data-driven nursing management