Skilled Nursing Facility (SNF) Operator: Case Study
One of the nation’s largest post-acute care providers, reduced ‘new hire turnover’ by 28% when they leveraged Arena Analytics. Operating 350+ centers and communities in 25 states, they needed to improve quality of care and reduce new hire turnover. Applying predictive analytics and machine learning to the hiring process, they achieved both goals.
SNF’s, also known as nursing homes, provide in-patient rehabilitation and medical care. They employ a wide variety of skilled healthcare providers and frontline staff. Operating over 300 communities across 25 states, this Skilled Nursing system offers high quality care that includes orthopedic rehab, specialized Alzheimer’s care, dialysis, ventilator care, senior and assisted living.
53% of new hires were leaving or dismissed within 180 days.
In order to consistently deliver exceptional quality of care, communities needed to increase retention of the new hires who were most essential in providing this care – nurses and support staff. The loss of over half of new hires so soon after joining the team burdened the staff who remained. They had to be ever more mindful of potential disruptions and inconsistencies that could threaten quality of care. They lost time and energy training yet another replacement for the same position, within short periods of time.
Arena integrated its predictive analytics platform into the hiring process for all nursing and caregiver roles at 25 sites. Arena analyzed candidate, local, and community data, to generate retention predictions. Through an ATS-integration (Applicant Tracking System), Arena surfaced these scores to hiring managers and recruiters for each job candidate, thus informing both their selection and support of new hires.
By selecting ~40% of new hires from the pool of applicants Arena predicted for retention and success, this provider reduced 180-day turnover by 28%. Not only did this reduction translate to reduced costs, but it strengthened and stabilized the entire workforce.
This reduction in turnover translates to 28% fewer re-hires needed. Estimating a lower-than-average cost per hire of $2,500, for the number of hires across 25 sites (120-beds each), the savings are calculated below: