The American healthcare system faces any number of challenges, from securing medical reimbursements from the government to keeping hackers out of its medical records. But hospitals face another big challenge that is significantly affecting their operations: staff turnover.
Up to half of healthcare workers leave their jobs each year, says Jeffrey A. Sachs, principal of the Sachs Policy Group, a New York City-based boutique consulting firm that advises healthcare leaders on policy, trends and business strategy.
In an effort to better retain staff, some providers are turning to recruiting and talent acquisition technologies such as Arena, formerly Pegged Software, which promises, through the use of predictive analytics, to reduce health systems’ early stage turnover rates by 10%.
Arena, which specifically targets health systems, collects information from three buckets — third-party data such as public-facing figures from sites such as LinkedIn and Glassdoor that make up a small portion of its data set; background information, such as job descriptions, gleaned from resumes submitted by candidates at the 486 facilities Arena works with; and interaction data, such as the answers applicants fill out on a questionnaire that appears to be an assessment test — and compares it to the outcomes of long-term employees. The company says it follows California’s rules for protection of personally identifiable data and complies with any additional requirements at state and federal levels.
An Arena algorithm takes all the data and runs comparisons between high-achieving individuals and applicants as a means to predict quantifiable outcomes, such as success in the position and likelihood that the newly hired employee stays with the health system for a long period of time.
Although applicants may apply for a specific position, the algorithm also can find the department that best suits an employee’s strengths and skills. For example, if nurses apply for an operating room position, the algorithm may predict that some will not perform well in that environment or choose to leave after a year. Arena’s technology will then suggest those people work in a different department, such as critical care.
Arena grew out of the technology built at CEO Michael Rosenbaum’s first company, Catalyst, a software engineering services firm. He saw that health systems were struggling with retention and knew he could leverage Catalyst’s predictive algorithms to improve their turnover rates.
One of the first providers Rosenbaum licensed his technology and services to was Adventist HealthCare Shady Grove Medical Center in Rockville, Md. Within the first year of using Arena, Shady Grove’s retention rate improved fivefold.
Adventist HealthCare isn’t alone in seeing turnover decrease when using Arena.
Regional One Health, a teaching hospital and the only Level 1 trauma center within 150-mile radius of Memphis, has more than 3,000 employees spread out through its East Memphis campus, extended care hospital, outpatient clinics, primary care network, regional medical center, rehabilitation hospital and surgery center. It also had a 20% turnover rate before enlisting Arena’s help in 2013.
“We were the only hospital in the area not using a pre-employee assessment,” says Carol Farris, director of talent acquisition and management at Regional One Health. “One of the things I wanted pre-employee assessment to do was help the recruiter screen the applicant out if the applicant didn’t have the skills, aptitude or prior experience needed.”
The health system looked at several technology offerings, none of which were specific to the health industry, which Farris says is “driven by different [employee] motives.”
“That was one of the reasons why Arena appealed to us,” she says. “They developed and designed that tool and system that could really capture the unique characteristics of successful healthcare employees.”
By the end of the 2017 fiscal year, Regional One Health’s turnover rate fell to 13.9%, a 6.1% decrease from 2013, and is expected to fall a percentage point each year thereafter, Farris says.
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