Artificial intelligence aids long-term care hiring
How predictive analytics can help healthcare providers find the right employees to reduce turnover risk
By Medline Newsroom Staff | October 7, 2021
This article is part of a series focusing on workforce engagement in post-acute care. The Medline Newsroom will feature interviews with healthcare leaders to discuss their approach to investing in long-term programs that help empower their staff and present them with intuitive tools to provide high quality care.
Sometimes, it seems like pre-pandemic life was so long ago, but many of the challenges severely impacting the long-term care industry over the last year and a half were a constant challenge prior to March 2020. Among the top issues – employee turnover.
Talent is key to an organization’s ability to survive and thrive, and companies like Arena Analytics are utilizing artificial intelligence (AI) to help senior care providers better predict a potential employee’s success in a specific position, and the likelihood of them staying. By doing so, the company is helping care providers hire employees who will thrive within an organization, build successful teams, and ultimately reduce turnover.
The Medline Newsroom spoke with Myra Norton, CEO and President of Arena Analytics, to learn how artificial intelligence is driving effective hiring results in the long-term care industry.
Medline Newsroom: When it comes to hiring, what are some examples of inefficiencies you’ve seen amongst clients that lead to high turnover rates?
Myra: Employers practice unconscious hiring bias, meaning they take cognitive shortcuts to determine if an applicant will be a good fit. In particular, a certain profile of the ideal candidate is established in our heads, such as specific education and job experience. We question when there’s a gap in employment, or maybe the candidate has a unique personality during the interview. But having these biases means we often overlook talented people who may be successful.
When it comes to hiring, employers hire people who look great on paper, but they don’t always meet expectations. The last 18 months have thrown an even more challenging labor market at care providers, but it comes with the opportunity to think outside the box, and for providers to question how and where they’re looking for talent. It is important for the industry to find creative ways to attract talent and give people entry into the long-term care industry. Looking at non-traditional pools of talent can help break the traditional mold of hiring practices. This is where data can help shine a light on the type of candidate who can thrive in an organization, but maybe hasn’t been considered before.
Medline Newsroom: Tell us about Arena Analytics and how artificial intelligence is helping senior care providers evolve their hiring and retention strategies.
Myra: Arena augments existing hiring processes based on outdated information with data-driven insights on candidates tied to positive business outcomes. Our goal is to help employers use predictive analytics––not to replace human judgment, but to enable effective decision making around candidates.
By integrating with a care provider’s current applicant tracking system, we gather historical data on employee hires and terminations, regional job market trends and applicant data from each candidate. This helps them build a profile of their ideal candidate and create custom models for each job role across departments and locations. An ideal employee match is not just about the job role, but also external environments. Artificial intelligence helps organizations analyze more than 10,000 data points per applicant to deliver a customized prediction, before point of hire, on whether the candidate will thrive in that role.
Medline Newsroom: By finding employees who will thrive in their position, what are some of the results you’ve seen with clients?
Myra: By creating a more stable workforce, we can help senior care providers drive better financial and care outcomes, increase team cohesiveness and enhance improvements in staff, resident and patient satisfaction. Across the continuum of care, we’ve integrated predictive analytics at nearly 1,500 communities, and are helping to process nearly 4 million job applicants each year. On average, leveraging predictive analytics for employee hiring has helped our healthcare customers reduce turnover by 21% in the first year.
And yet, finding people during the current labor shortage is no small feat. That’s why we’re encouraging our customers to look beyond their traditional talent pools to uncover hidden talent. Using our Talent Discovery solution, one prominent senior living customer grew their talent pool with qualified candidates who lacked senior living experience and who would have otherwise been overlooked by hiring managers. Upon our recommendation, these candidates were hired and years later are thriving in their respective roles. One woman with an insurance background has been tapped to be the face of a new community opening in the area. Another showed an immediate aptitude for elder care and her employer has offered to pay for her to complete a CNA certification program. A young man who started as a part time dining assistant in high school is heading off to college and considering a future in senior living. It’s deeply gratifying that our solutions can uncover hidden talent and identify where they will thrive. That is how we achieve our mission of expanding access to opportunity to build a more just, equitable and peaceful society.
More senior care leaders are turning to technology solutions to help train, retain and hire quality employees and transform data into efficiencies. For more than 10 years, Medline’s post-acute care sales team has been building partnerships with technology solutions providers, like OnShift, Real Time Medical Systems, HealthStream, abaqis by HealthStream and Hybrent to tackle timely workforce and quality management challenges.
Learn more about how Medline is helping long-term care providers improve operating performance and enhance care initiatives.