How Predictive Data Analytics Can Help Improve Nurse Retention

Nurse recruitment and retention have always been critical issues, but healthcare leaders have increased their focus on this issue after the COVID-19 pandemic. Recruitment is a costly affair! According to The Journal of Issues in Nursing the cost to replace a departing nurse is .75-2.0 times annual salary. The Bureau of Labor Statistics reports the average registered nurse salary in the U.S. is $82,750. Califorina has the highest RN salaries averaging $124,000. This means the average hospital loses $5.2 million to $8.1 million annually through nurse turnover (Relias Institute).

Healthcare centers need to find innovative solutions and go beyond traditional productivity analysis to retain nurses. The use of advanced workforce analytics that combines machine learning and big data to run predictive analyses can help reduce workforce turnover. But how, exactly? Let’s look at how predictive analytics tools can help.

Adopt a proactive recruiting model

In a traditional recruiting process, managers only initiate the hiring process when a position becomes vacant, or a new position is created. But even after a candidate is hired, they still need to complete a training and orientation program to become fully competent. During this ramp-up period, the position is often filled with premium pay, agency staff.

But with the predictive analytical model, you can predict a need for hiring. This proactive recruitment model, where the hiring process begins in anticipation of the need, reduces the time from when the need arises to when the position is filled. Using data like historical demand of the workforce, employee turnover, training needs, and more, you can create plans and forecasts to facilitate workforce and succession planning.

Address concerns that are reducing employee engagement

Employee engagement measures the relationship between an organization and its employees. It shows how passionate employees are about their work and how committed they are to your organization’s mission. Highly engaged employees connect with the organization’s goals on a deeper level and are less likely to leave.

Using the workforce analytics solution, you can measure the engagement of your nurses at the individual level and identify the most engaged and disengaged employees. With these insights you can understand engagement trends within your workforce, identify the cause of their concern, and design a solution to tackle the issue.

Use behavioral analytics to best match employment candidates with positions

Organizations often complain about high-quality nurses leaving their hospitals within just three months of being hired. They receive extensive training – a heavy cost and inconvenience to patients and other staff members. These early departures can happen through recruitment failures or new employees are placed in the wrong position.

Using predictive talent analytics and big data, one can identify the right candidate for a particular position. It starts by determining the characteristics of top-performing employees and discovering the best-suited candidates for the job role. Analytics will determine Skill Score, Success Profile Score, and Propensity to Accept an Offer Score. These insights will help you to determine the fit of a candidate for the position you are filling.

Improve employee experience through analysis of employee surveys and appraisals

Conducting employee surveys allows you to understand employee satisfaction levels and company culture. It gives you a clear understanding of how your employees view the organization and provide valuable insights to further improve the work environment. Higher employee experience levels translate to lower employee attrition rates

With the help of text mining and machine learning techniques, you can analyze data that is often underutilized, such as the text data provided by employees in surveys and performance appraisals, and work on enhancing your nurse experiences further.

Nurse retention is highest in organizations which have a strong commitment to engage their staff. With the help of big data, you will be able to clearly see what things are most important to your nursing staff. Focusing on these will increase engagement levels and reduce nurse turnover.

How do you get started?

Getting access to consolidated data and wrangling the tools needed to analyze this data can be a daunting task for healthcare organizations already swamped with the day-to-day activities of caring for their patients.

The good news is that there are partners available to help. The best place to start is to reach out to one of these partners and, with their help develop a roadmap to improve your use of analytics and big data, generate key workforce insights, and with these insights, begin bringing down your nurse turnover rate.