Predictive Analytics: Precision Planning for Healthcare’s Most Important Resource – Its People

Guest post by Jackie Larson, president, Avantas.

Jackie Larson
Jackie Larson

Predictive analytics and advanced labor management are the most important – and underutilized – methods to assure that provider organizations have the right caregivers in the right places at the right times.

A recent survey of nurse managers by AMN Healthcare and Avantas, Predictive Analytics in Healthcare 2016: Optimizing Nurse Staffing in an Era of Workforce Shortages, (available on the AMN website) brought the need for more awareness to light in just a few stats related to staffing and scheduling:

The survey also revealed a lack of sophisticated scheduling tools being utilized:

Further, the survey found that while nearly 90 percent of nurse managers said that a technology that can accurately forecast patient demand and staffing needs would be helpful, 80 percent were unaware that such a solution exists.

Strategies to Fulfill the Potential Predictive Analytics

This process to predict future patient demand and strategically plan clinician scheduling and staffing is scalable, cost effective and accurate. First, staffing data are processed with advanced algorithms, then forecasting models are created and validated, customized for each unit or service area within the organization, allowing workforce projections up to 120 days prior to the shift. The forecast is updated weekly, and by 30 days in advance of the shift, the forecast of staffing need is 97 percent accurate.

Compared to how scheduling and staffing is conducted at most healthcare organizations today, predictive analytics may seem like something out of a sci-fi movie. The truth is, this sophisticated forecasting of labor needs has been leveraged in other industries with great success. And, in healthcare, it can lay the foundation for significant advancement in utilization of staff, leading to improvements in morale, quality, and financial results. The advanced labor management strategies and tools layered on an accurate projection of staffing needs – months and weeks in advance of the shift – will turn an accurate forecast into an effective resource management strategy.

Adopting Workforce Analytics
Every organization’s staffing mix should be unique to the fluctuations in its patient volume. Once an organization understands its demand, it can then determine its supply – scheduling and staffing to meet patient demand in the most productive manner possible. The organization can analyze and solve the problems that reduce its available supply of core staff, such as leaves of absence, continuing education, training and other issues. This precision understanding of workforce availability is then layered with patient volume predictions, and the result is accurate insight into the core and contingency staffing levels needed to meet patient demand.

Proactive Open Shift Management
The use of predictive analytics to forecast staffing needs in advance can lead to an effective open shift program that rewards staff for picking up shifts several weeks in advance. When incentives are used to fill open shifts, those incentives should be at their peak 30 days out from the shift and decline in terms of dollars – rather than increase – as shifts are picked up and as the date of the shift approaches. This method creates a disincentive for nurses and other clinicians to wait until the last minute, hoping the amount of incentive pay might increase – a reality that plagues far too many provider organizations.

The Path toward Mastery
Everyone agrees on the need to be strategic in managing their workforce to deliver quality patient care. But while most chief nursing officers, clinical managers, finance directors and nurses may realize that current scheduling and staffing practices are inefficient and often ineffective, they may not realize that change can be made by focusing on the incremental steps that will lead to transformation.

As basic strategies become habit, the movement toward full implementation of predictive analytics and advanced labor management practices becomes a natural progression to mastery. Adopting predictive analytics and advanced labor management requires a change in thinking in how managers can best improve patient care, staff morale and the bottom line through precision management of healthcare’s most important resource – its people.

Write a Comment

Your email address will not be published. Required fields are marked *