Many healthcare organizations have been stung by staffing shortages that continue to swell. These effects can be felt at the unit-level of patient care facilities, where difficulties in scheduling and staffing of registered nurses are rising.
Unsure of what's to come in 2017 and the changes that will directly affect the healthcare industry, healthcare providers can ensure the well-being of their organization and staff, as well as the quality of care for the patients they serve, by engaging strategies that optimize their workforce.
Knowing that there is not an army of RNs over the horizon coming to the rescue, healthcare providers are tasked with making the best use of the staff they already have, and ensuring the right people are in the right places at the right times. This can be a complex and time-consuming process for managers, who could be devoting more of their valuable time elsewhere on their unit. Coordinating around-the-clock delivery of care is inherently complex and takes an ability to predict future needs.
With the announcement by President-elect Donald Trump to repeal the Affordable Care Act (ACA), many provider organizations have found themselves in a state of uncertainty. In healthcare, uncertainty often promotes indecision. Top healthcare organizations are focusing on what they can control while awaiting the fate of the ACA.
To reduce uncertainty, one key element that can be wrapped into an organization's workforce planning is predictive analytics. Within this process, forecasting models are created and validated, allowing workforce projections of staffing needs up to 120 days prior to the shift. The forecast is updated weekly, and by 30 days before the shift, the forecast of staffing need is 97% accurate.
Short of peering into a crystal ball, this degree of accuracy is substantial and can have positive effects on many aspects of the organization such as staff morale, patient satisfaction -- and the bottom line. Nurse managers worry about how staffing challenges hurt their staff, and are concerned that inadequate staffing negatively impacts patient satisfaction. Predictive analytics helps to alleviate this pressure on managers about how to appropriately use their staff, and the benefits have a ripple effect that can be felt throughout the entire organization.
Predictive analytics is not a new concept. The technology-enabled solution is already being utilized in various industries outside of healthcare — manufacturing, transportation, and financial services. It is weaving its way into healthcare, yet is not being widely used. In fact, according to a study conducted by AMN Healthcare and Avantas, 80% of nurse managers are unaware of available technology that can accurately forecast patient demand and staffing needs. Moreover, 90% stated such technology would be helpful in the daily scheduling and staffing of nurses.
This sophisticated forecasting of labor needs is grossly underutilized in the healthcare industry, lying dormant in an area in which it can have a dramatic impact. Predictive analytics can lay the foundation for significant advancement in the use of staff, turning an accurate forecast of needs into the bedrock of an effective resource management strategy. And the timing to employ such a strategy could not be better. While staffing shortages continue to be felt in provider organizations across the country, the time to leverage the staffing resources you already have is now.
Not a stand-alone solution, the forecast is the first step in the process. Knowing how much staff is needed to handle demand is far from actually being able to staff to that demand, and to do so in a cost-effective and sustainable manner. There are a thousand moving parts to consider as the weeks tick by and time reveals how the right staff member gets to a patient's bedside. Predictive analytics provides organizations with the blueprint they need to leverage the resources they have while maintaining high-quality patient care.
So while healthcare organizations peer into the unknown of what is to come in 2017, the data derived from predictive analytics can give clinical leaders a degree of comfort and control of being able to predict staffing needs and fill shifts appropriately.
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