Workforce optimization is a pain point for many provider organizations. Constrained labor resources, inconsistent policies and a lack of tools can create staffing challenges and stress, which can create a cycle of burnout and turnover that can negatively impact quality and patient satisfaction scores and cause costs to skyrocket.
The root of ineffective resource management primarily stems from a lack of clarity into future patient volume and inability to coordinate the right staff to effectively meet demand. Knowing how many and what types of staff are needed weeks in advance of the shift exists today, offering provider organizations an accurate glimpse into the future of patient demand. Predictive analytics provides a solution that enables organizations to align staff to patient demand in a cost effective and sustainable manner.
Using time-series mathematical modeling, predictive analytics uses an organization’s historical data to forecast patient demand up to 120 days in advance of the shift. Within 60 days of the start of the shift, the prediction is within one staff member of what is actually needed with 96 percent accuracy. Predictions are constantly being updated as new census information is received, improving the accuracy to 98 percent at 24 hours prior to the start of the shift.
Effective workforce planning begins with an advanced forecast of needs. Patient volume prediction is the blueprint. It provides a future snapshot of what the shift will look like relative to volume and the supply of caregivers needed based on that volume.
Automating the scheduling process with technology and utilizing advanced analytics to glean actionable insights helps unit managers monitor productivity and budgeting targets, guiding their staffing decisions. Having access to real-time data such as actual hours worked and labor costs allows unit managers to make any necessary staffing adjustments.
One health system that is reaping the benefits of predictive analytics is Mountain States Health Alliance. In their 2017 fiscal year, they realized a $10 million savings in labor management primarily by taking actions based on their analysis of outcomes and trends from actual hours worked and associated costs for each unit utilizing predictive analytics technology. Additionally, leadership has made it a priority to hold staff accountable for workflows by creating standard work processes.
This level of success takes dedication and focused effort to implement a new process and gain organizational buy-in. Having a core team of champions who are able to communicate the reason for change and hold each staff member accountable to driving its success will help lead the organization to the desired outcome.
The core labor management team at Mountain States Health Alliance has taken the time to analyze and understand their workforce data to present it to managers and staff in an actionable and relatable way. Their transparency and coaching empowers managers to make good staffing decisions. Further, the team serves as a liaison to bridge the gap between finance and clinicians, helping each department understand the issues of the other and providing solutions that is best for all.
Leveraging predictive analytics and advanced technologies can supercharge an organization’s path toward creating a sustainable and cost-effective workforce management strategy. Bringing this vision into reality is not a quick or easy fix. But it is a process worth the effort as gaining a shared vision among key stakeholders from cross-functional areas and focusing on change management and buy-in protocols are critical components of reaching the desired state of workforce optimization.
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