Equium forecasts upcoming workload and work intensity to enable intelligent workflow, scheduling, and staffing decisions. Maximize productivity and efficiency while reducing burnout.
Intelligent forecasting enables longer-term scenario planning for hiring decisions, equipment purchases, and staff allocation.
Staffing shortages lead to delayed patient care and provider burnout. Equium helps practices intelligently manage staffing levels to optimize productivity and efficiency while enabling greater scheduling flexibility to maximize work-life balance and reduce burnout.
resourcEQ uses machine learning and deep learning algorithms to predict optimized scan durations, identifying scheduling gaps to increase scanner utilization.
Improved scanner utilization reduces patient wait time, avoids delays in patient care, and decreases scheduling backlogs.
Real-time forecasting of scan durations, missed appointments, add-ons, and cancellations provide insights for schedule optimization to accommodate delays and reduce staff overtime.
Empower administrators and schedulers with automated machine learning to extract actionable insights and boost resource effectiveness. Daily volatility and uncertainty require quick and decisive action. Adapt your resources and scheduling to short- and long-term forecasts to stay ahead of shifting demand to create a high-performance environment.
resourcEQ provides an early warning forecast into upcoming disruptions in workflow, enabling you to prepare and intervene proactively.
Hotspots from abrupt surges in imaging orders can lead to backups, increased patient wait times, increased turnaround times, and delays in patient care. Scheduling gaps due to cancellations, late arrivals, or missed appointments are inefficient and costly. Instead of playing catch up and reacting to these anomalies, resourcEQ’s demand forecasting and dynamic surge protection can predict these hotspots and gaps to allow proactive scheduling and staffing adjustments to mitigate surges and fill in gaps. Make better-informed decisions with the help of machine learning, enabling your practice to optimize and balance workload with workforce capacity.