Dashboard Designed by Kelly Emrick, DHSc, PhD, MBA
How Do I Use the Dashboard? To use the dashboard, select the ordering pathway that best matches the reality you are modeling: Outpatient, Inpatient, ED, Emergent Add-ons, or Oncology. Each pathway experiences the workflow differently in both pacing and friction. Then walk through the stages from order entry through report distribution, billing, and QA, and enter realistic values for the levers at each stage. In practical terms, you will adjust a stage’s active time (hands-on minutes), calendar delay (waiting time between steps), capacity (how many cases that stage can realistically handle per day or per shift), and any defect or rework burden (repeat calls, missing information, protocol changes, patient tolerance issues, rescans, or documentation gaps). As you adjust the levers, the dashboard immediately recomputes utilization, pinch point flags, and pathway-level throughput pressure, enabling you to test improvement ideas in seconds. A good operating routine is first to load baseline values that reflect current performance, then run a few focused scenarios: increase capacity where you can (staffing, scanner time, transport coverage, protocol standardization), decrease rework where you must (order quality, screening completeness, sedation readiness, contrast safety steps), and compress delays where you have hidden queues (prior authorization lag, scheduling backlogs, imaging transfer processing, reading backlog). Use the CSV export to snapshot the current scenario, share it with leaders, or compare before-and-after states.
What Does the Dashboard Tell Me? The information shows where the workflow is structurally tight, where time is being consumed, and where risk concentrates as volume rises. It does so by separating “work time” from “wait time” and by showing whether a stage has enough capacity to absorb demand without forming a queue. The utilization-by-stage view serves as a heat map for identifying constraints: taller bars indicate a stage approaching its practical limit, where small disruptions can cause outsized downstream delays. When a stage is flagged as a watch or critical pinch point, the model signals that the stage’s capacity plus its defect and rework burden cannot reliably keep up with the pathway’s demand assumptions, so you should expect symptoms like schedule instability, add-on stacking, delayed starts, prolonged table time, delayed reads, or late report delivery. The pathway lens helps you interpret why the same stage behaves differently across settings; ED and emergent add-ons often show sensitivity to transport, protocoling speed, and scanner availability, while outpatient pathways frequently reveal delays in authorization, scheduling, and pre-scan screening readiness. Oncology pathways commonly expose coordination friction and priority conflicts that drive rework and interruptions. In short, the dashboard not only shows where the workflow is slow; it also explains why by identifying which stage variables are causing congestion, and it quantifies which levers are likely to deliver the greatest reduction in delay and variation with the least operational disruption.