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New Data Title: Weekly Treatment Sessions - Actual vs Projected

This visualization presents a synthetic dataset showing weekly treatment sessions for a shockwave therapy service, labeled as Actual Sessions and Projected Sessions over a 12-week horizon. The data are invented to illustrate how usage might evolve under a staged rollout scenario and are not drawn from real clinics or patients. The dimension driving the chart is a temporal sequence: weeks, a common unit for capacity planning and trend analysis in outpatient services. The two curves enable quick comparison between what was observed and what was forecast under a simple adoption model. Actual Sessions are generated to increase gradually, with a modest uptick after week 6 as outreach activities and word-of-mouth effects compound. Projected Sessions reflect a baseline growth path that assumes steady demand and consistent capacity, plus a mild acceleration in the latter half of the period. Differences between the lines highlight timing gaps, potential ramp-up delays, and the impact of external factors such as marketing campaigns, referral networks, or seasonal demand shifts. Methodology notes: The chart uses a standard line plot with two series and a single value per week. The dataset is self-contained and reproducible, intended for demonstration rather than statistical inference. When applying this model to real-world decision making, users should replace the synthetic values with audited clinic data, add confidence intervals, and consider more complex forecasting methods that account for seasonality or regional variation. The visualization aims to support capacity planning, inventory decisions, and service-line prioritization by providing a clear view of how demand may diverge from expectations. Users can export the chart as an image for reports and share it with stakeholders to align on targets, resources, and timelines. Limitations include the small sample size, the absence of patient-level information, and potential biases in the assumed trajectory. Continuous monitoring and periodic reforecasting are recommended to keep the model relevant to evolving conditions. For interpretation, focus on the gap between actual and projected values and investigate root causes such as access to technicians, device downtime, or patient awareness programs. The chart's simple design is intentional to facilitate quick comprehension by executives, clinicians, and marketing teams.