Cardiovascular Signals Dashboard
Population Health Surveillance
Independent analysis of post-pandemic cardiovascular trends in NHS hospital data
This dashboard provides a structured view of emerging cardiovascular signals identified through longitudinal analysis of NHS Hospital Episode Statistics. It is designed to help clinicians, researchers, institutions, and informed observers examine changes in disease trajectories, anomaly patterns, and system-level coherence after the pandemic period.
What this dashboard gives you access to
This is not a general information page. It is a focused analytical environment built to make complex post-pandemic cardiovascular patterns easier to examine. The aim is to move beyond headlines and isolated findings, and instead provide a structured view of how signals are behaving across time, systems, and diagnostic categories.
Trajectory Analysis
Explore annual cardiovascular admission trajectories across the full observation period and identify where post-pandemic patterns diverge from baseline direction.
Anomaly detection
Review codes and clusters showing statistically significant change in magnitude, persistence, or slope, rather than relying on anecdotal impressions.
System-level coherence
See whether apparently separate conditions are moving in parallel, which may indicate a broader physiological pattern rather than isolated noise.
Interpretive context
Access a clinically framed view of the data so that patterns can be considered in terms of relevance, plausibility, and priorities for further investigation.
Why this matters
Large healthcare datasets often contain important signals long before those signals are fully recognised in public discussion or formal guidance. The value of a dashboard like this is not simply in displaying numbers. It is in making it possible to examine whether changes are isolated, sustained, clustered, or physiologically coherent.
For cardiovascular disease in particular, small shifts spread across multiple related codes can be more informative than any single headline figure. A properly framed dashboard helps users identify where further scrutiny is justified, where pattern recognition begins to matter, and where questions should be asked with greater precision.
About Dr Philip McMillan
Dr Philip McMillan is an independent physician-researcher who has developed this dashboard to provide a more structured way of examining post-pandemic disease trajectories within NHS hospital data.
His work focuses on identifying patterns that may otherwise be missed when analysis remains fragmented, overly narrow, or disconnected from clinical interpretation.
This project has been built to support disciplined observation rather than premature certainty. Its purpose is to help users examine signals, understand their context, and assess where further discussion, collaboration, or formal investigation may be warranted.
Enter the data to understand context
The dashboard is intended to help serious users examine post-pandemic cardiovascular signals in a structured way. Begin with the data, or arrange a discussion if you want a more focused walkthrough of the patterns and their possible significance.