Group codes carry a check digit, so they cannot be made up — generate one here, then read it to the room. Anyone entering it lands in this group.
You will see the patients held by these students combined — not the whole 54,000-patient cohort. That keeps the room's numbers the ones the students are actually looking at.
Your panel
Read this to the room. Anyone who enters it joins this group.
| # | Patient region | Patients |
|---|
Give each student their number. Nobody shares a patient with anybody else.
Only pairings checked against the cohort when it was built can be drawn. The rest are grayed out with the reason, rather than drawn, because a chart of noise still looks like a finding.
The same tool as Part 3, with housing status and social vulnerability added as groupings. Both need more patients than one panel holds, so this box opens at all campuses.
Across the students enrolled in this group.
Prevalence of each Elixhauser condition among these patients.
Pick a condition to see the same summary for only the patients who have it. Conditions held by fewer than 30 patients in scope are not offered — below that the sub-group cannot carry its own distributions.
These associations do not show cause. They come from simulated data built on patterns observed in a real de-identified population. A difference between groups is a prompt to ask why a health system might produce it — not evidence that one thing produced the other.
Every term used in this session, in plain language. Terms are also underlined in the interface — select one to see its definition where you meet it.