Designing Dashboards for Public Health Leaders

Dashboards should answer the right questions at a glance. Start by naming the decisions the dashboard will support and the outcomes that matter; the checklist in choosing outcomes that matter keeps measures grounded in plain English. Because most dashboards rely on routine data, set expectations with real‑world evidence in healthcare decision‑making and make input quality visible using a small “data notes” box per panel (see basics in EHR data quality for real‑world evidence).

Decision‑first design

Write one line per panel: the decision it supports and who owns it. Use a short headline (“Timely day‑10 postpartum BP checks rose from 42% to 67%”) and one chart that carries the point. Add a one‑sentence takeaway and a “what we changed” box with owners and dates. For policy‑facing versions, mirror the concise structure in translating epidemiology for policymakers.

Keep measures simple and frozen

Pick 5–10 measures tied to goals and contracts. Freeze definitions and denominators; publish them in plain language. Pair outcomes with their drivers (e.g., day‑10 postpartum BP checks ↔ interpreter‑first outreach and transport vouchers). For narrative framing, see data storytelling for funding.

Equity baked in

Add built‑in stratifiers: language, race/ethnicity (when collected), payer, neighborhood, rurality, and age. Show crude and adjusted views side by side. Suppress small cells; annotate where suppression applies. When gaps appear, link to an action plan that uses capacity‑matched lists and scripts from AI for population health management.

Essential chart types

• Run/control charts for trends and stability
• Funnel plots for site variation (volume‑aware)
• Small maps for geographic patterns (with clear legends and accessible colors)
• Bar charts for subgroup comparisons (ordered, with CIs where helpful)

Avoid clutter: one idea per chart; clear labels; readable ranges; no 3D or superfluous gradients. Add short tooltips or footnotes for definitions and data notes.

Accessibility and readability

Use high‑contrast palettes; avoid color‑only encoding; label lines directly; keep alt text descriptive (say what the chart shows). Target an 8th–10th grade reading level. Make keyboard navigation and screen‑reader semantics work.

Cadence and ownership

Create a weekly 30‑minute huddle to review two measures and pick one change to test. Hold a monthly 50‑minute review to scan trends, subgroup gaps, and “what we changed.” Archive panels that do not drive action. When a change requires stronger evidence, elevate it to a pragmatic design per pragmatic trials and RWE: better together.

Example panel: postpartum follow‑up

Headline: “Timely day‑10 postpartum BP checks rose from 42% to 67% after interpreter‑first outreach and Saturday clinics.”

Elements:

• Run chart (weekly) with an annotation marking changes
• Funnel plot of sites with volume context
• Subgroup bar chart by language and neighborhood
• “What we changed” box with owner names

Common pitfalls (and fixes)

• Decoration over decision → write the decision per panel; remove distracting elements.
• Moving definitions → freeze and publish plain‑language definitions.
• Equity as an appendix → build subgroup views into every panel; plan remedies.
• No owners → add a “what we changed” box with names and dates.

Implementation checklist

• Phrase decisions and pick 5–10 measures; freeze definitions.
• Add equity stratifiers; suppress small cells; show crude and adjusted.
• Use one headline and one chart per panel with a “what we changed” box.
• Publish data notes; review weekly and monthly with owners.
• Elevate big changes to pragmatic evaluations when needed.

Key takeaways

• Decision‑first panels with frozen measures and equity views drive action.
• One headline and one chart beat cluttered pages.
• Ownership and cadence keep dashboards alive and useful.