Sample: clinic data quality audit

Sample article format. The numbers are illustrative and should be replaced with real source exports before publishing.

The first pass on a healthcare data project is usually not a dashboard. It is an argument about what the data can support.

This format is for a case-style post where the story is: what did we think the report meant, what did the raw data actually contain, and which metrics are safe enough to use?

The question

Can a clinic-facing compliance report be trusted for daily operating decisions, or is it mixing clean-looking metrics with partial source coverage?

Figure 1. Illustrative source coverage by field. A field can look present in the UI while still being incomplete in the export.

Active census 96%

Plan status 78%

Payor detail 63%

Counselor assignment 41%

What changed

The important move is to separate supported metrics from tempting metrics. If the field is incomplete, it should not become a headline KPI. It can be used as a caveat, a quality issue, or a prompt for source repair.

Metric	Use	Reason
Census	Headline	High source coverage and stable operational meaning.
Payor mix	Secondary	Useful, but plan labels require interpretation.
Counselor load	Do not headline	Partial assignment coverage makes ranking misleading.

The post would end with the operational recommendation: what stays on the dashboard, what gets demoted, and what data repair has to happen before the next version.