Unlocking the Power of Audit Tables: Lessons from Episode Tracking

When working with complex systems—like healthcare management platforms—having an audit table can be a lifesaver. These tables, which record every change to a record, often contain hidden gems of insight. But querying them effectively requires some care. Here’s what we learned while analyzing episodes in a clinical system.

The Challenge

At first glance, extracting open and close dates for episodes might seem straightforward. You’d think you could simply pull CreateDate and CloseDate from the main table. But in practice, quirks arise:

Close dates aren’t always populated. Some systems only store the closing action in the audit table, leaving the main table’s CloseDate blank.

Multiple status changes occur. An episode may open, close, and reopen several times. Which date should you pick for reporting?

Aggregating properly is tricky. You need to consider whether you want a summary per episode or to see every audit record individually.

How Audit Tables Help

This is where audit tables shine. By recording every change, along with timestamps and user information, they allow you to:

Reconstruct the lifecycle of a record with precision.

Detect episodes that were reopened or modified after closure.

Track how often and by whom changes were made.

Calculate meaningful metrics like days open, even when the main table lacks this information.

Lessons Learned from Querying

-- Demo: Calculate Open and Close Dates from an Audit Table
SELECT
    ea.AuditID AS EpisodeID,
    MIN(ea.ChangeDate) AS OpenDate,          -- earliest change = open
    MAX(ea.ChangeDate) AS CloseDate,         -- latest change = close
    DATEDIFF(DAY, MIN(ea.ChangeDate), MAX(ea.ChangeDate)) AS DaysOpen,
    CASE
        WHEN MIN(ea.ChangeDate) = MAX(ea.ChangeDate) THEN 'Open'
        ELSE 'Closed'
    END AS EpisodeStatus,
    COUNT(c.ID) AS ClinicalNotesCount,
    d.Description AS Disease
FROM EpisodeAudit ea
INNER JOIN Episode e
    ON ea.AuditID = e.ID
LEFT JOIN ClinicalNotes c
    ON e.ID = c.EpisodeID
INNER JOIN Diseases d
    ON e.Disease = d.ID
GROUP BY ea.AuditID, d.Description
ORDER BY CloseDate DESC;

When we built queries to analyze episodes:

Open dates can be derived from the earliest change. By taking the MIN(ChangeDate) per episode (or audit ID), we reliably identify when an episode first appeared.

Close dates can be derived from the latest change. MAX(ChangeDate) provides a logical “end” of the record, even if the official close field is empty.

Flagging open vs closed episodes is simple. If the first and last audit records are the same, the episode is still open.

Joining with related tables adds context. Including disease descriptions or clinical notes counts makes the dataset much more valuable for reporting.

Best Practices

Always use JOINs carefully when combining the audit table with the main entity or related tables to avoid double-counting.

Consider window functions for calculating durations without aggregating away individual changes.

Document your assumptions—like which ChangeType corresponds to “closed”—so your analysis is reproducible.

Conclusion

Audit tables may seem like just a historical log, but they are an incredible resource for understanding system behavior. With careful querying, they let you reconstruct events, calculate durations, and generate insights that wouldn’t be possible from the main tables alone.

Next time you encounter missing or inconsistent dates in a system, don’t panic—chances are, your audit table holds the key.