Standards and Guidelines for Electronic Medical Record Systems in ...

formats and ranges. This may be achieved through automated procedures for range
checking where the data element is validated against a range of allowable values for that
element, and by finding missing data for required fields. First order validation detects
obvious data entry errors, while leaving more complicated errors for data managers to
resolve asynchronously. For example, the EMR system checks the entry for hemoglobin
levels against the normal range to prevent erroneous outliers.
2. Second order validation is the historical comparison for the same data element so that an
alert is prompted if an indicator increases or decreases abruptly. For example, an EMR
system should flag an abrupt increase in weight from 50 to 70 kgs within a one-month
period.
3. Third order validation assesses data elements for consistency within a specific form or set
of indicators. For example, a red flag would be raised if the number of women receiving
PMTCT services was larger than the number of pregnant women treated for a given time
period.
4. Fourth order validation is the assessment of any statistical outliers (which may or may not
be accurate). This function is traditionally performed by an epidemiologist or statistician in
the course of cleaning a data set for analysis.
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