Using Reports to Drive Data Quality

Data Completeness: Completeness is defined as the “visit’s full set of data,” not the capturing of a single record  (message) or “last message only.” Data are considered across all messages associated with “the visit” to determine whether data in the field are missing. Record-level completeness is also included.

Data Timeliness: Reports and graphs note timeliness of visit-level data for either 24- or 48-hour periods. To calculate lag time, date/time of first message (for a visit) to arrive on the BioSense Platform is considered versus date/time of patient visit. (Note: Subsequent messages for the same visit are not included in the calculation.)

Data Validity: Reports show conformance to PHIN vocabulary standards and describe elements that do not adhere to standards but might have unusual values (e.g., age, temperature). Data either do or do not conform, and supporting reports specify the value of conformance. Missing data elements are categorized as nonconforming. Reports provide record-level information. Reports also include visit-level information by collapsing data across records and by using the same logic applied to downstream ESSENCE processing.

Questions about your site’s data quality? NSSP’s data support staff are available for one-on-one consultation. Contact the NSSP Service Deskexternal icon to set up a meeting.

Page last reviewed: September 24, 2021