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How To... Review Data Quality - Periodic Data Quality
Record Volume Update Section

 
More info on Periodic Data Quality Report:
 Record Volume Update Section
 Summary and Data Quality Sections
   

Total Records Submitted

The Total records submitted is a description of the number and percent of records on the transaction file that were submitted to CDC for analysis by the month and year of the child's date of visit for PedNSS and the mother's expected date of delivery (EDD), or last menstrual period (LMP) if EDD is not available, or infant's birth date for PNSS. Individual months are listed only if they comprise > 5% of the total records on the file. The cumulative percent of records should always be 100%.

Rejected Records

Duplicate Records
A duplicate record is a record submitted from the contributor that is mostly or entirely identical to another record in the same transaction file. When duplicate records are identified the first reported record is retained. There are four types of duplicate errors:

  • All fields match is an exact match of all fields on one record to all fields on another record. This can be caused when the contributor selects the same record more than once to be included in the CDC transaction file. Duplicate records where all fields match are more likely to occur when the contributor extracts three separate monthly files and then combines them into a quarterly transaction file. The extract program may not create duplicate records within a month's file, however it may extract the same record on the next month's file.
  • Key fields match is an exact match of key fields. Key fields are defined differently for PedNSS and PNSS; however, they both include fields such as state, substate, date of visit, and individual identifier. For example, in PNSS, duplicate records with key field matches occur when two prenatal only records are selected and extracted for the same woman.
  • Select fields is a match of selected fields. The selected fields are defined differently for PedNSS and PNSS.
    For PedNSS, the select fields include state, substate, child's alphanumeric identifier, date of birth, height (English/Metric), and weight (English/Metric) on more than 1% of records. A match of PedNSS select fields indicates that both records are for the same child, with the same height and weight data, but different dates of visit.
    For PNSS the select fields include: state, substate, woman's alphanumeric identifier and certain combinations of infant's date of birth, LMP and EDD, depending on record type. A match of PNSS select fields indicates that both records are for the same woman and the same pregnancy.

Review list of PedNSS fields used to identify Duplicate Records.
Review list of PNSS fields used to identify Duplicate Records.

Critical Errors
A critical error is a field that has missing or invalid data for the data that are critical for data analysis. Critical fields are defined differently for PedNSS and PNSS.

  • For PedNSS, the critical fields include: state, substate, date of visit, child's alphanumeric identifier identifier, date of birth and the sex. Records are also rejected if the date of visit is not after the date of birth.
  • For PNSS, the critical fields include: state, substate, initial visit date, woman's alphanumeric identifier, and completion code.
  • For PNSS, records are also rejected if the infant's date of birth and date of LMP (last menstrual period) or EDD are all missing or miscoded.

To reduce the number of records rejected for critical errors in both PedNSS and PNSS, ensure that all critical fields are required to be collected by clinic staff. For PNSS, ensure that a woman's postpartum visit date is copied to the initial visit date field on postpartum only records.

Review list of PedNSS fields used to identity Critical Errors.
Review list of PNSS fields used to identify Critical Errors.


Records Replaced on Master File

Records Replaced on Master File indicates records on the transaction file that will replace records already on the master file. This occurs when all key fields match on both transaction and master file records.

If the data quality report indicates that records were replaced on your master file:

  • verify that this transaction file is a replacement file to correct records on the master file
  • verify that the number and % of records replaced is as expected, and
  • if you are unable to verify the records that were replaced, then correct the extract and resubmit the file.


Records Added to the Master File

Records added to the master file includes the number and percent of records from the transaction file that were added to the master file. For PNSS, this includes information on the proportion of complete, prenatal only, and postpartum only records on the file. A lower or higher expected proportion of specific record types can indicate problems with assignment of completion codes. Generally the proportion of complete records should not be less than 50% of records and the proportion of either prenatal only or postpartum only records should not be less than 5% of records. These criterion are based on national PNSS that show about 70% of records are complete records 10% of records are prenatal only records, and 20% of records are postpartum only records. The Completion Code and Record Linkage Errors section of this report provides more information on the types of errors that result in incorrect assignment of a completion code for a record.


Total % of Transaction Records Added to the Master File

Total % of transaction records added to the master file is on the last line of the report summarizes the percent of records from the transaction file that were added to the master file.


Updated Number of PNSS Master File Records

Updated Number of PNSS Master File Records lists the prior years and current year-to-date monthly master file record volume including records from this transaction file that were added to the master file. Some problems that this portion of the PNSS data quality report can help identify are monthly record volume that is not similar to other months in the same year, and current year monthly record volumes that are not similar to prior year monthly record volumes.

If record volume is inconsistent:

  • lower than other months in the same year, confirm that all quarterly files related to these months were submitted
  • higher than other months in the same year, confirm if mass changes were made to clinic or individual identifications creating duplicate records for participants that cannot be identified as duplicates.
  • lower or higher record volume, confirm if a change in the program that extracts the data from the computer information system into the transaction file can explain the difference
  • current and prior year monthly record volume are not similar, confirm if shifts in program caseload can explain the difference

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Page last reviewed: May 1, 2009
Page last updated: May 1, 2009
Content Source: Division of Nutrition, Physical Activity and Obesity, National Center for Chronic Disease Prevention and Health Promotion

 

 



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