Introducing Data Quality

Chelmsford HEOC

“Data quality is crucial, and the availability of complete, accurate, reliable and timely data is important in supporting patient care, clinical governance, management and service agreements for healthcare planning and accountability.” Trust Data Quality policy

Data Quality (DQ) within IM&T currently focuses on the Trusts CAD provision, Cleric. It is a complex process which ensures that the Cleric data and reporting generated is compliant to the Ambulance Quality Indicators (AQIs), which are used to measure the Trusts performance.

Issues identified by DQ typically consist of process errors, created by users of system and incorrect interpretation of the data, or system errors created by errors within the software itself. Some examples of this are:

  • C1 Misreporting: Due to a system error, a small percentage of incidents are assigned the incorrect ‘Reporting Priority’, which is the ‘Category’ of the incident when the first response has arrived. These incidents are reviewed and submitted to Cleric for amendment. This has consistently improved Trust monthly C1 mean performance by 8 seconds for the last 18 months.
  • Missing Information: Incident times such as ‘At Scene’ can be missed if not pressed on the resources MDT or manually entered by AOC. These incidents do not contribute towards activity (such as number of attendances) or mean response calculations.
  • Manual Entry: Any free text or manually entered data is at risk of human error. For example, if a resource state time such as ‘At Scene’ is entered a for the wrong date, this will cause an inaccurate response time or hospital delay.

Data Quality has created multiple reports and processes to help AOC and Operations teams identify over 40 common Data Quality errors. This has led to over 10,000 individual issues being identified and corrected in the last 18 months, all of which comply with internal governance and were logged to allow regular audit and validation.

If you spot a potential reporting issue or for more questions on Data Quality please email and keep an eye out for future Data Quality NTK articles.

Published 4th June 2020

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