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Data quality

Our Role in Data Quality

The Health and Social Care Act 2012 (section 266) states that the HSCIC's statutory data quality role is to assess the extent to which the data it collects meets defined national standards and to publish the results of the assessments. In addition, the HSCIC may give advice or guidance on data quality relating to the collection, analysis, publication or other dissemination of data and information.

Our pdf icon Data Quality Assurance Strategy 2015-2020 [47kb] sets out how we will fulfil these responsibilities.

Assurance and Governance

DQA Steering Group

Data Quality Assurance (DQA) activity is governed by the DQA Steering Group who meet every two months to provide overall strategic direction for DQA. The Group is made up of internal members, as well as external representatives from Care Quality Commission, Department of Health, NHS England and NHS Improvement. We are working to ensure that the provider community are also represented at the DQA Steering Group. The Group's pdf icon Terms of Reference [571kb]  are available for reference, and any queries about the group should be directed to

DQA Provider Forum

A DQA Provider Forum meets quarterly with representatives from 12 provider organisations from around the country. The Forum is in its early stages and is soon to be supported by a national Provider E-Forum enabling further engagement from the 200+ interested parties that have raised an interest in being involved.

DQA User Forum

The DQA User Forum meets quarterly with representatives from a number of Clinical Commissioning Groups (CCGs), Commissioning Support Units (CSUs), NHS England and the Care Quality Commission (CQC). The Forum is in its early stages but has already seen some very positive actions come out of the first meeting to proactively support the improvement of data quality.

HSCIC Data Quality Work Programme

Data Quality Maturity Index

xls icon The Data Quality Maturity Index (DQMI) [546kb] is a new quarterly publication intended to raise the profile and significance of data quality in the NHS by providing data submitters with timely and transparent information about their data quality. The first publication is a start point set to engage the health system in the quality of core data items. Future versions of the DQMI will focus on a wider range of data fields contained within the initial 6 datasets used, along with further DQMIs to cover additional datasets submitted nationally by providers.

The xls icon DQMI [546kb] is a data quality value index based on the completeness and validity of key data items agreed through the National Information Board (NIB) data quality group, these include NHS number, date of birth, gender, postcode, speciality and consultant code, amongst others. For a full list please refer to the pdf icon Methodology. [377kb]

See the DQMI Distribution Chart for a quick preview of how the scores are distributed.

DQMI_Distribution_Chart_Image Displays a larger version of this image in a new browser window

The first publication of the index (24 May 2016) is based on calendar year 2015 data. Subsequent publications will develop the index and include quarterly data from 2016/17 forwards. The first publication includes data from the following datasets; Admitted Patient Care, Outpatient, Accident and Emergency, Mental Health, Improving Access to Psychological Therapies (IAPT) and Diagnostic Imaging. 

The index will be continuously improved and refined from engagement with stakeholders including fellow arm's length bodies, government, commissioners and data providers. The HSCIC is also providing supportive tools and information to enable data providers to investigate and analyse areas of concern in regard to their data quality -see the Data Quality Reporting Tool Prototype

As the use of electronic records grows in the NHS, so does the importance of understanding the quality of records. Health and social care organisations should review the xls icon DQMI [546kb] and use it with other tools and guidance to improve the quality of their data.

pdf icon The Methodology document [377kb] explains the detail behind the calculation of the score.

Information Update:

The May DQMI was based on the completeness and validity of submitted data. There have been some CDS specific low-impact instances identified where default not known codes (which cannot be used for useful analysis), are classed as valid in the data dictionary although are not counted as being valid in the DQMI. The combined impact of these at a national level is estimated to be 0.26 percentage points. These instances are listed below:

  • Ethnic category default code of 99, not known.
  • Null discharge dates were counted as being incomplete for all episodes in the CDS. In subsequent DQMIs we will only look at the final episode in the spell in the numerator and denominator for this.
  • Site code of treatment default value of R9998, not a hospital site, for outpatients.
  • Procedures or diagnosis data for which conditions are sensitive based on legal restrictions and had the NHS number field set to null were not counted as having a valid NHS number indicator.
  • ZZ99 postcodes relating to patients from overseas or of no fixed abode.

These instances will be counted as being valid in the next DQMI publication, and the use of them will be continually reviewed.

Please note that the overuse of default codes undermines the usefulness of data for a range of stakeholders. Consequently, the proportion of defaults used will be reported in the next DQMI, although will not affect the DQMI score.

User feedback has also highlighted that postcodes submitted without a space between the outward and inward components are being counted as being invalid in the DQMI, but are counted as being valid in the separate SUS Data Quality Dashboards. We will continue to count any postcode data being submitted in this form as being invalid in the August DQMI onwards and will be amending the SUS data quality dashboard going forward to be consistent with this.

We welcome any additional feedback from users as we look to develop the DQMI further.

To provide feedback on this iteration of the publication, and help improve it, please contact

Data Quality Reporting Tool Prototype

The Corporate Data Quality Assurance team has created a xls icon Data Quality Reporting Prototype [3Mb] for use alongside the DQMI.The tool is currently hosted in Excel, which is a short term solution and will be moved to a web business intelligence platform once stakeholders' feedback has been collated. We invite you to use the functionality and feedback with comments in order to shape the next iteration of the tool.

The aim of the tool is to provide stakeholders with the information they require to view the quality of data in a transparent and easy to use way. The Reporting Tool can be used to investigate the detail of the data quality indicator provided in the DQMI, and provides an opportunity for users to compare data quality across the datasets they submit in one place.

The reports can be filtered on dataset, data item and period, and measure the completeness and validity of the data submitted across a time series. The prototype tool holds data from the following datasets:

  • Accident and Emergency (A&E)
  • Outpatient (OP)
  • Admitted Patient Care (APC)
  • Diagnostic Imaging Dataset (DID)
  • Mental Health Services Data Set (MHSDS)
  • Improving Access to Psychological Therapies (IAPT)

To provide feedback on this version of the prototype reporting tool, and help improve it, please contact

Performance Evidence Delivery Framework

The HSCIC recommends the use of a supportive pdf icon Performance Evidence Delivery Framework [585kb]  designed to help data providers to improve their level of data quality by enhancing their own local processes. Aspects of the pdf icon framework [585kb] have been used successfully in an Acute Trust environment, leading to an improved understanding of the importance of data quality alongside an improvement in the quality of data itself

To provide feedback on this version of the framework, and help improve it, please contact

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