Data Quality Maturity Index (DQMI) methodology

The Health and Social Care Act 2012 (section 266) states that our 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.

Data Quality Maturity Index

The Data Quality Maturity Index (DQMI) is a monthly publication intended to highlight the importance of data quality in the NHS. It provides data submitters with timely and transparent information about their data quality. The first publication focused on the quality of set of core data items identified as being important to commissioners and regulators. Subsequent versions of the DQMI have been refined and extended based on stakeholder feedback and to support national incentives such as the Commissioning for Quality and Innovation (CQUIN) framework. Future developments of the DQMI will be shared through the Data Quality web site.

All these tools can be accessed from the NHS Digital website data quality page.

Associated tools

Power BI

An interactive reporting tool, produced in Power BI, provides a distribution of scores, with the option to create groupings by region and locality. This tool can also be used to create peer comparisons.

CSV File

A CSV file of the raw data on which the DQMI is based is available in machine readable format.

The DQMI publication also includes an experimental score which applies the same DQMI methodology but incorporates additional fields for potential future inclusion within the standard (official) DQMI. This feature allows for the impact of including new data items within the DQMI to be modelled, prior to them being incorporated into the standard DQMI.

When additional new data items are to be included in the DQMI they are first added to the experimental calculation for some time before being incorporated into the list of standard fields. This allows organisations time to assess the impact this change would have on their official DQMI score and take corrective action prior to the change being fully implemented.

The DQMI publication displays which datasets currently have experimental data items being modelled and which data items within those datasets are currently incorporated into the standard or experimental DQMI scores.