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Data quality

The DQMI is a monthly publication about data quality in the NHS, which provides data submitters with timely and transparent information.

Developments to the Data Quality Maturity Index

We have introduced a new data quality dimension to measure the level of consistency of a provider’s submission over a timeseries. This applies Statistical Process Control over a rolling 12-month period to produce a score based on the number of standard deviations from the average.  This score will be published as experimental for the remainder of 2019-20 so as not to impact the MHSDS DQMI whilst the CQUIN is being applied.

Thank you to everyone that completed our short survey on the data quality services and support offered by NHS Digital.  We are currently review the scores, identify the main themes within the feedback and develop an action plan to address these. We will publish the analysis and the action plan with the DQMI reports in November.

The survey is still open and can access the survey by clicking on this link NHS Digital Data Quality Assurance Survey.

We held the first Data Quality Assurance Provider Forum on 23rd September with data quality colleagues from across seventeen trusts.  The Terms of Reference of the forum were approved and the need to extend membership to all interested providers was agreed.  Can anyone wanting to join the forum please email the DQ Assurance mailbox below with your contact details and consent to be added to the membership list.

Any questions about he above or general enquiries relating to the DQMI please email the Corporate Data Quality Assurance Team at dqateam@nhs.net.

MHSDS Validity and Integrity Measures SQL

The below 2 pieces of code are used by the MHSDS team to generate the numbers provided to us for the DQMI. These should give through slight modifications providers the ability to pre-check the data. Unfortuantly no assistance modifying these etc will be available and are there for reference only.

Create validity measures SQL

Create integrity measures SQL

 

Current Data Quality Maturity Index (DQMI)

The DQMI is a monthly publication about data quality in the NHS, which provides data submitters with timely and transparent information.

Links to all of the DQMI publications, the associated methodology documents and the interactive report can be found below:

September 2019

DQMI-21 (June 2019)

DQMI-21 CSV

DQMI-21 Methodology

Power BI Interactive Report

DQMI Power BI User Guide

Current comorbidity diagnostic persistence

Diagnostic codes for conditions that do not remit should not be lost from patient records over time - this "diagnostic persistence" is a measure of data quality. The below factsheet highlights the proportion of patient episodes that include, or omit, a code for one of five clinical diagnoses where there is reason to expect that a code should continue to be recorded. We reviewed diagnostic codes for all episodes of hospital care over a three month period, and then looked back to compare whether a relevant code was previously recorded.

February 2018

DQMI Comorbidity Outputs 17-18 Q2 Jul to Sep v1.0 Final [859kb](Opens in a new window)

February Diagnostic Persistence Infographic_FINAL v0.1 [518kb](Opens in a new window)

Note: The Analysis is to show diagnostic coding for conditions that do not remit should not be lost from patient records over time - this "diagnostic persistence" is a measure of data quality, it is not to show poor diagnosis or treatment of conditions.

Historic comorbidity diagnostic persistence

Historic DQMI publications

August 2019

DQMI- 20 (May 2019)

DQMI- 20 CSV

DQMI- 20 Methodology

Power BI Interactive Report

DQMI Powe BI User Guide

July 2019

DQMI-19 (April 2019) (Updated 21/08/2019 to include DID data and changes made to the default in excess calculation)

DQMI-19 CSV (Updated 21/08/2019 to include DID data and changes made to the default in excess calculation)

DQMI-19 Methodology

Power BI Interactive Report

DQMI  Power BI User Guide

June 2019

Updated 26/07/2019 to include DID data

DQMI-18 (March 2019) (Updated 21/08/2019 with changes made to the default in excess calculation)

DQMI-18 CSV (Updated 21/08/2019 with changes made to the default in excess calculation)

DQMI-18 Methodology

Power BI Interactive Report

DQMI  Power BI User Guide

May 2019

DQMI-17 Methodology

DQMI-17 (February 2019) (Updated 21/08/2019 with changes made to the default in excess calculation)

DQMI-17 CSV (Updated 21/08/2019 with changes made to the default in excess calculation)

Power BI Interactive Report

DQMI Power BI User Guide

April 2019

DQMI-13-16 Methodology

DQMI-13 (October 2018)
DQMI-13 CSV

DQMI-14 (November 2018)

DQMI-15 (December 2018)
DQMI-15 CSV

DQMI-16 (January 2019) (Updated 21/05/2019 to include DID data)
DQMI-16 CSV (Updated 21/05/2019 to include DID data)

Power BI Interactive Report
DQMI Power BI User Guide

 

DQMI-14 CSV

February 2019

DQMI-12 (2018-19 Q2) - covers data for the period of July – September 2018
DQMI-12 Methodology
DQMI 12 CSV
Power BI Interactive Report
DQMI Power BI User Guide February 2019

November 2018

DQMI-11(2018-19 Q1)
DQMI-11 Methodology
DQMI 11 CSV
Power BI Interactive Report
DQMI Power BI User Guide November 2018

August 2018

DQMI-10 (2017-18 Q4)
DQMI-10 Methodology
DQMI 10 CSV
Power BI Interactive Report
DQMI Power BI User Guide August 2018

May 2018

DQMI-9 (2017-18 Q3)

DQMI-9 Methodology

DQMI 9 CSV

Power BI Interactive Report

DQMI Power BI User Guide May 2018

February 2018

DQMI-8 (2017-18_Q2) [694kb]

DQMI-8_Methodology

DQMI_8_CSV [2Mb](Opens in a new window)

Power BI Interactive Report

DQMI Power BI User Guide February 2018

November 2017

There are missing records for a number of providers (predominantly independent sector) in the CDS (APC, A&E, OP) data. This was caused by a change introduced by SUS+ in August which resulted in these missing records.

DQMI-7_(2017-18_Q1) [689kb](Opens in a new window)

DQMI-7 Methodology [1Mb](Opens in a new window)

DQMI 7 CSV [1Mb](Opens in a new window)

Power BI Interactive report

DQMI Power BI User Guide November 2017

Note: The Analysis is to show diagnostic coding for conditions that do not remit should not be lost from patient records over time - this "diagnostic persistence" is a measure of data quality, it is not to show poor diagnosis or treatment of conditions.

August 2017

DQMI-6 (2016-17 Q4) [730kb](Opens in a new window) covers data for the period of January - March 2017.

DQMI-6 Methodology [977kb](Opens in a new window) 

DQMI-6 CSV (Opens in a new window)

Power BI Interactive report

DQMI Power BI User Guide August 2017

May 2017

DQMI-5 (2016-17 Q3) [723kb](Opens in a new window) covers data for the period of October - December 2016. 

DQMI-5 Methodology [1018kb](Opens in a new window)

DQMI-5 CSV file [1Mb](Opens in a new window) CSV reissued on 24/05/2017 due to duplicates in the original file.

Power BI Interactive report

Power BI Report user guide May 2017

February 2017

DQMI-4 (2016-17 Q2) [643kb](Opens in a new window) covers data for the period of July - September 2016

DQMI-4 (2016-17 Q2) [643kb](Opens in a new window) 

DQMI-4 Methodology [1Mb](Opens in a new window)

DQMI-4 CSV [1Mb](Opens in a new window)

Power BI interactive report

Power BI Report User Guide February 2017

November 2016

DQMI-3 (2016-17 Q1) [683kb](Opens in a new window)  covers data for the period of April - June 2016

DQMI-3 Methodology [1Mb](Opens in a new window)

DQMI-3 CSV [1Mb](Opens in a new window)

Power BI interactive report

Power BI Report User Guide November 2016

August 2016

DQMI-2 (2015-16 Q4) covers data for the period of January - March 2016

DQ_maturity_index_introduction_and_methodology__15_8_16

DQMI-2 CSV file

Power BI interactive report

May 2016

DQMI-1 (2015 Annual) covers data for the period of January - December 2015

DQMI-1 methodology document

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 we collect meets defined national standards and to publish the results of the assessments. In addition, we may give advice or guidance on data quality relating to the collection, analysis, publication or other dissemination of data and information.

Our Data Quality Assurance Strategy 2018-2020 sets out how we will fulfil these responsibilities.

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 Terms of Reference are available for reference, and any queries about the group should be directed to DQAteam@nhs.net.

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.

DQA provider forum

A DQA provider forum meets quarterly with representatives from 20 provider organisations from around the country. The forum is supported by a national provider E-forum enabling further engagement from over 100 active members.

Performance evidence delivery framework

NHS Digital recommends the use of a supportive performance evidence delivery framework (version 2) designed to help data providers to improve their level of data quality by enhancing their own local processes. Aspects of the framework 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.

Related Links

Quick links

Last edited: 11 October 2019 10:42 am