Elective Care Data Quality and
GOSH
Peter Hyland
Director of Operational Performance and
Information
4th May 2017
History
• Initial IST review completed in May 2015 and a specific
Information review completed in July 2015
• Quality of our data, to ensure patients are treated within 18
weeks, needed to be strengthened
• Trust launched the Access Improvement Programme
• Programme sought to ensure we see patients within the correct
timeframes, with robust plans to see all patients on time in future
• Reporting on 18 week referral to treatment waiting times was
paused while the bulk of this work was carried out (August 2015
to January 2017)
What we did
• Cleaned up our data so that we know who is waiting and for how long
• Rewrote our technical processing related to the management elective
care (twice)
• Changed our operational processes to support better access for patients
• Rewrote our Access Policy to make it more robust
• Developed in excess of 60 standard operating procedures to support
Trust processes
• Developed and rolled out an RTT (and Cancer) training model to support
delivery of elective care
• Undertook a demand and capacity exercise across all areas to quantify
our capacity issues and inform recovery trajectories
• Treated longest waiting patients – waiting lists have come down
significantly across the Trust
Reporting and DQ
• Returned to reporting in January 2017
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Jan- 91.2%, Feb- 91.6%, Mar- 91.8%
Performance significantly above our agreed recovery trajectory
Plan to deliver the 92% standard in 2017
Still have long waiting patients in defined areas
• Robust reporting solution developed, tested and
implemented- Signed off by IST as ‘best practice’
• Absolute transparency of all elective care patient pathways
(not just RTT)
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Incomplete PTL
Planned PTL
Outpatient follow up PTL
RTT and non-RTT pathways- All managed in the same way
Booking reports
Automated Unify submission template directly from system
Reporting and DQ (Con’t)
Data Assurance Team
Data Assurance and not Data Validation
• Movement from a temporary Data Validation team to a substantive Data Assurance
Team
• 17 WTE including a Data Assurance Manager, 3x Data Assurance Team Leaders and 13x
Data Assurance Officers
• Trust lead and subject matter experts for Data Quality
• “Data right first time or corrected at source”
• Focus of the team is around all data quality issues and not just RTT
• Data Quality dashboard allows individual users to be identified….almost!
• Focus of the team is to:
1.
2.
3.
4.
5.
6.
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Identify errors or areas of poor practice and address them
Complete audits of data to assure the position
Undertake mentoring / training for staff were issues are identified
To provide a formal programme of training for staff around RTT, Cancer and Data Quality
Support the development of standard operation procedures to define operational processes
To undertake (minimal) data validation where required
Resource to support our EPR Programme going forward
Data Quality Dashboard
• Data Quality dashboard developed to address the needs of
the Trust
• Options appraisal completed- decision to use an external
provider with knowledge transfer to the IS Team
• Go-live at the end of March 2017
• 94 individual indicators focusing on DQ, more to follow
• 38 dedicated to RTT
• Each indicator is assigned a ‘Action Role’ (Data Assurance
Team Central / Divisional, Divisional Managers, Performance
Team
• Daily work lists available based on priority
• Direct link to the Trust SOP or other documentation
• Governance is through the weekly PTL meetings and Data
Quality Review Group
Data Quality Dashboard (Con’t)
The application is split into 7 tabs:
• Homepage – Allows easy entry into the routine daily reports.
• AC DQ Summary – Provides a summary of all available DQ metrics that
need to be acted on and can be filtered in a variety of ways.
• DQ Measures – Details and references to the SOPs and resolution for
each actionable DQ metric.
• Records – Patient level detail of all the selected metrics.
• Non AC DQ Summary - Provides a summary of all available DQ metrics
that do not need specific patient correction but informs on areas that
need improvement or review. These can be filtered in a variety of ways.
• DQ User Summary – A summary of last modified and created user
showing activity areas and metrics. Can track over time and can be used
to identify areas that may need training and support. (Limitations in
PIMs of the last modified user need to be taken into consideration)
• DQ Performance Summary – Overview of metrics and activity areas of
numbers of errors and correction details.
Data Quality Dashboard (Con’t)
Data Quality Dashboard (Con’t)
Unknown Clock Starts
• Unknown clock starts has been a significant issue for
GOSH
• 85% of referrals from secondary care
• Unknown clock start position in April 2016- 78%,
reduced to 10.8% in February 2017
• Contacting Trusts and establishing contacts
• Support by NHS Improvement- London with discussions
and agreed a workable solution
– Review of all referrals upon receipt to establish required data
– Chase referring Trusts three times for information
– Thereafter report as an unknown clock stop
• A national solution to this issue is required
So what now…..
• Data Assurance Team and the Data Quality Dashboard is
still very new, needs to be embedded
• Ensure there is operational ownership of the data and
support to rectify issues
• Prioritise the tasks required through the Data Quality
Dashboard to focus on high impact areas
• Review the Trust training package and ensure it meets
the needs of the Trust
• Issues still arise based on previous practice
Thank you for your time
Any questions