Malcolm Boyes Health Outcomes Consultant GSK An introduction to Statistical Process Control (SPC) and associated analysis with data for: Demonstration only Malcolm Boyes Health Outcomes Consultant GSK Areas surrounded in red boxes should be customized with local data (relevant to your presentation)

This presentation aims to provide: An understanding of the basic principles of funnel plots Examples of data for Demonstration Only Insert the data to be included in the funnel plots, the date to which the data refers Insert an appropriate reference for your data. An extract on how to reference electronic data sources are provided with the tool or full details are available online: www.library.uq.edu.au/training/citation/vancouv.pdf Reference Source Data for cases 2. Reference Source Data for Population

Background to Statistical Process Control (SPC) Introduced by Walter Shewhart (Bell Telephone Laboratories 1924) The method was exported to Japan in the 1950s, where it was successfully applied in industry. SPC techniques “demonstrate the simplicity and power of control charts at guiding their users towards appropriate action for improvement”. 1 1. Mohammed MA, Cheng KK, Rouse A, Marshall T. Bristol, Shipman, and clinical governance: Shewhart's forgotten lessons. Lancet 2001; 357(9254):463-467

What is Statistical Process Control (SPC) Statistical Process Control SPC is defined as: a philosophy, a strategy and a set of methods for ongoing improvement of systems, processes and outcomes 1 Simple graphical way to display data and outcomes It is a method which identifies unusual variation Aims to improve quality 1. Evidence based practice: Definition of SPC. Available at: http://www.evidencebasedpractice.org.uk/spc.htm [Accessed 31/03/2009]

Traditional approach in NHS It is common for performance data to be presented in the form of League tables or ranked data, for example DoH Hospital Episode Statistics (HES) data in Disease Management Information Toolkit 1 1. DOH. Disease management information toolkit. Long Term Conditions. 2008 July. [Accessed 16/07/09]; Available from:http://www.dh.gov.uk/en/Healthcare/Longtermconditions/DH_074772?IdcService=GET_FILE&dID=169229&Rendition=Web

The Use of League Tables in Decision Making1 League tables with only common cause variation may encourage unwarranted tampering League tables may lead to local special cause variation being ignored League tables may encourage the ‘blame culture’ and are not linked directly to improvement activity For more information by way of an illustrative example please see slide 13 and 14. 1. Roberts T. Understanding variation [Online] July 2005 [cited July 2009]; [17 Pages] Available from: http://www.evidencebasedpractice.org.uk/documents/presentations/spc_TEBPCJune2005.ppt

How does this help?1 Performance data should be used to guide quality improvement The purpose should be to find the ‘assignable’ causes and understand their origin – they should be prevented if bad and spread if good When only ‘unassignable’ causes are present, the process can only be improved by changing things that affect the process all of the time 1. Roberts T. Understanding variation [Online] July 2005 [cited July 2009]; [17 Pages] Available from: http://www.evidencebasedpractice.org.uk/documents/presentations/spc_TEBPCJune2005.ppt

Variation in a system is normal 1 The variation is caused by factors that are inherent in the system over time They affect all outcomes This is ‘common cause’ variation or The causes are ‘unassignable’ Common cause variation can be reduced by tackling things that affect the process all the time 1. Roberts T. Understanding variation [Online] July 2005 [cited July 2009]; [17 Pages] Available from: http://www.evidencebasedpractice.org.uk/documents/presentations/spc_TEBPCJune2005.ppt

Some variation may not be normal 1 The factors are not present in the process all the time They do not affect everybody They arise because of specific circumstances This is ‘special’ or ‘assignable’ cause variation. 1. Roberts T. Understanding variation [Online] July 2005 [cited July 2009]; [17 Pages] Available from: http://www.evidencebasedpractice.org.uk/documents/presentations/spc_TEBPCJune2005.ppt

Two types of SPC chart If you want to compare different individuals, units or hospitals etc over a single time period, a ‘funnel chart’ may be helpful If you want to compare a single individual, unit or hospital over different time periods, a ‘time chart’ may be helpful

Anatomy of an SPC ‘Funnel Chart’ Likely Common Cause Variation Likely Special Cause Variation Practices with higher or lower than average admissions may be explained by a variety of factors Upper 3SD Confidence Interval Lower 3SD Confidence Interval Non Elective admissions / 100 Patients Upper 2SD Confidence Interval Lower 2SD Confidence Interval Mean List Size Example data for illustrative purposes only

How ranking data may lead to misinterpretation (1/2) Hypothetical data showing how ranked data can lead to misinterpretation GP Practice Admissions List Size Admission Rate Dr C 3 5 60.0% Dr G 20 35 57.1% Dr E 56 110 50.9% Dr F 23 54 42.6% Dr D 25 70 35.7% Dr H 28 123 22.8% Dr A 24 132 18.2% Dr B 11 333 3.3% Average 190 862 22.0% Hypothetical data developed by GSK for illustrative purposes only

How ranking data may lead to misinterpretation (2/2) GP Practice Admissions List Size Admission Rate Dr C 3 5 60.0% Dr G 20 35 57.1% Dr E 56 110 50.9% Dr F 23 54 42.6% Dr D 25 70 35.7% Dr H 28 123 22.8% Dr A 24 132 18.2% Dr B 11 333 3.3% Average 190 862 22.0% Hypothetical data developed by GSK for illustrative purposes only

Presentation of Data for Demonstration purposes only Presentation of Demonstration graphs, using mock up data. Unplanned COPD admissions per 100 COPD patients plotted against COPD list size 1. Reference Source Data for cases 2. Reference Source Data for Population

Funnel Chart: x versus y Enter graph/graphs on this and following slides Slides should be customised with local data (see slides with areas surrounded in red boxes). Slides can be populated with data from: The Companion dataset - The spreadsheet should not be given to external customers. If you are sharing the spreadsheet with a customer (during a visit) to identify practices, focus only on data for the relevant PCOs Data provided from the customer – You must complete a generic agreement when using customer data AND save this form together with the data on the HOC LAN drive in the specific area set aside for this purpose Data from other sources – When completing funnel plots from another source: a) You must complete a data source form. b) You must reference the data source appropriately c) Refer to the SPC funnel plotting training and use the approved funnel plotting tool provided with this presentation Insert the data to be included in the funnel plots, the date to which the data refers Insert an appropriate reference for your data. An extract on how to reference electronic data sources are provided with the tool or full details are available online: www.library.uq.edu.au/training/citation/vancouv.pdf 1. Reference Source Data for cases 2. Reference Source Data for Population

Hypothetical data developed by GSK for illustrative purposes only 1. Reference Source Data for cases 2. Reference Source Data for Population

Hypothetical data developed by GSK for illustrative purposes only 1. Reference Source Data for cases 2. Reference Source Data for Population

Hypothetical data developed by GSK for illustrative purposes only 1. Reference Source Data for cases 2. Reference Source Data for Population

Hypothetical data developed by GSK for illustrative purposes only

For further information or to see the admissions data for COPD in your own Health Board contact Malcolm Boyes on: Mob: 07920 568403 Email: malcolm.2.boyes@gsk.com