generic funnesopl plotting presentation 3 9 10

7/30/2019 Generic Funnesopl Plotting Presentation 3 9 10

1/20

MAC/SLK/09/42934/2 December 2009

An introduction to Statistical Process Control

(SPC) and associated analysis with data for:

Demonstration only

Malcolm BoyesHealth Outcomes Consultant

GSK


2/20


This presentation aims to provide:

An understanding of the basic principles of funnelplots

Examples of data for Demonstration Only

1. Reference Source Data for cases

2. Reference Source Data for Population


3/20


Introduced by Walter Shewhart (Bell TelephoneLaboratories 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

Background to Statistical Process Control (SPC)

1. Mohammed MA, Cheng KK, Rouse A, Marshall T. Bristol, Shipman, and clinical governance: Shewhart's forgottenlessons. Lancet 2001; 357(9254):463-467


4/20


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]
http://www.evidencebasedpractice.org.uk/spc.htmhttp://www.evidencebasedpractice.org.uk/spc.htm


5/20


Traditional approach in NHS

It is common for performance data to be presented in the form of Leaguetables 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]; Availablefrom:http://www.dh.gov.uk/en/Healthcare/Longtermconditions/DH_074772?IdcService=GET_FILE&dID=169229&Rendition=Web
http://www.dh.gov.uk/en/Healthcare/Longtermconditions/DH_074772?IdcService=GET_FILE&dID=169229&Rendition=Webhttp://www.dh.gov.uk/en/Healthcare/Longtermconditions/DH_074772?IdcService=GET_FILE&dID=169229&Rendition=Web


6/20


The Use of League Tables in Decision Making1

League tables with only common cause variation mayencourage 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

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


7/20


How does this help?1

Performance data should be used to guide qualityimprovement

The purpose should be to find the assignable causes and

understand their origin they should be prevented if badand spread if good

When only unassignable causes are present, the process

can only be improved by changing things that affect theprocess all of the time




8/20


Variation in a system is normal 1

The variation is caused by factors that are inherent inthe system over time

They affect all outcomes

This is common cause variation or

The causes are unassignable

Common cause variation can be reduced by tacklingthings that affect the process all the time




9/20MAC/SLK/09/42934/2 December 2009

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.




10/20MAC/SLK/09/42934/2 December 2009

Two types of SPC chart

If you want to compare different individuals, units orhospitals etc over a single time period, a funnel

chart may be helpful

If you want to compare a single individual, unit orhospital over different time periods, a

time chart may be helpful


11/20MAC/SLK/09/42934/2 December 2009

0.0

10.0

20.0

30.0

40.0

50.0

60.0

0 50 100 150 200 250 300

COPD List Size

NonE

lectiveCOPDadmissions/10

0COPDPatients

Upper

99.8%

Upper

95%

Overall

Lower

95%

Lower

99.8%

Mean

Likely Special Cause Variation

Likely Special Cause Variation

Likely Common Cause

Variation

Practices with higher or lower than

average admissions may be explained

by a variety of factors

Anatomy of an SPC Funnel Chart

List Size

NonElectiveadmissions/10

0Patients

Example data for illustrative purposes only


12/20MAC/SLK/09/42934/2 December 2009

How ranking data may lead to misinterpretation(1/2)

Hypothetical data showing how ranked data can lead to misinterpretation

Hypothetical data developed by GSK for illustrative purposes only

GP Practice Admissions List Size Admission RateDr 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%

Hospital Admissions

0%

10%

20%

30%

40%

50%

60%

70%

Dr C Dr G Dr E Dr F Dr D Dr H Dr A Dr B

GP Practices

AdmissionRate


13/20MAC/SLK/09/42934/2 December 2009

Hospital Admissions

0%

10%

20%

30%

40%

50%

60%

70%

Dr C Dr G Dr E Dr F Dr D Dr H Dr A Dr B

GP Practices

Ad

missionRate

How ranking data may lead to misinterpretation(2/2)

Hospital Admissions

Dr B

Dr C

Dr D

Dr E

Dr F

Dr G

Dr H

Dr A

0.0

10.0

20.0

30.0

40.0

50.0

60.0

0 50 100 150 200 250 300

List Size

AdmissionRate

Upper99.8%

Upper95%

Overall

Lower95%

Lower99.8%

GP Practice Admissions List Size Admission RateDr 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


14/20MAC/SLK/09/42934/2 December 2009

Presentation of Data for Demonstration purposesonly

Presentation of Demonstration graphs, usingmock up data.

Unplanned COPD admissions per 100 COPDpatients plotted against COPD list size




15/20MAC/SLK/09/42934/2 December 2009

Funnel Chart: x versus y

Enter graph/graphs on this and following slides




16/20MAC/SLK/09/42934/2 December 2009

0.0

5.0

10.0

15.0

20.0

25.0

0 50 100 150 200 250

COPDUNPLANNEDADM

ISSIONS/100COPDpatients

COPD LIST SIZE

Demonstration COPD admissions/100 COPD patients

Upper

99.8%

Upper95%

Overall

Lower95%

Lower99.8%



Hypothetical data developed by GSK for

illustrative purposes only


17/20MAC/SLK/09/42934/2 December 2009

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

0 50 100 150 200 250 300 350

COPDUNPLANNEDAD

MISSIONS/100COPDpatients

COPD LIST SIZE


Upper99.8%

Upper95%

Overall

Lower95%

Lower99.8%



Hypothetical data developed by GSK

for illustrative purposes only


18/20MAC/SLK/09/42934/2 December 2009

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

0 50 100 150 200 250 300 350

COPDUNPLANNEDAD

MISSIONS/100COPDpatients

COPD LIST SIZE


Upper99.8%

Upper95%

Overall

Lower95%

Lower99.8%



Hypothetical data developed by GSK for

illustrative purposes only


19/20MAC/SLK/09/42934/2 December 2009

Hypothetical data developed by GSK for illustrative

purposes only

0.0

10.0

20.0

30.0

40.0

50.0

0 50 100 150 200 250

UnplannedCOPDadmisions/100COPDpatients

COPD List

Unplanned COPD admissions versus COPD list size

Upper

99.8%

Upper95%

Overall

Lower95%

Lower99.8%


20/20

For further information or to see the admissions data for COPD in yourown Health Board contact Malcolm Boyes on:

Mob: 07920 568403

Email: [email protected]
mailto:[email protected]:[email protected]

generic funnesopl plotting presentation 3 9 10

Documents