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Performance Monitoring

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Title: An overview of public health and its practice Author: GOSWUser Last modified by: James Hollinshead Created Date: 1/12/2004 6:06:11 PM Document presentation format – PowerPoint PPT presentation

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Title: Performance Monitoring


1
Performance Monitoring
  • Day 4 EM Analyst Training Course 02.10.12

2
Learning Objectives
  • At the end of the course, participants will be
    able to ...
  • explain what is meant by performance monitoring
  • identify the drivers, purpose and applications of
    performance monitoring
  • illustrate how performance monitoring is
    undertaken in practice

3
Performance monitoring
  • Executives worth their salt will be asking ...
  • are we achieving our objectives?
  • are we meeting our targets?
  • what should our priorities be?
  • whats our strategy for ....?
  • what changes do we need to make to local
    services?
  • where and how should we target our resources?
  • are our initiatives and service changes having
    the intended effect?

4
Drivers and purpose
  • Demand for accountability of public services
    Clinical governance.
  • Quantifying and qualifying the results of
    surveillance.
  • Encourage best practice identify opportunities
    for development and shared learning.
  • Clarify an organisations objectives and
    priorities.
  • Measuring progress against targets.

5
ASSESSING PERFORMANCE
6
Monitoring and evaluating play an important role
within the NHS
  • Definition?
  • Measuring and comparing observed data with a
    benchmark or baseline
  • Comparisons can be
  • over time (e.g. one year to the next)
  • between areas (e.g. local authorities)
  • against a target (e.g. 98)
  • against an expected value

7
Choosing an indicatorThe good indicators guide
A poorly designed indicator with reliable
data, or a well designed indicator with
unreliable and/or untimely data, has very little
value (and is sometimes dangerous).
8
The good indicators guide10 key questions
  1. What is being measured?
  2. Why is it being measured?
  3. How is the indicator defined?
  4. Who does it measure?
  5. When does it measure it?
  6. Will it measure absolute numbers or proportions?
  7. Where do the data actually come from?
  8. How accurate and complete will the data be?
  9. Are there any caveats/warnings/problems?
  10. Are particular tests needed (e.g.
    standardisation, significance tests or SPC) to
    test the meaning of the data and the variation
    they show?

9
The good indicators guide
  • Selection of indicators and the data that feed
    into them will often involve a trade off between
    what is convenient (and possible) and what is
    ideal.
  • The right indicator at the right time and in the
    right context can stimulate huge change where it
    might have no effect in other contexts and at
    other times. Change hearts and minds
  • Try not just to present the data look for the
    story it is telling.

10
Does this tell you enough?
Sources Office for National Statistics and
Teenage Pregnancy Unit
11
Comparators give context
Sources Office for National Statistics and
Teenage Pregnancy Unit
12
Ways of evaluating performance
  • Spine chart
  • Tartan rug
  • Benchmarking
  • Statistical Process Control
  • Control and run charts
  • Funnel plots

13
Ways of evaluating performance
Number of indicators Many/one Number of organisations Many/one Over time? Yes/no
Spine chart
Tartan rug
Benchmarking
Statistical Process Control (SPC) Control chart / Run chart
SPC funnel plot
14
Spine Chart
So you want to make a spine chart? http//www.wmph
o.org.uk/tools/ ERPHO Spine chart
video http//www.youtube.com/watch?v480Mswgcg8Mf
eatureplcp
15
Tartan rug
16
Benchmarking
  • Contextualise performance
  • Encourages best practice
  • Shared learning and areas for development

17
Benchmarking
  • Which local authority would you say had an issue
    with perinatal mortality? Can you think of any
    issues regarding presenting data in a league
    table such as this?

East of England average
Confidence interval
Perinatal mortality rate by local authority, East
of England 20012005, INpho 26
18
Statistical Process Control
  • common cause variation
  • the normal, everyday, inevitable (and usually
    unimportant), variation which is intrinsic and
    natural to any system
  • special cause variation
  • the more important variation which is indicative
    of something special happening and which calls
    for a fuller understanding and often action
  • For more info see APHO technical briefing
  • http//www.apho.org.uk/resource/view.aspx?RID3930
    6

19
Types of control chart
  • Run chart displays any data over time against
    its median
  • Control chart looks similar to a run chart but
    plots data against its mean and the appropriate
    control limits
  • Good for monitoring trends over time
  • Good for monitoring data against a specific
    target
  • AE 4 hour waits
  • Childhood obesity
  • Control charts explained to music
  • http//www.youtube.com/watch?v1XM3DpyBHss

20
Example of a control chart
  • Control charts are plots of the data with lines
    indicating the target value (mean, median) and
    control limits superimposed.

21
Types of control chart con..
  • Funnel plots
  • A type of chart where the indicator of interest
    is plotted against the denominator or sample
    size.
  • This gives it the characteristic funnel shape
  • ERPHO funnel plot video http//www.youtube.com/wat
    ch?v480Mswgcg8Mfeatureplcp
  • So you want to create a funnel plot?
  • APHO provides tools for creating funnel plots for
    different kinds of data
  • http//www.apho.org.uk/default.aspx?RID39403

22
Example of funnel plot
23
Using control charts and SPC methods
  • Control charts can help us to present and
    interpret our information more intelligently.
  • They can be used
  • To detect unusual or outlying patterns, e.g. poor
    performance, outbreaks or unusual patterns of
    disease
  • In health profiling and assessing levels of
    performance
  • To decide whether or not targets are being met
  • In assessing health inequalities (i.e. funnel
    plots)

24
Control chart AE 4 hour waitsChange in target
Green line target Red lines CIs
25
Funnel plotPerinatal Mortality
26
Breast cancer mortality
APHO technical briefing 2 Statistical process
control methods in public health intelligence
27
Lung cancer mortality
APHO technical briefing 2 Statistical process
control methods in public health intelligence
28
Summary
  • Good monitoring and benchmarking requires use of
    comparators
  • Good data visualisation is helpful
  • Statistical process control allows you to
    distinguish between common cause variation and
    special cause variation, which might indicate a
    problem or an exceptional performance within the
    system.

29
Further information
  • The Good Indicator Guide how to use and choose
    performance indicators http//www.apho.org.uk/reso
    urce/item.aspx?RID44584
  • APHO Technical Briefings
  • http//www.apho.org.uk/resource/view.aspx?RID3930
    6
  • No. 2 Statistical process control methods in
    public health intelligence
  • No. 3 Commonly used public health statistics
    their confidence intervals
  • No. 4 Target setting in a multi-agency
    environment
  • Health Profiles http//www.healthprofiles.info
  • WMPHO spine chart generator http//www.wmpho.org.
    uk/resources/WMPHO_Spine_chart.xlsm
  • ERPHO tool to produce run charts (you may need to
    log onto the ERPHO website) http//www.erpho.org.u
    k/viewResource.aspx?id14762
  • Create a p chart in excel
  • http//www.ehow.com/how_8039012_create-chart-using
    -samples.html

30
Learning Objectives
  • At the end of the course, participants will be
    able to ...
  • explain what is meant by performance monitoring
  • identify the drivers, purpose and applications of
    performance monitoring
  • illustrate how performance monitoring is
    undertaken in practice
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