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The Wider Use of
Risk Stratification Methodology
Alan Thompson
Chris Morris
Central Southern
Commissioning Support Unit
30th June 2014
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Introduction
• Initiated our work on risk stratification in early 2010
• 4 ½ years experience of all aspects from primary care
data extraction, IG, grouping of data, predictive models,
visualisation and reporting and how to use the
information a& intelligence
• Use the Johns Hopkins Adjusted Clinical Groups (ACG®)
System
• Purpose of todays short talk is to give you a flavour of
what we’re doing and signpost you to where you can get
more information
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Central Southern CSU Working Definitions
• Within the CSU we make the distinction between:
Patient level risk stratification -. The outputs are used by clinicians for
the purposes of supporting direct patient care eg case management. The
information produced describes each patient’s overall morbidity and their
risk of particular outcomes such as risk of emergency admission and risk
of high cost in the coming year
and
Population level risk profiling – The outputs of this process are used
by non-clinical staff for the purposes of supporting commissioning
activities. The information produced provides information about disease
and risk prevalence and distributions across wider populations and can
be used to inform planning and service redesign activities
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Role of Risk Stratification & Risk Profiling
• We have identified four main roles for the use of risk stratification, risk
profiling and risk adjustment methodologies:
1. To support case finding activities - finding suitable patients from all levels
of the risk pyramid for the various services and care programmes being provided
2. To support population profiling - undertaking population profiling
analyses to better understand the current and future health needs of the whole
population and commission services accordingly
3. To support resource management and our understanding of
relative performance - using risk and case-mix adjustments to enhance the
way in which we benchmark performance and understand comparative performance
4. Potentially to support a more equitable formula for resource
allocation - thinking about a new and more equitable approach to the allocation
of resources
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Recalibration of Models
• In 2013 we worked with JHU to recalibrate predictive
models within the ACG System
• Also developed a model to predict risk of emergency
admission and incorporated that into the ACG System
software
• Now have the ability to develop new models in the future
or add new variables as they become available
• More information about this work is available on the flyer
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Case-mix Adjustment
Total Primary Care Utilisation
Top 1% of population (100th percentile) uses 10%
activity
Top 5% of population (96th percentile) uses 30% of
activity
Association between Primary Care Utilisation
and Secondary Care Cost
Primary Care Utilisation
Non-user 16% 0% 1%
Low 30% 7% 5%
Moderate 17% 11% 8%
High 18% 21% 17%
Very High 13% 29% 30%
Extremely High 6% 33% 40%
People
Total Primary Care
Activity
Total Secondary
Care Cost
Multi-morbidity and
Primary Care Utilisation
Chronic Conditions
0 24% 39% 17% 13% 5% 1%
1 7% 25% 21% 26% 17% 5%
2 2% 10% 15% 29% 31% 14%
3 0% 4% 9% 25% 37% 25%
4 0% 2% 5% 18% 37% 38%
5 0% 1% 3% 13% 34% 49%
6 0% 1% 2% 9% 29% 60%
7 0% 0% 1% 7% 24% 68%
8+ 0% 0% 1% 3% 16% 79%
Primary Care Utilisation
Non-user Low Moderate High Very High Extremely High
Distribution of total cost
incl. indicative Primary Care cost
Distribution of Total Cost
Against Predictions
More Information
• More information about our work from:
– Alan Thompson – [email protected]
– Chris Morris – [email protected]
– Please pick up copies of the two flyers that we’ve brought with us
– Participation in one of the two webinars we’ve scheduled on:
• Friday 18th July 13.00 – 14.00 or
• Monday 21st July 13.00 – 14.00
– If you would like to participate in one of the webinars, please give
Chris or I your contact details over lunch
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Thank You
Any Questions?
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