1. health and fitness

Integration of the Diabetes Population Risk Tool (DPoRT)
into Public Health Practice
Sheila Datta, MSc, Epidemiologist, Peel Public Health
Laura Rosella, PhD, Scientist Public Health Ontario
Acknowledgements
• Peel Public Health: David Mowat, Sheila Datta, Nancy
Ramuscak, Julie Stratton
• Public Health Ontario: Laura Rosella, Michael Lebenbaum, Ian
Johnson, M. Mustafa Hirji, John Wang, Lennon Li, Leslea
Peirson
• Ottawa Hospital Research Institute: Douglas Manuel
• Institute for Clinical Evaluative Sciences : Therese Stukel
• Ministry of Health and Long Term Care: Michael Hillmer
www.oahpp.ca
2
Objectives
• Background: Diabetes Population Risk Tool (DPoRT)
• Methodology
• Application of the Tool in Peel
• Next Steps
Analogy: Clinical Risk Prediction
Age
Diabetes
Smoking
Blood Pressure
Framingham Risk
Calculator
10 Year Risk
of Coronary
Heart
Disease
Clinical
Risk Model
Response
Lipid profile
Covariates
4
Population Risk Modeling
Population
Characteristics
Covariates
Math
Population
Risk Model
Population’s
Risk of
Disease
Response
5
Vision
Enable a decision-maker to use the characteristics from their
population and estimate the number of new diabetes cases in
their population of interest for the purpose of:
• Resource planning
• Prevention
• Understand distribution of risk in the population
• To facilitate decision making and priority setting
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Diabetes Population Risk Tool (DPoRT)
OBJECTIVE: To create and validate a population based risk
prediction tool for incident diabetes mellitus using widely
available public data.
Validity in this context:
1. With the available factors is this the best model that can
be found (statistical)
2. Does the model predict accurately for its intended
purpose (public health relevance)
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Why this approach?
• Diabetes surveillance data at the national level is difficult to
gather and not linked to many risk factors
• Utilizes existing surveillance data on risk factors in Canada
• Balancing accessibility with model performance
www.oahpp.ca
DPoRT creation:
• DEVELOPMENT COHORT: Linked1996/7 NPHS in ON (N=23,403)
• VALIDATION COHORT 1: Linked 2000/1 CCHS in ON (N=37,463)
• VALIDATION COHORT 2: Linked1996/7 NPHS in MB (N=10,118)
• Risk attributes: only those that are routinely and publicly available (in
the NPHS and CCHS)
• Outcome - physician-diagnosed diabetes (ODD & MB version)
www.oahpp.ca
DPoRT 2.0 – an update!
• DEVELOPMENT COHORT: Linked1996/7 NPHS in ON (N=23,403)
+ Linked 2000/1 CCHS in ON (N=37,463) + Linked 2003/4 CCHS (N =
33,679)
• VALIDATION COHORT: Linked 2005 CCHS (N = 33,402)
• Risk attributes: only those that are routinely and publicly available (in
the NPHS and CCHS)
• Outcome - physician-diagnosed diabetes (Ontario Diabetes Database)
www.oahpp.ca
Validation
DPoRT was successfully validated in two external
validation cohorts and demonstrated good
discrimination and calibration
Compare observed
and predicted
Assess
discrimination via
‘ROC-like’ measures
(C statistic)
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Calibrate
(re-calibrate)
Model Features
• Weibull accelerated failure time model
• Variables are centered to the mean values of their population
(i.e. take into account the baseline level of risk)
• Separate for males and females
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Attributes of DPoRT
MALES
FEMALES
Body Mass Index (Kg/m2)
Body Mass Index (Kg/m2)
Age
Age
Non-white Ethnicity
Non-white Ethnicity
Prevalent hypertension
Prevalent hypertension
Smoking
Immigrant Status
Prevalent heart disease
Post Secondary Education
Post Secondary Education
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Example use of the Diabetes Population Risk Tool to predict
the 9-year risk of diabetes for a specific high-risk man
www.oahpp.ca
Rosella L C et al. J Epidemiol Community Health doi:10.1136/jech.2009.102244
Applying the risk tool
• Sex-specific DPoRT models can be applied to any of the
national health surveys in Canada (NPHS or CCHS) for those
who are 20 year + and free of diabetes at baseline
• The number of new cases is estimated by multiplying the
diabetes risk (probability) by the population number
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DPoRT
• DPoRT was designed so that it could be applied to routinely
collected and publicly available data allowing the tool to be used
by a wide audience
• Tool can be applied to quantify impact that changes in baseline
risk factors will have on future diabetes incidence
• An innovative way to make routinely collected population health
data useful for diabetes prevention planning in a practical and
meaningful way
Rosella L C et al. J Epidemiol Community Health doi:10.1136/jech.2009.102244
16
Application of the Diabetes Population
Risk Tool (DPoRT) for Peel Public Health
www.oahpp.ca
Understanding Diabetes in Peel
• The prevalence of diabetes has increased rapidly over the past
decade; Diabetes rates in Peel exceed those of Ontario
• Without intervention, diabetes is projected to continue rising
due to increasing obesity rates and changes to the ethnocultural makeup of Peel’s population
• Efforts to understanding diabetes supports the Term of Council
Priorities to prevent obesity and diabetes in Peel.
• Peel Regional Council understands the need for interventions
aimed to reduce the burden of diabetes in Peel
www.oahpp.ca
Projecting Disease Burden in the Future (2010-2020)
Population (age ≥ 20) 2010 New Cases 2011-2020
Incidence
Canada
22,298,000
1,967,000
8.8%
Ontario
8,511,000
747,000
8.8%
844,000
76,000
9.2%
Peel Region
www.oahpp.ca
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Predicted Number of New Diabetes Cases in Peel (2010-2020)
Overall
75,032
High Risk
24,672
Obese
24,570
South Asian
www.oahpp.ca
15,236
How the Tool Can Be Used to
Support Public Health
• Forecast future incidence of disease
• Characterizing groups at increased risk for diabetes
• Casting future needs for medical resources
• Estimate the impact of interventions
www.oahpp.ca
Original Canadian Community
Health Survey (CCHS)
Overview of DPoRT
application in Peel
Restrict sample
(Peel residents who are
age ≥20 without diabetes)
Re-code CCHS variables into
format required by DPoRT
Calculate summary statistics
for overall population
Use DPoRT risk equation to estimate
individual 10-year risk and the
number of diabetes cases they represent
Identify the effects of prevention
activities
E.g. Approximately 8,000 cases can be
prevented if all of Peel is targeted with
intervention with 10% relative risk
reduction vs. approximately 8,600 cases
prevented if only high risk individuals are
targeted with intervention with a 30% risk
reduction
E.g. Approximately 80,000
new diabetes cases expected
in Peel between 2010-2020
Identify high risk
Individuals
Identify risk across population
strata
Identify future health care needs
E.g. 11% of Peel
population as 10year risk ≥ 20%
E.g. Peel 10-year risk is 10.5% and
6.3% in lowest and highest income
quintiles respectively
E.g. Over the next 10 years,
approximately 7,600 of these new
diabetes cases will develop glaucoma
Ten-year Diabetes Incidence Rate (%) by Ontario Public Health Unit (2010-2020)
Timiskaming Health Unit
HKP R
No rthwestern Health Unit
Huro n Co unty Health Unit
Thunder B ay District Health Unit
Durham Regio n Health Department
Grey B ruce Health Unit
Co unty o f Lambto n
Elgin-St. Tho mas P ublic Health
Sudbury & District Health Unit
Chatham-Kent P ublic Health
Renfrew Co unty & District Health Unit
Haldimand-No rfo lk
P erth District Health Unit
P eel P ublic Health
Simco e M usko ka District Health Unit
A lgo ma P ublic Health
Yo rk Regio n P ublic Health
Hastings & P rince Edward
Windso r-Essex Co unty Health Unit
City o f Hamilto n
Kingsto n-Fro ntenac
City o f To ro nto
P eterbo ro ugh
No rth B ay P arry So und District Health Unit
Niagara Regio n P ublic Health
Wellingto n-Dufferin-Guelph
P o rcupine Health Unit
Leeds, Grenville and Lanark District Health Unit
M iddlesex-Lo ndo n Health Unit
Eastern Ontario Health Unit
B rant Co unty Health Unit
Oxfo rd Co unty P ublic Health
Regio n o f Waterlo o P ublic Health
Ottawa P ublic Health
Halto n Regio n Health Department
0
2
4
6
8
10
12
14
Ten-year diabetes incidence rate and number of new diabetes cases
in Peel region by BMI category (2010–2020)
35
40000
30
35000
30000
25
25000
20
20000
15
15000
10
10000
5
5000
0
0
<23
www.oahpp.ca
Diabetes Cases (N)
23-25
25-30
30-35
35+
Number of diabetes cases
10-year diabetes incidence rate (%)
Diabetes Risk (%)
Ten-year diabetes incidence rate by age and region in Canada
(2010–2020)
20
10-year diabetes incidence rate (%)
18
16
14
12
10
8
6
4
2
0
Under 45 years
45–64 years
Canada
www.oahpp.ca
Ontario
65 year or older
Peel
Ten-year diabetes incidence rate by sex, age group and region in
Canada (2010–2020)
10-year diabetes incidence rate (%)
25
20
15
10
5
0
Under 45 years
45–64 years
65 year or older
Under 45 years
45–64 years
65 year or older
Male
Male
Male
Female
Female
Female
Canada
www.oahpp.ca
Ontario
Peel
Ten-year diabetes incidence rate and number of new diabetes cases
in Peel region by Ethnicity (2010–2020)
Diabetes Risk (%)
Diabetes Cases (N)
40000
35000
10
30000
8
25000
20000
6
15000
4
10000
2
5000
0
0
White
www.oahpp.ca
South Asian
Black
Other
Number of diabetes cases
10-year diabetes incidence rate (%)
12
Application of DPoRT for Public Health
Planning
Incident DM
Cases in 10 years
Number of
Cases Averted
NNT
Weight
(Kg)
Weight
Loss
(Kg)
75,032
---
---
73.3
---
1% reduction in weight at
the population
72,908
2,124
389
72.5
0.7
5% reduction in weight at
the population
65,153
9,879
84
69.6
3.7
Individuals with obesity
24,570
---
---
95.8
---
5% reduction in the
weight of the obese
population
20,379
4,191
24
91.0
4.8
10% reduction in the
obese population
17,013
7,557
13
86.2
9.6
Current
Population Intervention
Targeted Intervention
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Application of DPoRT for Public Health
Planning
Incident DM Cases in
10 years
Number of Cases
Averted
NNT
Current
75,032
---
---
South Asians
15,236
---
---
12,951
2,285
69
69,394
5,638
---
Targeted Intervention Among South Asians
15% risk reduction among
South Asians
Multi-pronged Strategy
1% reduction in weight in the
population and 15% risk
reduction among individuals
who are high risk
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Lifestyle Intervention in 10% highest risk (HR = 0.51)
Peel Region
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QALYs Changed
HC Cost Savings
Deaths Averted
11,641
$22.0 million
277
30
Making the Case for Funding Public Health
Additional QALYs Lost
Excess Health Care Costs
Excess Deaths
Canada
7,430,279
$14,322,496,107.29
180,287
Ontario
2,961,526
$5,706,924,371.02
71,847
307,089
$591,122,791.28
7,444
Peel Region
• Assume willingness to spend $50,000 to prevent each QALY
• Discount QALYs & Cost Savings by 5% each year
• Target a 5% proportional reduction in incidence of diabetes
• c/o M. Mustafa Hirji
www.oahpp.ca
31
Strengths of DPoRT
• Meaningful
• Relevant for public health
• Simple
• Uses data and software available to PHUs
• Validated (in 2 external population cohorts)
www.oahpp.ca
Limitations of DPoRT
• Reliance on self-report measures (strength and a weakness)
• Use of physician-diagnosed diabetes as an outcome
• Does not apply to those < 20 years of age, institutionalized, or
on reserve
www.oahpp.ca
Next Steps for Peel Public Health
• Development of user guide
• Training Epidemiologists on using DPoRT
• Presentation to staff on the applications of DPoRT to support
public health practice
• Consultation tool
• Working with PH teams to help evaluate potential strategies
using DPoRT
www.oahpp.ca
Next Steps: New Knowledge Users
• Sandy Bay First Nations Community (SBFN) (Co-I: Sharon
Bruce, PhD)
• Regional Health Authorities (RHAs) via the Need To Know
(NTK) Team (Co-Is: Pat Martens PhD & Randy Fransoo PhD)
• Manitoba Health (KU: Patricia A. Caetano PhD: Lead
Epidemiologist and Director, Epidemiology & Surveillance
Public Health)
• Simcoe Muskoka District Health Unit (SMDHU) (KU: Dr. Charles
Gardner, MOH)
www.oahpp.ca
35
Updates to DPoRT
• DPoRT 2.0
• Costing
• Obesity Population Risk Tool (OPoRT)
www.oahpp.ca
36
Tools to inform the prevention of obesity and diabetes
Obesity Population Risk Tool
(OPoRT)
Baseline
BMI
Diabetes Population Risk Tool
(DPoRT)
Future
BMI
Diabetes
(incidence &
prevalence)
Risk Factors
Risk Factors
Diabetes Burden Tool
(DBT)
Diabetes Burden
 Health Care Utilization
 Diabetes Complications
 Costs (total and attributable)
Evaluation
Objective 3:
Evaluate the
effectiveness
and impact of
the KtoA process
using a case
study approach
to provide
description,
understanding
and assessment
of the knowledge
translation
strategies used
to put DPoRT
into action.
Framework for
Knowledge
Transfer
OBJECTIVE 2: Complete the
Knowledge-to-Action cycle
in different jurisdictions,
including: (i) Training and
supporting health
professionals and decision
makers to use DPoRT using
their available data on
diabetes trends and risk
factors; (ii) Assessing
barriers and facilitators of
DPoRT use; and, (iii)
Tailoring and delivering the
outputs of DPoRT analyses
that will inform decisions
about local programming
priorities.
Ottawa
Model of
Research Use
DPoRT
Adapted from Graham ID,
Logan J, Harrison MB, et al.
Lost in knowledge
translation: time for a map?
J Contin Educ Health Prof
2006;26:13-24
OBJECTIVE 1: Create and support partnerships among the researchers who developed the tool and the decision makers and other professionals
who will apply the tool in local and provincial health contexts in Ontario and Manitoba. This is a foundational objective that will underpin all aspects
www.oahpp.ca
of the project.
38
Points of consideration
• Little evidence on community-level interventions for diabetes
• Risk factor focus, rather than diabetes-focus in health units
• Epidemiologists and program planners working interactively
• Need to evaluate that population risk modeling actually results
in better planning
• Limitations of DPoRT
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39
Contact Information
• Laura Rosella ([email protected])
• Michael Lebenbaum ([email protected])
• Sheila Datta ([email protected])
www.oahpp.ca
References
1.
Rosella, L.C., Manuel, D.G, Burchill, C., Stukel, T.A. A population based risk algorithm for the development
of diabetes: Development and validation of the Diabetes Population Risk Tool Risk Tool (DPoRT). Journal of
Epidemiology and Community Health. 2011; 65(11): 613-20.
2.
Manuel, D.M., Rosella, L.C., Hennessy, D., Sanmartin, C., Wilson, K. Predictive risk algorithms in a
population setting: an overview. Journal of Epidemiology and Community Health 2012;66:859-865
3.
Rosella, L.C., Corey, P., Stukel, T.A., Mustard, C., Hux, J., Roos, L., Manuel, D.G. The role of ethnicity in
predicting diabetes risk at the population level. Ethnicity and Health. 2012;17(4):419-37.
4.
Rosella, L.C., Corey, P., Stukel, T.A., Mustard, C., Hux, J., Manuel, D.G. The influence of measurement error
on calibration, discrimination, and overall estimation of a risk prediction model. Population Health
Metrics. 2012 Nov 1;10(1):20
5.
Manuel D.G. and Rosella L.C. Commentary: Assessing population (baseline) risk is a cornerstone of
population health planning-looking forward to address new challenges. International Journal of
Epidemiology 2010;39:380-2.
6.
Manuel DG, Rosella L.C., Tuna M, Bennett C. How many Canadians will be diagnosed with diabetes
between 2007 and 2017? Assessing population risk. ICES Investigative Report. Toronto: Institute for Clinical
Evaluative Sciences; 2010.
www.oahpp.ca
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EXTRA SLIDES
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42
DPoRT K to A Grant Goals and Objectives
The OVERALL GOAL of the proposed KtoA project is for researchers and decision-makers in varied health
related settings to work collaboratively to build capacity and facilitate the application of DPoRT as a strategic
aid for population-based risk assessment, intervention and planning decisions. The specific OBJECTIVES of this
project to achieve this goal are to:
1.
Create and support partnerships among the researchers who developed the tool and the knowledge
users who will apply the tool in local and provincial health contexts in Ontario and Manitoba. This is a
foundational objective that will underpin all aspects of the project.
2.
Complete the Knowledge-to-Action knowledge application process (KtoA) cycle in different
jurisdictions, including:
1.
Training and supporting health professionals and decision-makers to use DPoRT using their
available data on diabetes trends and risk factors;
2.
Assessing barriers and facilitators of DPoRT use;
3.
Tailoring and delivering the outputs of DPoRT that will be used to inform programming and policy
decisions.
3.
Evaluate the effectiveness and impact of the KtoA process using a case study approach to provide
description, understanding and assessment of the knowledge translation strategies used to put DPoRT
into action.
www.oahpp.ca
43
Rosella et al. Ethnicity and Health 2012;17(4):419-37
www.oahpp.ca
10-year population risk (%)
9.85
10.11
10.06
7.83
Rosella et al. Ethnicity and Health
2012;17(4):419-37
7.95
7.97
Incident cases
386,964 396,624 395,215
321,724 326,737 327,671
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No
ethnicity
DPoRT
Full
ethnicity
No
ethnicity
DPoRT
Full
ethnicity
Model Performance of 3 algorithms
C-Statistic
No ethnicity
DPoRT
Full ethnicity
H-L χ2
No ethnicity
DPoRT
Full ethnicity
Males
Females
0.76
0.77
0.77
0.76
0.76
0.76
11.38
15.36
33.91
6.05
8.00
9.11
Rosella et al. Ethnicity and Health 2012;17(4):419-37
www.oahpp.ca