Future Incidence, Prevalence and Cost of Diabetes: An applied example of using a population prediction tool to inform public health Laura Rosella Nancy Ramuscak Michael Lebenbaum Amalia Plotogea David Mowat Canadian Public Health Association May 27, 2014

Population Risk Algorithm: Diabetes Population Risk Tool (DPoRT) Age Body weight Blood pressure Ethnicity Etc. Likelihood of developing Type 2 diabetes (T2DM) E.g. 20% in 10 years Prevention approach -Treatment *Individual focus Age distribution % obese % low income Ethnic distribution Etc. Ten-year T2DM risk in a region (community, country, health region) Prevention approach -Targets -Magnitude and scale of burden

Diabetes Population Risk Tool (DPoRT) Vision: To enable decision-makers to use routinely collected population characteristics to estimate the number of new diabetes cases in their population of interest for the purpose of: Resource planning Prevention Understanding distribution of risk in the population Facilitating decision-making and priority setting Used to quantify the impact that changes in baseline risk factors will have on future diabetes incidence Designed to be applied to routinely collected and publicly available data allowing the tool to be used by a wide audience. Source: Rosella L C et al. J Epidemiol Community Health doi: /jech

OBJECTIVE 2: Complete the KtoA cycle : (i) Training and supporting health professionals and decision makers to use DPoRT (ii) Assessing barriers and facilitators of DPoRT use (iii) Tailoring and delivering the outputs of DPoRT to inform decisions OBJECTIVE 1: Create and support partnerships OBJECTIVE 3: Evaluate the process 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: DPoRT Knowledge to Action

Canadian Community Health Survey (CCHS) Restrict sample (E.g. Peel residents who are age ≥20 without diabetes) Re-code CCHS variables for DPoRT Use DPoRT risk equation to estimate individual 10-year risk and the number of diabetes cases they represent Identify high risk Individuals Identify the effects of prevention activities Identify future health care needs Calculate summary statistics for overall population Identify risk across population strata Overview of DPoRT application 5

Projecting Future Burden of Diabetes Population Total # of incident cases Diabetes risk (%) 95% CI Peel89, Ontario869, High risk (top 10%)28, Obese28, South Asian 15,

Total number of incident cases of diabetes and projected risk by Body Mass Index (BMI), Peel,

Intervention Scenarios Intervention scenarioAverage risk difference for individuals (%) Average number needed to treat (NNT) # diabetes cases averted 1% weight loss among total population ,054 10% weight loss among those who are obese ,576 15% risk reduction among those in the top 10% of risk ,084 Multiple intervention strategy (#1 & #3) ,952

Attributable Costs of Diabetes ScenarioNumber of incident cases in 10-years Number of cases averted with intervention Cost (10-year) Total cost of diabetes89,787-- $580,293,140 1% weight loss among total population 86,2343,054 ($20,294,930) 10% weight loss among those who are obese 28,1148,576 ($93,607,636) 15% risk reduction among those in the top 10% of risk 26,1334,084 ($24,943,592)

Next Steps Knowledge to Action evaluation Application to real world examples Communication of results to public health staff Use during program planning and decision-making Update with each new release of Canadian Community Health Survey data

Thank you! Questions?