Population prevalence of disease risk factors and economic consequences for

the healthcare system- possible scenarios

Inna FeldmanUppsala University

Inna.feldman@kbh.uu.se

Estimation of future costs

Future

Health (risk factors)

Health (risk factors)

Morbidity Morbidity

CostsCosts

Health (risk factors)

Morbidity

Costs

Present Past

Compare

Compare

Change

Risk factors: BMI>30, obesity Daily smoking Lack of exercise, physical activity less than 2h/week Risk alcohol consumption (AUDIT)Source: Population survey

Age group: adults, 20-84 years old (4 age groups)

Costs: heathcare costs per patient/yearSource: Stockholm County´s VAL databases

Example for prevalence: Uppsala County (low risk factors - prevalence) Sörmland County (high risk factors - prevalence)

Base for economic consequences:: lower number of new cases (reduced incidence) due to positive development of risk factors

Starting points

BMI>30 Smoking Lack of exercise

Risk alcohol consumption

x x x

x x x

x x x

x x x x

x

x x

x x

x x

x x x x

x x x

Diabetes

Ischaemic heart disease

Stroke

Colon cancer

Lung cancer

Breast cancer

Prostate cancer

COPD

Depression

Fractures

Diagnoses:

Disease risk factors

Risk factors – related risks (RR)

Relative risk (RR) is the risk of an event (or of developing a disease) relative to exposure.

Relative risk is a ratio of the probability of the event occurring in the exposed group versus a non-exposed group

The model is based on related risks for these four risk factors

Risk factors – sources

Swedish and international studies Age- and gender-specific Can be updated according to new studies and new results

Män Kvinnor Källor 20-49 50-64 65-74 75-84 20-49 50-64 65-74 75-84 Diabetes 1,1 1,2 1,15 1,15 1,1 1,2 1,2 1,2 Willi et al, 2007 Ichemisk

hjärtsjukdom 4,4 2,9 1,8 1,4 4,5 3,4 2,1 1,5 Prochaska & Hilton,

2012 Stroke 3,4 2,6 1,9 1,5 3,7 3,0 2,1 1,3 Colditz et al, 1998;

Robbins et al, 1994 Koloncancer 1,2 1,2 1,2 1,2 1,2 1,2 1,2 1,2 Giovannucci, 2001;

Parkin, 2011 Lungcancer 14,3 26,4 28,0 21,6 11,5 16,1 14,1 10,6 Parkin, 2011 KOL 3,4 10,6 12,3 11,8 2,7 9,3 10,8 7,5 Lindberg, 2007 Depression 1,02 1,02 1,02 1,02 1,02 1,02 1,02 1,02 Buden et al, 2010 Höftfraktur 1,8 1,8 1,8 1,8 1,8 1,8 1,8 1,8 Marks, 2009

BMI>30 Smoking Lack of exercise

Risk alcohol consumption

6,4 1,2 2

1,7 2,9 1,3

1,3 2,6 2,2

1,5 1,2 1,6 1,8

26,4

- - - -

1,2 1,1

10,6 1,1

1,3 1,02 1,76 2

1,8 2 1,2

Men, 50-64 years old

Relative risks - example

Diagnoses:

Diabetes

Ischaemic heart disease

Stroke

Colon cancer

Lung cancer

Breast cancer

Prostate cancer

COPD

Depression

Fractures

BMI>30 Smoking Lack of exercise

Risk alcohol consumption

7,3 1,2 2

1,9 3,4 1,3

1,4 3,0 2,2

1,5 1,2 1,6 1,8

16,1

1,7 - 1,2 -

- -

9,3 1,1

1,3 1,02 1,7 2

1,8 2 1,2

Women, 50-64 years old

Relative risks - example

Diagnoses:

Diabetes

Ischaemic heart disease

Stroke

Colon cancer

Lung cancer

Breast cancer

Prostate cancer

COPD

Depression

Fractures

IF is defined as the percent reduction in desease incidence because of reduction of a risk factor prevalence to a certain level

IF=[(P2-P1)+RR(P1-P2)]/[(1-P1)+RR*P1]

Example: Smoking P1=0,13 (13%) P2=0,1 (10%)

Lung cancer RR=26 IF=0,17

A reduction in smoking rates from 13% to 10% results in a reduction in the incidence of lung cancer by 17%.Stroke

RR=2,6 IF=0,04 A reduction in smoking rates from 13% to 10% results in a reduction in the incidence of stroke by 4%.

How the change in risk factors influences disease incidence: IF ”Impact fraction”

Relative risks: Swedish and international scientific studies, gender- and age-specific

Incidence: Swedish registers and scientific studies

Prevalence of gender- and age-specific risk factors used to estimate number of new cases

Development of ealier models from Uppsala County

The model can be adapted to different populations by taking into account the existing age structure and the prevalence of risk factors

The Model

The costs

Annual health care costs for a person with a respective diagnosis

Based on Stockholm County’s database

Mainly costs for the first year of disease

Did not include medication costs

Can be updated

Time perspective

How long does it take to reduce the risk?Differs for different diseases and risk factorsLack of studies

Assumption:

Changing in RR

0

2

4

6

8

10

12

14

16

18

Time

RR

The risk factors developed positively with a reduction in prevalence by 1% for every gender and age group

Example: Women, 50-64 years old

BMI>30 Smoking Lack of exercise

Risk alcohol consumption

2011 16% 14% 22% 6%

2016 15% 13% 21% 5%

Results 1: Uppsala County

BMI>30 Smoking Lack of exercise

Risk alcohol consumption

-39 -2 -12

-8 -19 -4

-1 -1

-1 -1 -1

-7

-1

-1 -1

-34 -1

-1 -1 -2

-3 -3 -3 -1

-49 -67 -24 -4

Diabetes

Ischaemic heart disease

Stroke

Colon cancer

Lung cancer

Breast cancer

Prostate cancer

COPD

Depression

Fractures

Total:

Diagnoses:

Reduction in number of new cases

If risk factors prevalence decreases by 1%:

BMI>30 2MM -1%

Smoking 4MM -2%

Lack of exercise 1,2MM -0,5%

Risk alcohol consumption

0,2MM -0,1%

Expected yearly health care costs of the diseases in Uppsala County: 257MM

Yearly savings

BMI>30 Smoking Lack of exercise

Risk consumption

of alcohol

2011 18% 19% 21% 8%

2016 17% 18% 20% 7%

Results 1: Sörmland County

The risk factors develop positively with a reduction in prevalence by 1% for every gender and age group

Example: Women, 50-64 years old

BMI>30 Smoking Lack of exercise

Risk alcohol consumption

-30 -2 -11

-7 -15 -4

-1 -1

-1 -1 -1

-6

-1

0 -29 -1

0 -1 -1

0 -3 -3

-39 -57 -22 -3

Diabetes

Ischaemic heart disease

Stroke

Colon cancer

Lung cancer

Breast cancer

Prostate cancer

COPD

Depression

Fractures

Total:

Diagnoses:

Reduction in number of new cases

BMI>30 1,4MM -0,6%

Smoking 3,5MM -1,5%

Lack of exercise 1,0MM -0,4%

Risk alcohol consumption

0,1MM -0,06%

Yearly savings

If risk factors prevalence decreases by 1%:

Expected yearly healthcare costs of the diseases in Sörmland County: 237MM

Uppsala - Sörmland: comparison of BMI and smoking

Risk factors Uppsala Sörmland

BMI>30 -1% -0,6%

Smoking -2% -1,5%

Lack of exercise -0,5% -0,5%

Risk alcohol consumption -0,1% -0,06%

Uppsala - Sörmland: relative savings

Strengths

Can include as many diagnoses as we have data for:IncidenceRisk factors and RRCosts

Can be used to calculate other HE-parameters, as QALY

Easy to understand and to use

Can be applied to local data

Weaknesses

Based on the population at baseline, should include population prognosis

Time aspect, more careful estimation

Some risk factors significantly correlate, overestimation

The model estimates only one-year reduction in morbidity, but changes in life style are likely to are affect morbidity for several more years - underestimation

Policy relevance

Policy options

Risk Factors

Disease prevalence

Economic consequences

The decrease in the prevalence risk factors can result in significant

cost savings for the healthcare system

Relative savings depend on the baseline level of the risk factor

which influences the amount of cost savings

The model takes into account only healthcare costs (it can include

other societal costs and health effects)

This model may be used in other relevant studies

Conclusions

Development

Just now: Data program with user - friendly interface to make different

estimations

Coming soon: Inclusion of other societal costs Calculation of QALY Possible to make estimations for different time perspectives

Discussion?