title: Projection of the burden of type 2 diabetes mellitus in Germany: a demographic modelling approach to estimate the direct medical excess costs from 2010 to 2040.
abstract: OBJECTIVE
  To model the future costs of Type 2 diabetes in Germany, taking into account demographic changes, disease dynamics and undiagnosed cases.
  
  
  METHODS
  Using a time-discrete Markov model, the prevalence of diabetes (diagnosed/undiagnosed) between 2010 and 2040 was estimated and linked with cost weights. Demographic, epidemiological and economic scenarios were modelled. Inputs to the model included the official population forecasts, prevalence, incidence and mortality rates, proportions of undiagnosed cases, health expenditure and cost ratios of an individual with (diagnosed/undiagnosed) diabetes to an individual without diabetes. The outcomes were the case numbers and associated annual direct medical excess costs of Type 2 diabetes from a societal perspective in 2010€.
  
  
  RESULTS
  In the base case, the case numbers of diabetes will grow from 5 million (2.8 million diagnosed) in 2010 to a maximum of 7.9 million (4.6 million diagnosed) in 2037. From 2010 to 2040, the prevalence rate amonf individuals ≥40 years old will increase from 10.5 to 16.3%. The annual costs of diabetes will increase by 79% from €11.8 billion in 2010 to €21.1 billion in 2040 (€9.5 billion to €17.6 billion for diagnosed cases).
  
  
  CONCLUSIONS
  The projected increase in costs will be attributable to demographic changes and disease dynamics, and will be enhanced by higher per capita costs with advancing age. Better epidemiological and economic data regarding diabetes care in Germany would improve the forecasting accuracy. The method used in the present study can anticipate the effects of alternative policy scenarios and can easily be adapted to other chronic diseases.
authors.affiliation: Institute of Biometrics and Epidemiology, German Diabetes Center, Leibniz Center at Heinrich Heine University, Düsseldorf, Germany. regina.waldeyer@ddz.uni-duesseldorf.de
authors.forename: R
authors.initials: R
authors.lastname: Waldeyer
authors.forename: R
authors.initials: R
authors.lastname: Brinks
authors.forename: W
authors.initials: W
authors.lastname: Rathmann
authors.forename: G
authors.initials: G
authors.lastname: Giani
authors.forename: A
authors.initials: A
authors.lastname: Icks
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D017281:Cost of Illness; D003365:Costs and Cost Analysis; D057210:Delayed Diagnosis / Q000191:economics; D003924:Diabetes Mellitus, Type 2 / Q000175:diagnosis / Q000191:economics* / Q000453:epidemiology / Q000628:therapy*; D004180:Direct Service Costs / Q000639:trends; D005544:Forecasting; D005858:Germany / Q000453:epidemiology; D017048:Health Care Costs / Q000639:trends; D006801:Humans; D015994:Incidence; D008390:Markov Chains; D008875:Middle Aged; D018803:Models, Economic; D009026:Mortality; D011157:Population Dynamics / Q000639:trends; D015995:Prevalence