This project will study the treatment and rehabilitation of stroke patients in
Norway through statistical and simulation based modelling.
We will use standard statistical modelling techniques to analyze and
represent associations and causal effects among patient parameters like
age, sex, socio-economic status and ethnicity and dependent variables
like length of hospital stay, duration of rehabilitation, level of anxiety and
depression and health related quality of life. We will develop discrete
event simulation models to describe the different paths that stroke patients
follow through treatment and rehabilitation. We plan to make separate
sub-models for the different phases of the disease: An Incidence model
represents the random events of new stroke cases in the population. A
Pre-hospital model represents the phase until hospitalization. A hospital?s
stroke unit model represents internal queues, radiology and treatment
processes. A rehabilitation model describes factors that govern the utilization
of rehabilitation resources. A long-term care model represents duration and
level of care, while a municipality model describes the local support that the
patient receives. On top of all this we develop a demography model that
represents time trends in the population, which enables us to analyze how
the treatment-rehabilitation machinery will respond to an ageing population.
The analysis will uncover social and ethnic inequalities, as well as suboptimal
current use of resources, which can be rectified. The predictions of future
demands for treatment and rehabilitation will help us to identify bottlenecks
before they become a problem. The Ahus project NOR-SPOT has collected
detailed follow-up data from 1908 admissions to the stroke unit. In addition
we will utilize national databases like the Norwegian Patient Registry.
The combination of NOR-SPOT data and more coarse data for the entire
Norwegian stroke population will enable us to analyze both in depth and
width.
