Diabetes mellitus has become one of main burdens on public health in most countries. A tendency toward less physical activity has led to increased obesity and thus greater prevalence of type 2 diabetes (T2D), cardiovascular disease, and complications related to these [1]. Studies and statistics show that though general health has improved in Finland, differences between socioeconomic groups have actually increased [2]. While the quality of care in Finland is considered generally good, better cost-efficiency and control of risk factors are needed to improve the equity of health care and to prepare for the future costs and needs of aging populations [3].
Data from the patient register of T2D were analyzed to discover possible explanations for spatial differences in treatment outcomes and to be able to assess different health care practices between health care units in region of North Karelia, Finland. The role of primary health care (PHC) in chronic disease treatment is significant, and finding ways to improve the efficiency of the health care system in the future is considered essential.
A literature review and preliminary data analysis were used to evaluate the possible reasons behind spatial differences of T2D treatment outcomes. Patient register data cover multiple attributes of all T2D patients living in region of North Karelia. Register data were analyzed to find relations between patients’ treatment outcomes, spatial accessibility to a primary health care unit, and other patient characteristics. Geographic Information Systems software was used for geocoding address data and to calculate the road distances to the health care units.
Preliminary results showed that spatial accessibility does not have a statistically significant influence on treatment outcomes. Further data analysis with patient visit data did not indicate spatial accessibility as having a strong influence on patients’ utilization of health care services. The literature review showed the versatility of approaches associated with the study of spatial differences of chronic diseases but did not provide readily applicable methods for the research question.
Previously, it was known that spatial differences in treatment outcomes and preventive care exist in the area of interest. Although understanding of the influence of patient characteristics, health care resources, treatment practices, and spatial accessibility was increased with this study, no unambiguous explanatory factors for the spatial differences in treatment outcomes were discovered. New approaches for further study, need for more advanced analysis methods, and the need for additional data sources were noted.
References
[1] Shaw JE, Sicree R A, Zimmet PZ. Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res.Clin.Pract., 2010, 87, 1, 4-14
[2] Tarkiainen L, Martikainen P, Laaksonen M, Valkonen T. (2012). Trends in life expectancy by income from 1988 to 2007: decomposition by age and cause of death. Journal of Epidemiology and Community Health 66, 7, 573-578
[3] OECD. OECD Economic Surveys: Finland (2012). Organisation for Economic Co-operation and Development.
Supervisor
Stefan Thurner, Advanced Systems Analysis Program, IIASA
Note
Teppo Repo, of the University of Eastern Finland, is a citizen of Finland. He was funded by the IIASA Finnish National Member Organization and worked in the Advanced Systems Analysis Program during the YSSP.
Please note these Proceedings have received limited or no review from supervisors and IIASA program directors, and the views and results expressed therein do not necessarily represent IIASA, its National Member Organizations, or other organizations supporting the work.
Further information
International Institute for Applied Systems Analysis (IIASA)
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