Analyzing non-infection-related health care utilization and health outcomes in people with type 2 diabetes during the COVID-19 pandemic: making use of individually linked statutory health insurance data and survey data

• Applicant: Professorin Dr. Andrea Icks
• Subject Area: Public Health, Healthcare Research, Social and Occupational Medicine
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 536622689

During the COVID-19 pandemic, a number of measures were implemented to reduce the number of infections. In difficult circumstances, adequate diagnostics and treatment for COVID-19 had to be organized. This also had an impact on the provision of health care. Many medical facilities reduced services of non-COVID-19 related health care. In addition, people feared the risk of infection and may have avoided using medical practices, emergency departments, or clinics. Both reduced supply and reduced demand may be reasons for reduced health care utilization. For COVID-19, chronic disease has been shown to be associated with a higher risk of COVID-19 infection as well as a higher risk of a severe outcome, i.e., the direct consequences of COVID-19. Similar associations can be assumed for the aforementioned indirect effects, i.e., with supply, utilization patterns, and potentially resulting health outcomes for other health concerns not directly related to COVID-19. Currently, it is unclear to what extent persons with chronic diseases are at higher risk for indirect consequences of the COVID-19 pandemic, and what reasons may be involved. Therefore, the objectives of our project are (1) to investigate healthcare utilization among people with diabetes. Furthermore, (2) we want to examine whether a potential change in utilization is associated with adverse health outcomes in this group of people. In addition, (3) we want to analyze whether fear of infection or COVID-19-related long-term health consequences or a reduction in healthcare provision led to cancelled appointments by patients and doctors respectively, and whether this had an impact on health outcomes of individuals with diabetes. Our analysis is based on the input-throughput-outcome model. The COVID-19 pandemic can be considered an exogenous environmental factor that directly influences COVID-19-related outcomes, as well as other health outcomes through changes in service utilization. For our project, we use health insurance data as well as clinical data from the disease management program (DMP) in combination with primary data from a cross-sectional survey that are individually linked.

• DFG Programme: Research Grants