Statistical methods and epidemiology of chronic conditions in the field of general practice and family medicine

Abstract

The field of general practice and family medicine is diverse and has to deal with several complex health problems. Essential characteristics of general practitioner (GP) services cover among others a comprehensive, patient-focused care and the coordination of treatment through the wider health care system to sufficiently meet the patients’ needs. By providing primary health care for all, GP services may contribute to a more coherent level of care across different population groups. The focus of this dissertation was on analyzing patterns and determinants of major topics on chronic conditions in relation to social discrepancies in the German population. Our results show that the coexistence of multiple chronic conditions - referred to as multimorbidity - was not only more prevalent but also occurred earlier in age in socially deprived groups, which requires appropriate management. More advanced methods are vital to analyze trends and developments over time to adequately capture the population needs. Accordingly, an algorithm for modeling time-varying coefficients in discrete time-to-event settings by recursive partitioning was proposed. It was shown that the proposed algorithm can be useful in applications in medical and social science.