Social Inequality in Medical Treatment v1

Social Inequality in Medical Treatment Objective: This project investigates the extent and nature of social inequality in potentially inappropriate medication (PIM) among individuals with multimorbidity in two studies. Study 1: This study identifies the socioeconomic factors associated with PIM among individuals with multimorbidity. Study 2: This study analyzes geographic and practice-related variations in the use of PIM, using the individual's social position as an indicator. Design: The project comprises two population-based cohort studies. Population: The primary study population consists of all Danish residents from January 1, 2014, to December 31, 2021. Participants will be followed until emigration, death, or the end of the study. Data: The studies will be based on data from Danish national registers, which contain information on individual diagnoses recorded in secondary healthcare, redeemed prescriptions, general practice affiliation, contact patterns in primary and secondary healthcare, as well as geographic, demographic, social, cultural, and economic variables. These data will be retrieved from sources such as the Danish Civil Registration System, the National Patient Register, the Psychiatric Central Research Register, the National Prescription Register, the Health Insurance Register, Statistics Denmark, and the DREAM database. Variables: PIM will be identified in the registers using a modified version of the START/STOPP criteria, based on ATC and ICD-10 codes, which is a recognized screening tool for identifying PIM. Social inequality, based on Bourdieu's theoretical perspectives, will be operationalized through a set of factors identified by a review of the existing literature and variable lists from the registers. Thus, the analyses will be based on variables representing economic capital (e.g., housing type, assets and debts, lifetime income, ownership), cultural capital (e.g., household educational background, previous employment sector), and social capital (e.g., marital status, children, relationships). Analysis: The first study will identify economic, cultural, and social risk factors for PIM among multimorbid individuals. The second study will estimate the distribution of PIM across geographic characteristics (rural vs. urban, municipality size, etc.) and general practice characteristics (solo vs. group practice, background population, etc.). The primary analytical approach will be multivariate Poisson regression, allowing for the independent analysis of sub-outcomes with different relevant risk populations, which can then be aggregated into an "observed-to-expected ratio" across practices that can be compared with social position characteristics. In the analysis of geographic and general practice-related characteristics, the study will examine whether characteristics can be identified that have potential significance for the extent of social inequality in the frequency of PIM.