RESUMO
This study aims to estimate direct health-related costs for victims of intimate partner violence (IPV) using nationwide linked data based on police reports and two healthcare registers in Finland from 2015 to 2020 (N = 21,073). We used a unique register dataset to identify IPV victims from the data based on police reports and estimated the attributable costs by applying econometric models to individual-level data. We used exact matching to create a reference group who had not been exposed to IPV. The mean, unadjusted, attributable healthcare cost for victims of IPV was 6,910 per individual over the 5-year period after being first identified as a victim. When adjusting for gender, age, education, occupation, and mental-health- and pregnancy-related diagnoses, the mean attributable health-related cost for the 5 years was 3,280. The annual attributable costs of the victims were consistently higher than those for nonvictims during the entire study period. Thus, our results suggest that the adverse health consequences of IPV persist and are associated with excess health service use for 5 years after exposure to IPV. Most victims of IPV were women, but men were also exposed to IPV, although the estimates were statistically significant only for female victims. Victims of IPV were over-represented among individuals outside the labor force and lower among those who were educated. The total healthcare costs of victims of IPV varied according to the socioeconomic factors. This study highlights the need for using linked register data to understand the characteristics of IPV and to assess its healthcare costs. The study results suggest that there is a significant socioeconomic gradient in victimization, which could also be useful to address future IPV prevention and resource allocation.
Assuntos
Vítimas de Crime , Violência por Parceiro Íntimo , Masculino , Gravidez , Humanos , Feminino , Pré-Escolar , Polícia , Saúde Mental , Custos de Cuidados de SaúdeRESUMO
In 2019, the Innovative Medicines Initiative (IMI) funded the ConcePTION project-Building an ecosystem for better monitoring and communicating safety of medicines use in pregnancy and breastfeeding: validated and regulatory endorsed workflows for fast, optimised evidence generation-with the vision that there is a societal obligation to rapidly reduce uncertainty about the safety of medication use in pregnancy and breastfeeding. The present paper introduces the set of concepts used to describe the European data sources involved in the ConcePTION project and illustrates the ConcePTION Common Data Model (CDM), which serves as the keystone of the federated ConcePTION network. Based on data availability and content analysis of 21 European data sources, the ConcePTION CDM has been structured with six tables designed to capture data from routine healthcare, three tables for data from public health surveillance activities, three curated tables for derived data on population (e.g., observation time and mother-child linkage), plus four metadata tables. By its first anniversary, the ConcePTION CDM has enabled 13 data sources to run common scripts to contribute to major European projects, demonstrating its capacity to facilitate effective and transparent deployment of distributed analytics, and its potential to address questions about utilization, effectiveness, and safety of medicines in special populations, including during pregnancy and breastfeeding, and, more broadly, in the general population.