RESUMO
This article addresses the question of how climate change may affect health and to what extent real-world data can contribute to research in this topic area. Climate change is altering the environmental and living conditions of humankind, and has thus also become a relevant health problem. The increase in extreme weather events, changes in exposure to UV and air pollution, and the climate-associated spread of allergens or novel pathogens are significantly changing the spectrum of diseases and the need for medical care in the population. However, in Germany, only few findings on the consequences for the healthcare system and on particularly affected population groups exist so far. Real-world data (primary data, register data, and administrative data) in combination with environmental exposure data and other relevant data (e.g., socio-economic data) have the potential to significantly advance research on the health consequences of climate change. This paper identifies changes in environmental and living conditions and associated health risks. It describes the databases that are generally available for analysing health effects of climate change. A concrete example is used to show how individual health data (in this case claims data of the statutory health insurance), environmental exposure data and other data can be successfully combined. Finally, the article offers a comprehensive overview of open research questions that can be answered with real-world data.
Assuntos
Poluição do Ar , Mudança Climática , Alemanha , Poluição do Ar/efeitos adversos , Exposição Ambiental/efeitos adversos , AlérgenosRESUMO
BACKGROUND: Measuring the quality of provided healthcare presents many challenges, especially in the context of medical rehabilitation. Rehabilitation is based on a holistic biopsychosocial model of health that includes a person's long-term functioning; hence, outcome domains are very diverse. In Germany, rehabilitation outcomes are currently assessed via patient and physician surveys. Health insurance claims data has the potential to simplify current quality assurance procedures in Germany, since its comprehensive collection is federally mandated from every healthcare provider. By using a cross-sectoral approach, quality assessments in rehabilitation can be adjusted for the quality provided in previous sectors and individual patient risk factors. METHODS: SEQUAR combines two studies: In a prospective longitudinal study, 600 orthopedic rehabilitation patients and their physicians are surveyed at 4 and 2 time points, respectively, throughout rehabilitation and a follow-up period of 6 months. The questionnaires include validated instruments used in the current best-practice quality assurance procedures. In a retrospective cohort study, a nationwide claims database with more than 312,000 orthopedic rehabilitation patients will be used to perform exploratory analysis for the identification of quality indicators. The identified SEQUAR claims data quality indicators will be calculated for our prospective study participants and tested for their ability to approximate or replace the currently used, best-practice quality indicators based on primary data. DISCUSSION: The identified SEQUAR quality indicators will be used to draft a novel, state-of-the-art quality assurance procedure that reduces the administrative burden of current procedures. Further research into the applicability to other indications of rehabilitation is required. TRIAL REGISTRATION: WHO UTN: U1111-1276-7141; DRKS-ID: DRKS00028747 (Date of Registration in DRKS: 2022/08/10).
