The impact of integrated care on health care utilization and costs in a socially deprived urban area in Germany: A difference‐in‐differences approach within an event‐study framework
研究德国社会贫困城市地区一项整合护理计划对医疗利用和费用的因果效应，发现该计划显著增加了住院、急诊和门诊次数及相关费用，可能改善了医疗可及性或识别了未满足需求。
We investigated the impact of an integrated care initiative in a socially deprived urban area in Germany. Using administrative data, we empirically assessed the causal effect of its two sub-interventions, which differed by the extent to which their instruments targeted the supply and demand side of healthcare provision. We addressed confounding using propensity score matching via the Super Learner machine learning algorithm. For our baseline model, we used a two-way fixed-effects difference-in-differences approach to identify causal effects. We then employed difference-in-differences analyses within an event-study framework to explore the heterogeneity of treatment effects over time, allowing us to disentangle the effects of the sub-interventions and improve causal interpretation and generalizability. The initiative led to a significant increase in hospital and emergency admissions and non-hospital outpatient visits, as well as inpatient, non-hospital outpatient, and total costs. Increased utilization may indicate that the intervention improved access to care or identified unmet need.