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  • 标题:Administrative databases as a tool for identifying healthcare demand and costs in an over-one million population
  • 本地全文:下载
  • 作者:Fabiana Madotto ; Michele A Riva ; Carla Fornari
  • 期刊名称:Epidemiology, Biostatistics and Public Health
  • 印刷版ISSN:2282-0930
  • 出版年度:2013
  • 卷号:10
  • 期号:2
  • DOI:10.2427/8840
  • 语种:English
  • 出版社:PREX
  • 摘要:Background: the aim of this study was to assess healthcare demand of specific groups of population and their costs borne by Italian Health System, using healthcare administrative databases. Methods: demographic, clinical and economic data were obtained from datasets available at the Regional Health System, combined into a data warehouse (DENALI), using a probabilistic record linkage to optimize the data matching process. The study population consisted of more than 1 million people registered in 2005 at one Local Healthcare Unit of Lombardy. Eight different segments were identified. Costs occurring in 2005 for hospital admissions, drug prescriptions, outpatient medical specialist visits were quantified in each segment. Results: healthy people accounted for 53% of the population and cost € 180 per-capita. Subjects with only one chronic disease made up 16% of the population and cost € 916 per-capita, those affected by several chronic diseases accounted for 13% and cost € 3 457 per-capita. Hospitalizations were the cost driver in five segments, ranging from 42% to 89% of total expenditures. Outpatient visits were the cost driver among healthy subjects (54%) and those with a possible chronic disease (42%), while drug costs ranged between 4% (“acute event”) and 32% (“one chronic disease”). Overall, healthcare cost was € 809 per-capita. Conclusions: healthcare costs were mainly determined by people affected by chronic conditions, even if “healthy people” ranked third for total expenditure. These costs need an appropriate identification of healthcare demand, that could be efficiently monitored through the use of administrative databases.
  • 关键词:Administrative databases; Segmentation of population; Healthcare demand; Healthcare costs
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