ArticleInternational journal of environmental research and public health2021
Influence of Pharmaceutical Copayment on Emergency Hospital Admissions: A 1978-2018 Time Series Analysis in Spain.
Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- The silence of opioids-dependent chronic pain patients: A text mining analysis from sex and gender perspective.PloS one · 2025Article
- Intersectional analysis of social determinants of health and their association with mortality in patients with multimorbidity.Journal of global health · 2024Article
- Multimorbidity, social determinants and intersectionality in chronic patients. Results from the EpiChron Cohort.Journal of global health · 2023Observational
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6 authors.
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Abstract
No studies have evaluated the influence of pharmaceutical copayment on hospital admission rates using time series analysis. Therefore, we aimed to analyze the relationship between hospital admission rates and the influence of the introduction of a pharmaceutical copayment system (PCS). In July 2012, a PCS was implemented in Spain, and we designed a time series analysis (1978-2018) to assess its impact on emergency hospital admissions. Hospital admission rates were estimated between 1978 and 2018 each month using the Hospital Morbidity Survey in Spain (the number of urgent hospital admissions per 100,000 inhabitants). This was conducted for men, women and both and for all-cause, cardiovascular and respiratory hospital discharges. Life expectancy was obtained from the National Institute of Statistics. The copayment variable took a value of 0 before its implementation (pre-PCS: January 1978-June 2012) and 1 after that (post-PCS: July 2012-December 2018). ARIMA (Autoregressive Integrated Moving Average) (2,0,0)(1,0,0) models were estimated with two predictors (life expectancy and copayment implementation). Pharmaceutical copayment did not influence hospital admission rates (with
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