72b5675a46314fa67670ab56aa29b655 1-s2.0-S0167668725001222-main.pdf 2774c3e860bc16824def8fdfb61115b5487fa897 1-s2.0-S0167668725001222-main.pdf 8c68a3e8565265a85c03bf970a4d3f378f61a819c36fb33d6d57d1f504afbaac 1-s2.0-S0167668725001222-main.pdf Title: Back to normal? a method to test and correct a shock impact on healthcare usage frequency data Subject: Insurance Mathematics and Economics, 126 (2026) 103175. doi:10.1016/j.insmatheco.2025.103175 Keywords: Health services,Risk modelling,Poisson offset,Covid-19,Time series,Pre-processing Author: David Moriña Creator: Elsevier Producer: Acrobat Distiller 8.1.0 (Windows) CreationDate: Fri Nov 28 13:09:32 2025 CET ModDate: Fri Nov 28 22:07:34 2025 CET Custom Metadata: yes Metadata Stream: yes Tagged: yes UserProperties: no Suspects: no Form: none JavaScript: no Pages: 9 Encrypted: no Page size: 595.276 x 793.701 pts Page rot: 0 File size: 2893014 bytes Optimized: yes PDF version: 1.7 name type encoding emb sub uni object ID 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Children: Item: Title: 1 Introduction Item: Title: 2 Background Item: Title: 3 Methods and data Children: Item: Title: 3.1 Shock impact detection and evaluation Item: Title: 3.2 Implications for pre-processing data net of a shock impact in GLM frequency modelling Item: Title: 3.3 Gap of cost estimation Item: Title: 3.4 Data Item: Title: 4 Results Item: Title: 5 Discussion Item: Title: 6 Conclusion Info: Title: Back to normal? a method to test and correct a shock impact on healthcare usage frequency data Author: David Moriña Subject: Insurance Mathematics and Economics, 126 (2026) 103175. doi:10.1016/j.insmatheco.2025.103175 Keywords: Health services,Risk modelling,Poisson offset,Covid-19,Time series,Pre-processing Creator: Elsevier Producer: Acrobat Distiller 8.1.0 (Windows) CreationDate: Fri Nov 28 13:09:32 CET 2025 ModDate: Fri Nov 28 22:07:34 CET 2025 ID: 0xada71a12c307d8bc347116a1d0322222, 0xcacacffb206b61119fc39d82706936cf Filters: FilterPipeline: FlateDecode Fonts: Type0: Font: 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Insurance Mathematics and Economics, 126 (2026) 103175. doi:10.1016/j.insmatheco.2025.103175 Health services Risk modelling Poisson offset Covid-19 Time series Pre-processing Back to normal? a method to test and correct a shock impact on healthcare usage frequency data David Moriña Amanda Fernández-Fontelo Montserrat Guillén VoR 28th November 2025 Acrobat Distiller 8.1.0 (Windows) Health services,Risk modelling,Poisson offset,Covid-19,Time series,Pre-processing 28th November 2025 10.1016/j.insmatheco.2025.103175 noindex journal 2026-01-01 1 January 2026 10.1016/j.insmatheco.2025.103175 0167-6687 103175 Insurance Mathematics and Economics 103175 https://doi.org/10.1016/j.insmatheco.2025.103175 126 https://www.elsevier.com/tdm/tdmrep-policy.json 1 2025-11-28T12:09:32 Elsevier 2025-11-28T21:07:34 2025-11-28T21:07:34 uuid:1b499bed-4ce8-4c0c-b682-0d58baae1cbe uuid:b6ed5266-03cb-4855-90c0-636283357f42 True Pages: Page: Label: 1 Annotations: Annotation: Subtype: Link Contents: 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