Healthcare administrative databases are becom- ing more and more important and reliable sources of clinical and epidemiological information. They are able to track sev- eral interactions between a patient and the public healthcare system. In the present study, we make use of data extracted from the administrative data warehouse of Regione Lom- bardia, a region located in the northern part of Italy whose capital is Milan. Data are within a project aiming at provid- ing a description of the epidemiology of Heart Failure (HF) patients at regional level, to profile health service utiliza- tion over time, and to investigate variations in patient care according to geographic area, socio-demographic character- istic and other clinical variables. We use multi-state models to estimate the probability of transition from (re)admission to discharge and death adjusting for covariates which are state dependent. To the best of our knowledge, this is the first Italian attempt of investigating which are the effects of pharmacological and outpatient cares covariates on patient’s readmissions and death. This allows to better characterise disease progression and possibly identify what are the main determinants of a hospital admission and death in patients with Heart Failure.

Multi-state approach to administrative data on patients affected by chronic heart failure

Grossetti, Francesco
;
Paganoni, Anna Maria
Validation
2018

Abstract

Healthcare administrative databases are becom- ing more and more important and reliable sources of clinical and epidemiological information. They are able to track sev- eral interactions between a patient and the public healthcare system. In the present study, we make use of data extracted from the administrative data warehouse of Regione Lom- bardia, a region located in the northern part of Italy whose capital is Milan. Data are within a project aiming at provid- ing a description of the epidemiology of Heart Failure (HF) patients at regional level, to profile health service utiliza- tion over time, and to investigate variations in patient care according to geographic area, socio-demographic character- istic and other clinical variables. We use multi-state models to estimate the probability of transition from (re)admission to discharge and death adjusting for covariates which are state dependent. To the best of our knowledge, this is the first Italian attempt of investigating which are the effects of pharmacological and outpatient cares covariates on patient’s readmissions and death. This allows to better characterise disease progression and possibly identify what are the main determinants of a hospital admission and death in patients with Heart Failure.
2018
2017
Grossetti, Francesco; Ieva, Francesca; Paganoni, Anna Maria
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/4015748
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