A multistate model to evaluate COPD progression integrating drugs consumption data and hospital databases 
Abstract
Background
The increase in costs related to the diagnosis and treatment of chronic-degenerative diseases requires a better knowledge of the true care pathway of patients. The study objective was to explore, using multi-state modeling, how analyses of drug prescriptions and data obtained from hospital discharge sheets can be used in combination to build a model of patients health care pathway in a non experimental setting. The model was applied to Chronic Obstructive Pulmonary Disease (COPD).
Methods
Based on the GOLD guidelines, access to hospitalization for COPD and prescription pharmaceuticals were awarded to seven transients states theoretically progressive. The intensity of transition were estimated with the non-parametric method proposed by Aalen and Johansen for multi-state Markov models non-homogeneous in time.
Results
The COPD patients included in the study are 111190. Patients admitted with a diagnosis of non acute COPD had a growing probability over time of needing prescriptions for inhaled corticosteroids (ICS) or the set combination of long-acting beta-agonists (LABA) and ICS; they also had a rising probability of an exacerbation. The use of ICS alone or in combination with LABA delays a hospital admission for acute respiratory failure by about 6 months, as compared to short-acting beta-agonists or anticholinergics.
Conclusion
The probabilities of a transition and their distribution in relation to time, sex, age and clinical status can be a helpful tool for those operating in the health care sector, who are called upon to carry out decisions from the standpoints of both efficacious clinical management and an efficient use of resources.Full Text:
PDFDOI: https://doi.org/10.2427/11145
NBN: http://nbn.depositolegale.it/urn%3Anbn%3Ait%3Aprex-15640
References
Article Metrics
Metrics powered by PLOS ALM
Refbacks
- There are currently no refbacks.
Copyright (c) 2015 Epidemiology, Biostatistics and Public Health
EBPH Epidemiology, Biostatistics and Public Health | ISSN 2282-0930

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.