IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

The Evolution of Comorbidities in Hospital Administrative Databases: A 15-Year Analysis

The Evolution of Comorbidities in Hospital Administrative Databases: A 15-Year Analysis
View Sample PDF
Author(s): Alberto Freitas (Faculty of Medicine of the University of Porto (FMUP), Portugal & Center for Health Technology and Services Research (CINTESIS), Portugal), Isabel Garcia Lema (Faculty of Medicine of the University of Porto (FMUP), Portugal & Center for Health Technology and Services Research (CINTESIS), Portugal)and Altamiro Costa-Pereira (Faculty of Medicine of the University of Porto (FMUP), Portugal & Center for Health Technology and Services Research (CINTESIS), Portugal)
Copyright: 2020
Pages: 12
Source title: Hospital Management and Emergency Medicine: Breakthroughs in Research and Practice
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-2451-0.ch006

Purchase

View The Evolution of Comorbidities in Hospital Administrative Databases: A 15-Year Analysis on the publisher's website for pricing and purchasing information.

Abstract

The analysis of inpatient comorbidities is important for hospital management, epidemiological studies, and health services research and planning. This paper aims to study the evolution of coded comorbidities in a nationwide administrative database. Specifically, data from Portuguese hospitals over the period 2000-2014 was used. Secondary diagnoses, coded with ICD-9-CM, were used to identify comorbidities in 9,613,563 inpatient episodes, using both the Elixhauser and the Charslon/Deyo methods. A description of comorbidities evolution over years, including an analysis of the associated principal diagnosis, was carried out. Results clearly evidence a positive association between the number of secondary diagnoses and coded comorbidities. It can be argued that the increased number of comorbidities over time is mostly related to an increase in the quality of coded data, and not so much to an increase in the severity of treated patients. Data analysts, researchers and decision makers should be alert to possible data quality bias, such as completeness, when using administrative databases.

Related Content

Nouha Arfaoui, Jalel Akaichi. © 2020. 26 pages.
Manel Saad Saoud, Abdelhak Boubetra, Safa Attia. © 2020. 18 pages.
Jim Ryan, Barbara Doster, Sandra Daily, Carmen Lewis. © 2020. 26 pages.
Rakhee, M. B. Srinivas. © 2020. 13 pages.
Rui Veloso, Filipe Portela, Manuel Filipe Santos, José Machado, António da Silva Abelha, Fernando Rua, Álvaro Silva. © 2020. 16 pages.
Alberto Freitas, Isabel Garcia Lema, Altamiro Costa-Pereira. © 2020. 12 pages.
Filipe Portela, Manuel Filipe Santos, António da Silva Abelha, José Machado, Fernando Rua. © 2020. 10 pages.
Body Bottom