George Mnatzaganian1, Philip Ryan, Paul E Norman, Janet E Hiller. 1. School of Population Health and Clinical Practice, Discipline of Public Health, The University of Adelaide, South Australia, Australia. george.mnatzaganian@adelaide.edu.au
Abstract
OBJECTIVES: The main objectives of this study were to validate the hospital morbidity data (HMD) and to compare the performance of three comorbidity adjusting methods in predicting 1-year and 5-year all-cause mortality in a male general hospital population in Western Australia (WA). STUDY DESIGN AND SETTING: Population-based data were integrated with WA-linked data system. Deyo-Charlson Index, Enhanced-Charlson Index, and Elixhauser's method measured comorbidity. Mortality was modeled using Cox regression, and model discrimination was assessed by Harrell's C statistics. RESULTS: The HMD were most likely to identify major comorbidities, such as cancer, myocardial infarction, diabetes mellitus, and major operations. The presence of comorbidity was independently associated with an increased risk of adverse outcomes. All models achieved acceptable levels of discrimination (Harrell's C: 0.70-0.76). The Enhanced-Charlson Index matched the Deyo-Charlson Index in predicting mortality. Elixhauser's method outperformed the other two. Including information from past admissions achieved nonsignificant improvement in model discrimination. A dose-response effect was observed in the effect of repeated episodes on risk of 5-year mortality. CONCLUSION: Comorbidities diagnosed at different points in time may have different associations with the risk of adverse outcomes. More research is required to integrate the effect of repeated episodes in currently used methods that measure and adjust for comorbidity.
OBJECTIVES: The main objectives of this study were to validate the hospital morbidity data (HMD) and to compare the performance of three comorbidity adjusting methods in predicting 1-year and 5-year all-cause mortality in a male general hospital population in Western Australia (WA). STUDY DESIGN AND SETTING: Population-based data were integrated with WA-linked data system. Deyo-Charlson Index, Enhanced-Charlson Index, and Elixhauser's method measured comorbidity. Mortality was modeled using Cox regression, and model discrimination was assessed by Harrell's C statistics. RESULTS: The HMD were most likely to identify major comorbidities, such as cancer, myocardial infarction, diabetes mellitus, and major operations. The presence of comorbidity was independently associated with an increased risk of adverse outcomes. All models achieved acceptable levels of discrimination (Harrell's C: 0.70-0.76). The Enhanced-Charlson Index matched the Deyo-Charlson Index in predicting mortality. Elixhauser's method outperformed the other two. Including information from past admissions achieved nonsignificant improvement in model discrimination. A dose-response effect was observed in the effect of repeated episodes on risk of 5-year mortality. CONCLUSION: Comorbidities diagnosed at different points in time may have different associations with the risk of adverse outcomes. More research is required to integrate the effect of repeated episodes in currently used methods that measure and adjust for comorbidity.
Authors: Muhammad Shahreyar; Tamunoinemi Bob-Manuel; Rami N Khouzam; Mohammad W Bashir; Samian Sulaiman; Oluwaseun Akinseye; Arindam Sharma; April Carter; Samuel Latham; Sanjay Bhandari; Arshad Jahangir Journal: Ann Transl Med Date: 2018-01
Authors: Robert A Moran; Guillermo García-Rayado; Daniel de la Iglesia-García; Emma Martínez-Moneo; Esther Fort-Martorell; Eugenia Lauret-Braña; Mar Concepción-Martín; Fabio Ausania; Carlos Prieto-Martínez; Miguel González-de-Cabo; Noé Quesada-Vázquez; M Asunción Marcaide-Ruiz-de-Apodaca; José A Pajares-Díaz; Francia C Díaz; José L de-Benito; Jennifer Hinojosa-Guadix; Pilar Marqués-García; Jaume Boadas; Eduardo Bajador-Andreu; Oswaldo Moreno; Federico Argüelles-Arias; Gregorio Martín-Benítez; Carla Tafur-Sánchez; Jesús Leal-Téllez; Beatriz Romero-Mosquera; Ruben Hernaez; Georgios I Papachristou; Vikesh K Singh; Enrique de-Madaria Journal: United European Gastroenterol J Date: 2018-09-03 Impact factor: 4.623