Open AccessWhat “big population data” tells us about neurological disorders comorbidity
Author(s) -
Sara Anwar,
David Cawthorpe
Publication year - 2016
Publication title -
journal of hospital administration
Language(s) - English
Resource type - Journals
eISSN - 1927-7008
pISSN - 1927-6990
DOI - 10.5430/jha.v5n6p75
Subject(s) - comorbidity , odds ratio , medicine , confidence interval , odds , population , diagnosis code , stroke (engine) , disease , psychiatry , pediatrics , logistic regression , mechanical engineering , engineering , environmental health
Objective: To use a large population dataset to examine neurological disorder comorbidity. Seventeen main classes of Diagnosed International Classification of Disease (ICD) disorder codes were grouped and compared to ICD-9 Nerurological disorder codes.Methods: Calgary, Alberta, health zone diagnosis, sex and age data from 1994-2009 physician billings (n = 763,449) were grouped and tallied on the basis of the presence or absence of any neurological disorder across the 17 remaining ICD main disorder classes and represented as odds ratios (ORs with 95% confidence intervals).Results: Within the ICD categories the 17 classes were ranked by ORs: Ill-defined conditions (OR 7.42), musculoskeletal and connective tissue system disorders (OR 4.22), and psychiatric disorders (OR 3.81) were the ranked the highest main classes, respectively. Thirteen additonal main classes had ORs greaeter than 2.00.Conclusions: There was a strong relationship between neurological disorders and the ICD main classes. The results of this broad stroke analysis point to the requirement for analysis of the both the temporal relationships (e.g., before vs. after) between neurological disorders and comorbid disorderss as well as more fine-grained description of the specifice intra-class disorders underlying the reported odds ratios.