Document Detail


Temporal properties of diagnosis code time series in aggregate.
MedLine Citation:
PMID:  24235118     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Time series are essential to health data research and data mining. We aim to study the properties of one of the more commonly available but historically unreliable types of data: administrative diagnoses in the form of the International Classification of Diseases, Ninth Revision (ICD9) codes. We use differential entropy of ICD9 code time series as a surrogate measure for disease time course and also explore Gaussian kernel smoothing to characterize the time course of diseases in a more fine-grained way. Compared to a gold standard created by a panel of clinicians, the first model classified diseases into acute and chronic groups with a receiver operating characteristic area under curve of 0.83. In the second model, several characteristic temporal profiles were observed including permanent, chronic, and acute. In addition, condition dynamics such as the refractory period for giving birth following childbirth were observed. These models demonstrate that ICD9 codes, despite well-documented concerns, contain valid and potentially valuable temporal information.
Authors:
Adler Perotte; George Hripcsak
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural    
Journal Detail:
Title:  IEEE journal of biomedical and health informatics     Volume:  17     ISSN:  2168-2208     ISO Abbreviation:  IEEE J Biomed Health Inform     Publication Date:  2013 Mar 
Date Detail:
Created Date:  2013-11-15     Completed Date:  2014-04-24     Revised Date:  2014-05-27    
Medline Journal Info:
Nlm Unique ID:  101604520     Medline TA:  IEEE J Biomed Health Inform     Country:  United States    
Other Details:
Languages:  eng     Pagination:  477-83     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Data Mining / methods*
Electronic Health Records
Entropy
Female
Humans
International Classification of Diseases*
Male
Medical Informatics Applications*
ROC Curve
Time Factors
Grant Support
ID/Acronym/Agency:
R01 LM006910/LM/NLM NIH HHS; R01 LM006910/LM/NLM NIH HHS; T15 LM007079/LM/NLM NIH HHS; T15 LM007079/LM/NLM NIH HHS
Comments/Corrections

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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