NDLI: A Method for Determining an Emergency Readmission Time Window for Better Patient Management

Content Provider	IEEE Xplore Digital Library
Author	Demir, E. Chaussalet, T. Haifeng Xie Millard, P.H.
Copyright Year	2006
Description	Author affiliation: Health & Social Care Modelling Group, Westminster Univ., London (Demir, E.; Chaussalet, T.; Haifeng Xie; Millard, P.H.)
Abstract	This paper introduces a modelling approach to determining the appropriate width of a time window within which an admission is classified as a readmission. The approach is based on an intuitive idea that patients, who are discharged from hospital, can be broadly considered as consisting of two groups - a group that is at high risk of readmission and a group that is at low risk. Using national data from the London area (UK), we demonstrate its usefulness in the case of chronic obstructive pulmonary diseases (COPD), one of the leading causes of early readmission. Although marked regional differences exist for the optimal width of the time window for COPD patients, our findings are largely inline with figures used by the government, hence provide some support for the use of 28 days as the time window for defining COPD readmissions. The novelty of this modelling approach lies in its ability to estimate an appropriate time window based on evidence objectively derived from operational data. Therefore, it can provide a means of monitoring performance for hospitals, and can potentially contribute to the better management of patient care
Starting Page	789
Ending Page	793
File Size	195812
Page Count	5
File Format	PDF
ISBN	0769525171
ISSN	10637125
DOI	10.1109/CBMS.2006.15
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-22
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Disaster management Hospitals Diseases Histograms Government Patient monitoring Social factors Surgery Pediatrics Gynaecology
Content Type	Text
Resource Type	Article
Subject	Radiology, Nuclear Medicine and Imaging Computer Science Applications

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