Sequence Analysis of Long-Term Readmissions among High-Impact Users of Cerebrovascular Patients
Joint Authors
Rao, Ahsan
Aylin, Paul
Bottle, Alex
Darzi, Ara
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-05-16
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Objective.
Understanding the chronological order of the causes of readmissions may help us assess any repeated chain of events among high-impact users, those with high readmission rate.
We aim to perform sequence analysis of administrative data to identify distinct sequences of emergency readmissions among the high-impact users.
Methods.
A retrospective cohort of all cerebrovascular patients identified through national administrative data and followed for 4 years.
Results.
Common discriminating subsequences in chronic high-impact users (n=2863) of ischaemic stroke (n=34208) were “urological conditions-chest infection,” “chest infection-urological conditions,” “injury-urological conditions,” “chest infection-ambulatory condition,” and “ambulatory condition-chest infection” (p<0.01).
Among TIA patients (n=20549), common discriminating (p<0.01) subsequences among chronic high-impact users were “injury-urological conditions,” “urological conditions-chest infection,” “urological conditions-injury,” “ambulatory condition-urological conditions,” and “ambulatory condition-chest infection.” Among the chronic high-impact group of intracranial haemorrhage (n=2605) common discriminating subsequences (p<0.01) were “dementia-injury,” “chest infection-dementia,” “dementia-dementia-injury,” “dementia-urine infection,” and “injury-urine infection.” Conclusion.
Although common causes of readmission are the same in different subgroups, the high-impact users had a higher proportion of patients with distinct common sequences of multiple readmissions as identified by the sequence analysis.
Most of these causes are potentially preventable and can be avoided in the community.
American Psychological Association (APA)
Rao, Ahsan& Bottle, Alex& Darzi, Ara& Aylin, Paul. 2017. Sequence Analysis of Long-Term Readmissions among High-Impact Users of Cerebrovascular Patients. Stroke Research and Treatment،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1203541
Modern Language Association (MLA)
Rao, Ahsan…[et al.]. Sequence Analysis of Long-Term Readmissions among High-Impact Users of Cerebrovascular Patients. Stroke Research and Treatment No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1203541
American Medical Association (AMA)
Rao, Ahsan& Bottle, Alex& Darzi, Ara& Aylin, Paul. Sequence Analysis of Long-Term Readmissions among High-Impact Users of Cerebrovascular Patients. Stroke Research and Treatment. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1203541
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1203541