Sequence Analysis of Long-Term Readmissions among High-Impact Users of Cerebrovascular Patients
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 readmission...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017-01-01
|
| Series: | Stroke Research and Treatment |
| Online Access: | http://dx.doi.org/10.1155/2017/7062146 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832568503480090624 |
|---|---|
| author | Ahsan Rao Alex Bottle Ara Darzi Paul Aylin |
| author_facet | Ahsan Rao Alex Bottle Ara Darzi Paul Aylin |
| author_sort | Ahsan Rao |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-70092a28baf14c25820c7c118763e2e7 |
| institution | Kabale University |
| issn | 2090-8105 2042-0056 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Stroke Research and Treatment |
| spelling | doaj-art-70092a28baf14c25820c7c118763e2e72025-02-03T00:58:54ZengWileyStroke Research and Treatment2090-81052042-00562017-01-01201710.1155/2017/70621467062146Sequence Analysis of Long-Term Readmissions among High-Impact Users of Cerebrovascular PatientsAhsan Rao0Alex Bottle1Ara Darzi2Paul Aylin3Faculty of Medicine, Dr Foster Unit, Imperial College London, 3 Dorset Rise, London EC4Y 8EN, UKFaculty of Medicine, Dr Foster Unit, Imperial College London, 3 Dorset Rise, London EC4Y 8EN, UKFaculty of Medicine, Institute of Global Health, Imperial College London, St Mary’s Hospital, Praed Street, London W2 1NY, UKFaculty of Medicine, Dr Foster Unit, Imperial College London, 3 Dorset Rise, London EC4Y 8EN, UKObjective. 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.http://dx.doi.org/10.1155/2017/7062146 |
| spellingShingle | Ahsan Rao Alex Bottle Ara Darzi Paul Aylin Sequence Analysis of Long-Term Readmissions among High-Impact Users of Cerebrovascular Patients Stroke Research and Treatment |
| title | Sequence Analysis of Long-Term Readmissions among High-Impact Users of Cerebrovascular Patients |
| title_full | Sequence Analysis of Long-Term Readmissions among High-Impact Users of Cerebrovascular Patients |
| title_fullStr | Sequence Analysis of Long-Term Readmissions among High-Impact Users of Cerebrovascular Patients |
| title_full_unstemmed | Sequence Analysis of Long-Term Readmissions among High-Impact Users of Cerebrovascular Patients |
| title_short | Sequence Analysis of Long-Term Readmissions among High-Impact Users of Cerebrovascular Patients |
| title_sort | sequence analysis of long term readmissions among high impact users of cerebrovascular patients |
| url | http://dx.doi.org/10.1155/2017/7062146 |
| work_keys_str_mv | AT ahsanrao sequenceanalysisoflongtermreadmissionsamonghighimpactusersofcerebrovascularpatients AT alexbottle sequenceanalysisoflongtermreadmissionsamonghighimpactusersofcerebrovascularpatients AT aradarzi sequenceanalysisoflongtermreadmissionsamonghighimpactusersofcerebrovascularpatients AT paulaylin sequenceanalysisoflongtermreadmissionsamonghighimpactusersofcerebrovascularpatients |