Predicting all-cause unplanned readmission within 30 days of discharge using electronic medical record data: A multi-centre study

10.1111/ijcp.14306

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Main Authors: Sharmin, Sifat, Meij, Johannes J, Zajac, Jeffrey D, Moodie, Alan Rob, Maier, Andrea B
Other Authors: MEDICINE
Format: Article
Language:English
Published: WILEY 2022
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Online Access:https://scholarbank.nus.edu.sg/handle/10635/234879
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Institution: National University of Singapore
Language: English
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spelling sg-nus-scholar.10635-2348792024-04-17T09:36:30Z Predicting all-cause unplanned readmission within 30 days of discharge using electronic medical record data: A multi-centre study Sharmin, Sifat Meij, Johannes J Zajac, Jeffrey D Moodie, Alan Rob Maier, Andrea B MEDICINE Science & Technology Life Sciences & Biomedicine Medicine, General & Internal Pharmacology & Pharmacy General & Internal Medicine HOSPITAL READMISSION RISK-FACTORS DEATH VALIDATION DISEASE MODELS 10.1111/ijcp.14306 INTERNATIONAL JOURNAL OF CLINICAL PRACTICE 75 8 2022-11-29T00:55:25Z 2022-11-29T00:55:25Z 2021-05-17 2022-11-28T09:10:03Z Article Sharmin, Sifat, Meij, Johannes J, Zajac, Jeffrey D, Moodie, Alan Rob, Maier, Andrea B (2021-05-17). Predicting all-cause unplanned readmission within 30 days of discharge using electronic medical record data: A multi-centre study. INTERNATIONAL JOURNAL OF CLINICAL PRACTICE 75 (8). ScholarBank@NUS Repository. https://doi.org/10.1111/ijcp.14306 1368-5031 1742-1241 https://scholarbank.nus.edu.sg/handle/10635/234879 en WILEY Elements
institution National University of Singapore
building NUS Library
continent Asia
country Singapore
Singapore
content_provider NUS Library
collection ScholarBank@NUS
language English
topic Science & Technology
Life Sciences & Biomedicine
Medicine, General & Internal
Pharmacology & Pharmacy
General & Internal Medicine
HOSPITAL READMISSION
RISK-FACTORS
DEATH
VALIDATION
DISEASE
MODELS
spellingShingle Science & Technology
Life Sciences & Biomedicine
Medicine, General & Internal
Pharmacology & Pharmacy
General & Internal Medicine
HOSPITAL READMISSION
RISK-FACTORS
DEATH
VALIDATION
DISEASE
MODELS
Sharmin, Sifat
Meij, Johannes J
Zajac, Jeffrey D
Moodie, Alan Rob
Maier, Andrea B
Predicting all-cause unplanned readmission within 30 days of discharge using electronic medical record data: A multi-centre study
description 10.1111/ijcp.14306
author2 MEDICINE
author_facet MEDICINE
Sharmin, Sifat
Meij, Johannes J
Zajac, Jeffrey D
Moodie, Alan Rob
Maier, Andrea B
format Article
author Sharmin, Sifat
Meij, Johannes J
Zajac, Jeffrey D
Moodie, Alan Rob
Maier, Andrea B
author_sort Sharmin, Sifat
title Predicting all-cause unplanned readmission within 30 days of discharge using electronic medical record data: A multi-centre study
title_short Predicting all-cause unplanned readmission within 30 days of discharge using electronic medical record data: A multi-centre study
title_full Predicting all-cause unplanned readmission within 30 days of discharge using electronic medical record data: A multi-centre study
title_fullStr Predicting all-cause unplanned readmission within 30 days of discharge using electronic medical record data: A multi-centre study
title_full_unstemmed Predicting all-cause unplanned readmission within 30 days of discharge using electronic medical record data: A multi-centre study
title_sort predicting all-cause unplanned readmission within 30 days of discharge using electronic medical record data: a multi-centre study
publisher WILEY
publishDate 2022
url https://scholarbank.nus.edu.sg/handle/10635/234879
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