Literature DB >> 33104780

Thirty-day readmission rate of COVID-19 patients discharged from a tertiary care university hospital in Turkey: an observational, single-center study.

Oğuz Abdullah UyaroĞlu1, Nursel Çalik BaŞaran1, Lale ÖziŞik1, Gülçİn Tellİ Dİzman2, İmdat EroĞlu3, Taha Koray Şahİn3, Zahİt TaŞ2, Ahmet Çağkan İnkaya2, Mıne Durusu TanriÖver1, Gökhan Metan2, Gülay Saİn GÜven1, Serhat Ünal2.   

Abstract

BACKGROUND: The 30-day readmission rate is an important indicator of patient safety and hospital's quality performance. In this study, we aimed to find out the 30-day readmission rate of mild and moderate severity coronavirus disease of 2019 (COVID-19) patients discharged from a tertiary care university hospital and to demonstrate the possible factors associated with readmission.
METHODS: This is an observational, single-center study. Epidemiological and clinical data of patients who were hospitalized with a diagnosis of COVID-19 were retrieved from a research database where patient information was recorded prospectively. Readmission data were sought from the hospital information management system and the National Health Information System to detect if the patients were readmitted to any hospital within 30 days of discharge. Adult patients (≥18 years old) hospitalized in COVID-19 wards with a diagnosis of mild or moderate COVID-19 between 20 March 2020 (when the first case was admitted to our hospital) and 26 April 2020 were included.
RESULTS: From 26 March to 1 May, there were 154 mild or moderate severity (non-critical) COVID-19 patients discharged from COVID-19 wards, of which 11 (7.1%) were readmitted. The median time of readmission was 8.1 days (interquartile range [IQR] = 5.2). Two patients (18.1%) were categorized to have mild disease and the remaining 9 (81.9%) as moderate disease. Two patients who were over 65 years of age and had metastatic cancers and hypertension developed sepsis and died in the hospital during the readmission episode. Malignancy (18.7% vs. 2.1%, P = 0.04) and hypertension (45.5% vs. 14%, P = 0.02) were more common in those who were readmitted.
CONCLUSIONS: This is one of the first studies to report on 30-day readmission rate of COVID-19 in the literature. More comprehensive studies are needed to reveal the causes and predictors of COVID-19 readmissions.
© The Author(s) 2020. Published by Oxford University Press on behalf of International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  30-day readmission rate; COVID-19; readmission

Year:  2021        PMID: 33104780      PMCID: PMC7665548          DOI: 10.1093/intqhc/mzaa144

Source DB:  PubMed          Journal:  Int J Qual Health Care        ISSN: 1353-4505            Impact factor:   2.038


  14 in total

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Journal:  Kidney360       Date:  2022-04-15

2.  Current Trends in Readmission Prediction: An Overview of Approaches.

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Journal:  Arab J Sci Eng       Date:  2021-08-16       Impact factor: 2.807

3.  Epidemiologic characteristics of cases with reinfection, recurrence, and hospital readmission due to COVID-19: A systematic review and meta-analysis.

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4.  COVID-19-Related Circumstances for Hospital Readmissions: A Case Series From 2 New York City Hospitals.

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Journal:  J Patient Saf       Date:  2021-06-01       Impact factor: 2.243

5.  Emergency department visits and readmissions after COVID-19 hospitalization: a cross-sectional analysis.

Authors:  Mary Gwin; Massoud Saleki; Hannah Lampert; Nicholas Meo; Maralyssa Bann
Journal:  Intern Emerg Med       Date:  2021-02-03       Impact factor: 3.397

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Journal:  Int J Biol Sci       Date:  2021-02-18       Impact factor: 6.580

7.  Hospital readmissions and post-discharge all-cause mortality in COVID-19 recovered patients; A systematic review and meta-analysis.

Authors:  Zhian Salah Ramzi
Journal:  Am J Emerg Med       Date:  2021-11-06       Impact factor: 4.093

8.  Factors associated with hospital readmissions among patients with COVID-19: A single-center experience.

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Journal:  J Med Virol       Date:  2021-06-06       Impact factor: 20.693

9.  An explanatory machine learning framework for studying pandemics: The case of COVID-19 emergency department readmissions.

Authors:  Behrooz Davazdahemami; Hamed M Zolbanin; Dursun Delen
Journal:  Decis Support Syst       Date:  2022-01-18       Impact factor: 6.969

10.  Remote Hospital Care for Recovering COVID-19 Patients Using Telemedicine: A Randomised Controlled Trial.

Authors:  Harriët M R van Goor; Martine J M Breteler; Kim van Loon; Titus A P de Hond; Johannes B Reitsma; Dorien L M Zwart; Cornelis J Kalkman; Karin A H Kaasjager
Journal:  J Clin Med       Date:  2021-12-17       Impact factor: 4.241

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