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Readmission and Death After Initial Hospital Discharge Among Patients With COVID-19 in a Large Multihospital System

Educational Objective
To identify the key insights or developments described in this article
1 Credit CME

Although more patients are surviving severe coronavirus disease 2019 (COVID-19), there are limited data on outcomes after initial hospitalization. We therefore measured the rate of readmission, reasons for readmission, and rate of death after hospital discharge among patients with COVID-19 in the nationwide Veterans Affairs (VA) health care system.

We identified index hospitalizations for COVID-19 among veterans at 132 VA hospitals (admitted March 1–June 1, 2020; discharged March 1–July 1, 2020) in the VA’s Corporate Data Warehouse.1 Definitions included definite hospitalizations for COVID-19, in which patients were diagnosed during hospitalization, and probable hospitalizations, in which patients were diagnosed during the 14 days preceding or 7 days following hospitalization.2,3

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Article Information

Corresponding Author: John P. Donnelly, PhD, Department of Learning Health Sciences, University of Michigan, 2800 Plymouth Rd, NCRC Bldg 14, #G100, G014-130, Ann Arbor, MI 48109 (jpdonn@med.umich.edu).

Accepted for Publication: October 13, 2020.

Published Online: December 14, 2020. doi:10.1001/jama.2020.21465

Correction: This article was corrected online on December 30, 2020, to adjust the numbers and percentages of women as reported in the Table.

Author Contributions: Drs Donnelly and Prescott had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Donnelly, Prescott.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Donnelly.

Critical revision of the manuscript for important intellectual content: Wang, Iwashyna, Prescott.

Statistical analysis: Donnelly, Wang.

Obtained funding: Prescott.

Administrative, technical, or material support: Prescott.

Supervision: Prescott.

Conflict of Interest Disclosures: Dr Donnelly reported receiving grants from the National Heart, Lung, and Blood Institute (NHLBI) and personal fees from the Annals of Emergency Medicine. Dr Iwashyna reported receiving grants from VA Health Services Research and Development. Dr Prescott reported receiving grants from the Agency for Healthcare Research and Quality and the Department of Veterans Affairs. No other disclosures were reported.

Funding/Support: Drs Donnelly and Iwashyna are supported by grant K12-HL138039 from the NHLBI. Dr Prescott is supported by grant R01-HS026725 from Agency for Healthcare Research and Quality. This work was supported by grant IIR 17-045 from the VA Health Services Research and Development (Dr Iwashyna). This material is the result of work supported with resources and use of facilities at the Ann Arbor VA Medical Center.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: This article does not represent the views of the Department of Veterans Affairs or the US government.

References
1.
Vincent  BM , Wiitala  WL , Burns  JA , Iwashyna  TJ , Prescott  HC .  Using Veterans Affairs corporate data warehouse to identify 30-day hospital readmissions.   Health Serv Outcomes Res Methodol. 2018;18:143-154. doi:10.1007/s10742-018-0178-3Google ScholarCrossref
2.
COVID-19 resources. Health Services Research & Development: US Department of Veterans Affairs. Accessed October 7, 2020. https://www.hsrd.research.va.gov/covid19.cfm
3.
Scehnet  J , DuVall  S . VA COVID-19 shared data resource update: VA informatics and computing infrastructure. US Department of Veterans Affairs. Accessed August 17, 2020. https://www.hsrd.research.va.gov/for_researchers/cyber_seminars/archives/3834-notes.pdf
4.
Clinical Classifications Software Refined (CCSR) for ICD-10-CM Diagnoses. Healthcare Cost and Utilization Project (HCUP). Agency for Healthcare Research and Quality. Published 2020. Accessed August 17, 2020. https://www.hcup-us.ahrq.gov/toolssoftware/ccsr/ccs_refined.jsp
5.
Wang  XQ , Vincent  BM , Wiitala  WL ,  et al.  Veterans Affairs patient database (VAPD 2014-2017): building nationwide granular data for clinical discovery.   BMC Med Res Methodol. 2019;19(1):94. doi:10.1186/s12874-019-0740-x PubMedGoogle ScholarCrossref
6.
Blackwell  M , Iacus  S , King  G , Porro  G .  Cem: coarsened exact matching in Stata.   Stata J. 2009;9(4):524-546. doi:10.1177/1536867X0900900402 Google ScholarCrossref
AMA CME Accreditation Information

Credit Designation Statement: The American Medical Association designates this Journal-based CME activity activity for a maximum of 1.00  AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Successful completion of this CME activity, which includes participation in the evaluation component, enables the participant to earn up to:

  • 1.00 Medical Knowledge MOC points in the American Board of Internal Medicine's (ABIM) Maintenance of Certification (MOC) program;;
  • 1.00 Self-Assessment points in the American Board of Otolaryngology – Head and Neck Surgery’s (ABOHNS) Continuing Certification program;
  • 1.00 MOC points in the American Board of Pediatrics’ (ABP) Maintenance of Certification (MOC) program;
  • 1.00 Lifelong Learning points in the American Board of Pathology’s (ABPath) Continuing Certification program; and
  • 1.00 credit toward the CME [and Self-Assessment requirements] of the American Board of Surgery’s Continuous Certification program

It is the CME activity provider's responsibility to submit participant completion information to ACCME for the purpose of granting MOC credit.

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