rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Risk prediction models for hospital readmission
    sub title: a systematic review
  name:
    name part: Kansagara, Devan
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: United States
    name part: Department of Veterans Affairs.
    name part: Health Services Research and Development Service,
    role:
      role term: issuing body.
  name:
    name part: Portland VA Medical Center
    name part: Evidence-based Synthesis Program Center.
  name:
    name part: Evidence-based Synthesis Program (U.S.)
  type of resource: text
  genre: bibliography
  genre: Technical reports.
  genre: Statistics.
  origin info:
    place:
      place term: dcu
    date issued: 2011
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (ii, 33 pages) : illustrations
  abstract: An increasing body of literature attempts to describe and validate hospital readmission risk prediction tools. Interest in such models has grown for two reasons. First, transitional care interventions may reduce readmissions among chronically ill adults. Readmission risk assessment could be used to help target the delivery of these resource-intensive interventions to the patients at greatest risk. Ideally, models designed for this purpose would provide clinically relevant stratification of readmission risk and give information early enough during the hospitalization to trigger a transitional care intervention, many of which involve discharge planning and begin well before hospital discharge. Second, there is interest in using readmission rates as a quality metric. Recently, the Centers for Medicare & Medicaid Services (CMS) began using readmission rate as a publicly reported metric, with plans to lower reimbursement to hospitals with excess risk-standardized readmission rates. Valid risk adjustment methods are required for calculation of risk-standardized readmission rates which could, in turn, be used for hospital comparison, public reporting, and reimbursement determinations. Models designed for these purposes should have good predictive ability; be deployable in large populations; use reliable data that can be easily obtained; and use variables that are clinically related to, and validated in, the populations in which use is intended. This systematic review was performed to synthesize the available literature on validated readmission risk prediction models, describe their performance, and assess their suitability for clinical or administrative use.
  note: Devan Kansagara [and six others].
  note: "Evidence-based synthesis program."
  note: "October 2011."
  note: GPO Cataloging Record Distribution Program (CRDP).
  note: Includes bibliographical references (pages 12-16).
  note: Prepared for: Department of Veterans Affairs, Veterans Health Administration, Health Services Research & Development Service, Washington, DC 20420. Prepared by: Evidence-based Synthesis Program (ESP) Center, Portland VA Medical Center, Portland, OR, Devan Kansagara, M.D., M.C.R., Director
  note: VA-ESP 05-225
  subject:
    geographic code: n-us---
  subject:
    topic: Hospitals
    topic: Admission and discharge
    geographic: United States
  subject:
    topic: Risk assessment
    geographic: United States
  subject:
    topic: Mathematical models
  subject:
    topic: Evidence-based medicine
  subject:
    topic: Hospitals
    topic: Admission and discharge
  subject:
    topic: Risk assessment
  subject:
    geographic: United States
  classification: VA 1.107/3:R 49
  identifier: https://purl.fdlp.gov/GPO/gpo155319
  record info:
    record content source: NLM
    record creation date: 120403
    record change date: 20220803200709.3
    record identifier: in00004445329
    language of cataloging:
      language term: eng