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: Evaluating the impact of accreditation using interrupted time series segmented regression analysis
    sub title: a reflective analysis
  name:
    name part: Devkaran, Subashnie
    role:
      role term: creator
    role:
      role term: author.
  type of resource: text
  genre: bibliography
  genre: Case studies.
  origin info:
    place:
      place term: enk
    date issued: 2020
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource : illustrations.
  abstract: Due to rising health care costs and resource constraints, this is an unprecedented time for health care leaders in terms of policy, information technology, and organizational change. The impact of health care policy interventions including accreditation has been researched adopting a variety of methodologies and research designs. There is a lack of rigorous research including the methodological challenges of measuring outcomes and linking cause and effect to these complex, changing, long-term policy interventions in health care organizations. Most studies have used cross-sectional designs and/or comparative static analysis of data at two points in time. Due to the dynamic nature of accreditation, such methodologies can only identify statistical associations between variables but cannot alone establish causality. This case study provides a reflective account of the first empirical interrupted time series analysis of accreditation designed to examine the impact on hospital quality measures. Lessons learnt such as selection of appropriate measures and methodological considerations will be detailed in this case study.
  target audience: specialized
  note: Subashnie Devkaran.
  note: Includes bibliographical references and index.
  subject:
    topic: Medical policy
    genre: Case studies
  subject:
    topic: Regression analysis
    genre: Case studies
  subject:
    topic: Politique sanitaire
    genre: Études de cas
  subject:
    topic: Analyse de régression
    genre: Études de cas
  subject:
    topic: Medical policy
  subject:
    topic: Regression analysis
  classification: RA393 .D48 2020
  classification: 362.1
  related item:
    title info:
      title: SAGE Research Methods Cases : Medicine and Health
  identifier: 9781529740196
  identifier: 1529740193
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: SGPBL
    record creation date: 200324
    record change date: 20240923170416.9
    record identifier: in00005495523
    language of cataloging:
      language term: eng