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Optimize Pre-Discharge Order Process

Om Optimize Pre-Discharge Order Process

The initiation of early discharge planning may improve discharge times and an expedited release on the day of discharge. At the project site there was no systematic process to decrease discharge time for medical surgical patients, so an evidence-based solution was sought. The purpose of this quantitative quasi-experimental quality improvement project was to determine if or to what degree the translation of Mallipudi et al.'s research on the implementation of pre-discharge orders on the day before discharge impacted discharge times when compared to current practice among adult patients in an inpatient medical-surgical unit in urban Texas over four-weeks. Sister Callista Roy's adaptation theory and Kurt Lewin's change management theory provided the theoretical underpinnings of the project. The total sample size was 135; with n = 97 in the comparative group and n = 38 in the implementation group. Data were extracted from the facility's electronic health record.

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  • Språk:
  • Engelsk
  • ISBN:
  • 9782850838774
  • Bindende:
  • Paperback
  • Sider:
  • 88
  • Utgitt:
  • 10 september 2023
  • Dimensjoner:
  • 152x6x229 mm.
  • Vekt:
  • 142 g.
  Gratis frakt
Leveringstid: 2-4 uker
Forventet levering: 26 oktober 2024

Beskrivelse av Optimize Pre-Discharge Order Process

The initiation of early discharge planning may improve discharge times and an expedited release on the day of discharge. At the project site there was no systematic process to decrease discharge time for medical surgical patients, so an evidence-based solution was sought. The purpose of this quantitative quasi-experimental quality improvement project was to determine if or to what degree the translation of Mallipudi et al.'s research on the implementation of pre-discharge orders on the day before discharge impacted discharge times when compared to current practice among adult patients in an inpatient medical-surgical unit in urban Texas over four-weeks. Sister Callista Roy's adaptation theory and Kurt Lewin's change management theory provided the theoretical underpinnings of the project. The total sample size was 135; with n = 97 in the comparative group and n = 38 in the implementation group. Data were extracted from the facility's electronic health record.

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