Development and Evaluation of Risk Models to Predict Readmission or Death Following Discharge from an Adult General Systems Intensive Care Unit

Simple item page
dc.contributor.advisorStelfox, Henry Thomas
dc.contributor.authorBoyd, Jamie
dc.contributor.committeememberJames, Matthew T.
dc.contributor.committeememberZuege, Danny J.
dc.date2018-11
dc.date.accessioned2018-07-11T21:19:13Z
dc.date.available2018-07-11T21:19:13Z
dc.date.issued2018-07-06
dc.description.abstractTransitions of care from intensive care unit (ICU) to ward are high-risk periods of healthcare delivery associated with ICU readmission and post-ICU mortality. Evidence-based processes for transitions are crucial for improving outcomes. Validated prediction models that include consistently associated risk factors for ICU readmission or post-ICU mortality may help to improve these practices. This mixed-methods thesis was comprised of three distinct phases: 1) systematic review and meta-analysis; 2) development of prediction models for ICU Readmission and Post-ICU Mortality using two approaches (literature-derived coefficients, data-derived coefficients [Derivation Cohort]), 3) validation of the models in an external Validation Cohort. The models for ICU Readmission showed limited discriminative ability whereas the Post-ICU Mortality models were stronger. Developing prediction models using pooled measures of association is a feasible approach, producing similar results to more the traditional data-derived method. Additional investigation to further validate the findings is required.en_US
dc.identifier.citationBoyd, J. M. (2018) Development and Evaluation of Risk Models to Predict Readmission or Death Following Discharge from an Adult General Systems Intensive Care Unit (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/32355en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/32355
dc.identifier.urihttp://hdl.handle.net/1880/107133
dc.language.isoeng
dc.publisher.facultyCumming School of Medicine
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectcritical care
dc.subjectintensive care unit
dc.subjecttransitions of patient care
dc.subjectprediction models
dc.subjectreadmission
dc.subjectin-hospital mortality
dc.subjectmeta-analysis
dc.subjectlogistic regression
dc.subject.classificationHealth Care Managementen_US
dc.titleDevelopment and Evaluation of Risk Models to Predict Readmission or Death Following Discharge from an Adult General Systems Intensive Care Unit
dc.typemaster thesis
thesis.degree.disciplineCommunity Health Sciences
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.item.requestcopytrue
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
ucalgary_2018_boyd_jamie.pdf
Size:
1.42 MB
Format:
Adobe Portable Document Format
Description:
Thesis Document
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.74 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Open Theses and Dissertations