Stelfox, Henry ThomasBoyd, Jamie2018-07-112018-07-112018-07-06Boyd, 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/32355http://hdl.handle.net/1880/107133Transitions 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.engUniversity 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.critical careintensive care unittransitions of patient careprediction modelsreadmissionin-hospital mortalitymeta-analysislogistic regressionHealth Care Managementmaster thesis10.11575/PRISM/32355