Monash University
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Methods for outlier detection in clinical registries

thesis
posted on 2025-07-07, 00:52 authored by Jessy Marion Hansen
Clinical registries collect data about specific patient groups (including people with a certain disease or undergoing a certain surgical procedure) to monitor their outcomes and improve their quality of care. Registries will often compare patient care and outcomes (such as mortality) between hospitals (benchmarking) and then use statistical methods to find any hospitals that have significantly worse outcomes (outliers) that can be targeted for improvement. This thesis evaluates the accuracy of different benchmarking and outlier detection methods, and makes recommendations for the best clinical registry settings for improving outlier detection accuracy.<p></p>

History

Principal supervisor

Arul Earnest

Additional supervisor 1

Susannah Ahern

Additional supervisor 2

Ahmad Reza Pourghaderi

Year of Award

2025

Department, School or Centre

Public Health and Preventive Medicine

Course

Doctor of Philosophy

Degree Type

DOCTORATE

Faculty

Faculty of Medicine, Nursing and Health Sciences

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    Faculty of Medicine, Nursing and Health Sciences Theses

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