Outcomes Measurement
We develop and evaluate ways to measure what matters in ocular oncology: core outcome frameworks, patient-reported outcomes, referral quality, delays in care, and benchmarks for care.
O3R University of Calgary / University of Alberta
Ocular Oncology Outcomes Research
Measurement systems for real-world ocular oncology care.
We build outcome measures, evidence infrastructure, and clinical tools that make ocular oncology research usable in real care.
Research focus
What we work on
We organize our work around clinical problems that need better measurement, stronger evidence infrastructure, or tools that fit the workflow of care.
Clinical Decision Support and AI
We build and validate tools that can support earlier, more consistent clinical decisions, including AI-supported approaches to choroidal nevus assessment and follow-up.
Perioperative Systems
We translate perioperative evidence into practical protocols for ocular oncology surgery, including enhanced recovery and prehabilitation work designed for clinical implementation.
Data Infrastructure
We create the data linkages, registry, and QA infrastructure needed for trustworthy multi-project research and future multi-site collaboration.
Projects
Active work
Our projects include manuscripts, data infrastructure, and tools moving toward clinical use.
NeviSight
In progressAI-supported risk stratification for choroidal nevus assessment and follow-up, with emphasis on interpretable outputs, external validation, and integration into ocular oncology screening workflows.
No public link yet
AOBP Registry
In progressA REDCap registry for the Alberta Ocular Brachytherapy Program, currently undergoing validation to support reliable clinical data capture, outcomes research, and future multi-site ocular oncology studies.
No public link yet
PROM-UM
CompletedA patient-reported outcome measure for post-brachytherapy uveal melanoma care, focused on capturing patient experience in a clinically and psychometrically meaningful way.
Core Outcome Set
In developmentA shared minimum outcome framework for ocular oncology studies, intended to improve consistency in what researchers measure and make findings easier to compare across studies, clinics, and datasets.
No public link yet
Standardized Referral
In progressA program studying referral pathways for suspected uveal melanoma, including delayed referral rates, referral-letter quality, and patient perceptions of referral delays.
No public link yet
ERAS in Ocular Oncology
In progressDevelopment of a formal enhanced recovery protocol for ocular oncologic surgery, with attention to perioperative evidence, implementation, and clinical consensus.
No public link yet
Pre-RAS
In developmentDevelopment of a structured preparation and recovery-planning program for uveal melanoma patients undergoing ocular oncology care.
No public link yet
Textbook Outcomes
In developmentBenchmark development for defining high-quality ocular oncology surgical care using outcomes that are clinically meaningful, measurable, and comparable.
No public link yet
Team
Our team
O3R is a virtual-first research group connecting students, clinicians, and collaborators around practical ocular oncology problems.
TC
Principal Investigator
Trafford Crump, PhD
Trafford Crump is a health services researcher focused on measurement frameworks, real-world evidence, and practical clinical systems. His work bridges psychometrics, outcomes research, data infrastructure, and deployable tools for specialist care.
EW
Principal Investigator
Ezekiel Weis, MD, MPH
Ezekiel Weis is an ocular oncologist and Provincial Lead of the Alberta Ocular Biopathology Program. His research focuses on the diagnosis, surveillance, and management of intraocular tumors.
MJ
Manjot Jhinjar
Undergraduate Student
EL
Emily Laycock
Graduate Student
MP
Michelle Pham
Medical Student
ES
Emmet Soibelman
Undergraduate Student
Patient partnership Active initiative
Help shape uveal melanoma research
We are bringing together people across Canada who have been diagnosed with uveal melanoma to help identify patient priorities and guide meaningful research.
Join / collaborate
Join the Lab
We look for students and collaborators who are curious, reliable, and interested in turning research into usable clinical systems.
Trainees work on concrete projects: manuscripts, registry QA, outcome measurement, clinical AI validation, evidence synthesis, and implementation tools. The lab is virtual-first and project-driven, with a strong emphasis on clear writing, careful data work, and practical outputs that can be used by clinicians and research teams.
Send a short note describing your interests, your CV, and any relevant research, writing, data, clinical, or software experience.
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