byOlive
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Health Economics · Analytics · Strategy
Health Services Research · Calgary, AB

Bold assumptions.
Verified.

Surfacing the assumptions that determine conclusions — before the data does it for you.

I work where clinical reality meets statistical inference — and ask what we're actually measuring.

Most research buries its assumptions. I surface them. The difference between a model that informs and one that misleads is rarely the data — it's what was assumed before the analysis began.

My work sits at the intersection of health economics, longitudinal methods, and the uncomfortable question of whether the thing being measured is the thing that matters.

2025 Presenter, Johns Hopkins Frailty Conference — Frailty as mediator between social determinants and cardiac outcomes
2024– MSc Health Economics, University of Calgary
2023 Clinical Research Coordinator — PCOS infrastructure redesign, recruitment surpassed objectives
Prior Government of Alberta — applied analytics and policy research
Selected
work.
01
Intrinsic Capacity vs. Frailty: Why We're Measuring the Wrong Thing
Healthcare systems spend billions quantifying frailty — a construct built on deficits and decline. Meanwhile, the WHO's intrinsic capacity framework, which measures what older adults can do rather than what they've lost, sits largely unused. This piece argues the choice of measure is not methodological preference — it is a value judgment with real resource allocation consequences. I demonstrate divergent model behaviour using longitudinal data from the Canadian Longitudinal Study on Aging.
02
The Solar Panel Decision: When ROI Is the Wrong Question
A $120k capital decision on a grain and cattle farm with a 25-year horizon. Traditional payback analysis obscured what mattered: downside protection in an uncertain energy landscape, optionality, and operational resilience. A framework built on risk quantification rather than return speculation led to a confident decision. This case study is about what happens when the standard assumption — that ROI is the right lens — is the first thing you surface and discard.
Self-published case study · 2024
Tell me what you're trying to decide.
Precision in questions leads to precision in answers. If you have a research problem, a data question, or a decision with real stakes — I'm interested.
byo@byolive.ca →