Tezeta, ትዝታ, means memory or nostalgia in Amharic, but it carries something closer to longing. It is also a mode in Ethiopian music, with a whole tradition of songs built around that feeling.
This version is by Mulatu Astatke, a pioneer of Ethio-jazz. I chose it for a simpler reason: Ethiopia is my mother’s country, and this feels like a small piece of that side of my family playing quietly underneath my work.
I build health economic models that turn clinical evidence into decisions people can explain.
Aida van Riel is a health economist based in Rotterdam, the Netherlands. She holds an MSc in Health Economics from Erasmus University Rotterdam, graduated cum laude, and builds cost-effectiveness, budget-impact and pricing models that turn clinical evidence into decisions people can explain.
Health economics lives between what we want to provide and what we can provide. Every model simplifies, every threshold reflects a choice, and every decision affects real people.I wanted to understand those choices well enough to question them. So I became a health economist.
A model can produce an answer. The interesting part is understanding what had to be true for that answer to hold.
A treatment can improve health and still not be the best use of a fixed budget.
Cost-effectiveness is not only about what a treatment adds. It is also about the health that could have been produced elsewhere with the same resources. That opportunity cost is what turns an ICER from a calculation into a decision.
The base-case result is only the beginning.
A model can look precise while depending heavily on a handful of uncertain inputs or structural choices. I care less about whether the ICER is €31,842 than whether the conclusion survives plausible changes to the assumptions underneath it.
Trial follow-up ends. The decision horizon usually does not.
Long-term outcomes often have to be extrapolated beyond the observed data. The choice of survival distribution, treatment-effect assumption, or time horizon can matter more than another decimal place in the observed estimate.
They sound similar. They answer different questions.
A medicine can be cost-effective at a given price and still create an unaffordable budget impact at scale. It can also have a high list price without that price telling us much about its production cost. Value, price, and affordability belong in the same conversation, but they are not interchangeable.
Value asks whether the benefits a medicine produces justify the resources used to provide it. In cost-effectiveness analysis, that often means comparing additional costs with additional QALYs and a reference threshold.
Price is the amount charged for the medicine. It may be a list price or a confidential net price, and it is not the same thing as either the medicine’s production cost or its value.
Affordability asks what happens when the price is multiplied across everyone who may receive the treatment. Even a cost-effective medicine can create a budget impact that is difficult to absorb at scale.
A new therapy entered the Dutch market at €13,695 per cycle. I built a partitioned survival model, a five-year budget impact model, and a cost-based access price using the ASCERTAIN framework, to test whether that price could be justified.
A 20-year cohort Markov model built from trial data, with survival extrapolation and probabilistic uncertainty analysis.
A four-part access strategy for a medicine with strong public-health value but weak commercial incentives.
A first-in-class gene therapy faced $73M in development costs and a $30–50M funding gap. I built a financing strategy around sequencing partnership capital before an equity raise.
The 2008 crisis unexpectedly sent migrant workers home. I used that shock to study what changed for the spouses they returned to.
Coverage expanded rapidly. Financial protection did not. I looked at how targeting, benefit design and implementation pulled the two apart.
A new breast cancer medicine arrived in the Netherlands asking €13,695 for every 28 day cycle. My project asks what happens when the price a health system can justify and the price a manufacturer can justify are nowhere near each other.
before we start: the same medicine has three defensible prices, built from completely different logic
| Price | Price per cycle | ICER, cost per QALY gained |
|---|---|---|
| The asking price | €13,695 | €1,109,246 |
| The access price | €6,800 | €570,549 |
| The value-based price | €516 | €79,589 |
Holding everything else in the model constant, the treatment reaches the €80,000 per QALY reference threshold at approximately €516 per cycle. That is about 96 percent below the original asking price of €13,695.
I then used the ASCERTAIN framework to estimate a price based on research, manufacturing and supply costs, plus an allowable return. This produced a very different figure of approximately €6,800 per cycle.
€6,800 is the cost based access price from Step 02. It is estimated from research, manufacturing and supply costs, plus an allowable return.
But at €6,800 per cycle, the treatment is still above the cost effectiveness threshold. To reach that threshold, the price would need to be around €516 per cycle.
So the two approaches give very different answers:
That gap is the key finding.
A simple discount may not be enough to close a gap this large. A managed entry agreement could instead bring price, spending and uncertainty into the same negotiation. That might mean a confidential net price, a limit on total spending, or payments linked to how the treatment performs.
The model does not decide which agreement is right. It shows why a different kind of agreement may be needed.
I can show you what I built. They can tell you how I worked.
“Her independence in conducting the research was highly positive, as was her attention to detail.”
No fundamental corrections to her research approach were necessary, and her attention to detail during data collection was highly positive.
She also applied a newly developed pricing model for which there is so far no reference in the literature. Where assumptions were needed, she made them explicit and justified them well.
I am more than happy to recommend her for positions in market access and health economics and outcomes research.
“Very impressive across the board.”
Well written, with a very impressive methodology and an excellent description of the results.
The methodology combined a cost effectiveness analysis, sensitivity analyses, an access based pricing model and a budget impact analysis. Many do just one or two of these, which makes her work all the more impressive.
It was clear that she was really on top of the literature, and took ownership of every part of it.
Why does care reach some people and not others? I grew up seeing that question from two very different sides.
I grew up knowing that healthcare can exist and still be out of reach, because of distance, cost, capacity, or what a family has to give up to get it.
Those trade-offs were real to people I knew long before I had words like access, affordability or financial protection for them.
That is where the question came from.
In the Netherlands I encountered a health system that makes many of those choices unusually visible: evidence requirements, cost-effectiveness, severity, reimbursement and the limits of a finite budget.
Health economics gave me a way to take questions I already cared about and make them testable: to model the trade-offs, challenge the assumptions and ask whether resources could be used better.
That is where the question became a method.
A running list of the questions, methods and shifts in HEOR I want to understand before they become standard practice.
Rare disease forces an evidence problem: tiny populations, incomplete data and trials that may never look conventional. I was interested in where AI can genuinely strengthen real-world evidence, and where regulators will still need to see the reasoning behind the model.
A useful horizon scan of where HEOR is heading: changing evidence standards, new methods and the questions likely to shape reimbursement over the next few years. I keep this one as a map of what I should be learning next.
Senior HEOR practitioners on the skills they wish they had built earlier, and where technical competence stops being enough. I liked this one because it was aimed almost exactly at the stage I am in now.
The investor side of evidence generation: what has to be demonstrated before capital follows, and how reimbursement expectations can shape which technologies are investable long before they ever reach a patient.
Give me a mountain, decent weather and a long trail and I’m happy. A good view at the end definitely helps.
I just really like being outside. Parks, forests, beaches, long walks. I’m happiest when there’s something green around me.
I’m the person who gets distracted by every animal I see. I love all of them, but dogs are definitely my biggest weakness.
My taste is genuinely all over the place. I’ve been told I have the music taste of an old woman, and when I find a song I love, old or new, I’ll play it on repeat for days.
Put me in warm water with a mask and I can disappear for hours. I somehow never get bored of seeing what’s underneath.
Still pretty new to this one. I got certified off the Perhentian Islands and immediately started thinking about where I could dive next.
I started by editing the things I film while travelling to share with family and friends. Now I also make LinkedIn videos, product reviews and creator content for YouTube.
“I didn’t explain a lot, and she understood it pretty accurately. That’s pretty cool to see.”
I like problems that do not come with an obvious answer, and I am always interested in learning something new. My background is in health economics, but I am open to interesting work well beyond it. A thoughtful project, an ambitious company, a problem that needs figuring out, or simply a team doing something I have never done before can all get my attention.I learn quickly, work independently and genuinely enjoy getting into unfamiliar territory. If you are building something interesting and think I could add something to it, write to me.
