Health economics & outcomes research
Assumptions Aside is an independent health economics consultancy. We build the cost-effectiveness models, HTA strategies and real-world evidence that manufacturers, public payers and state health programs use to decide what is worth funding.
Assumption test
01 / 04
We hear
Est. 2021
Boston, MA
Biopharma · Public health · AI
HTA · RWE · Policy
Built to the standards of
Built to the standards of
Why it matters
167
schools in a CDC-funded cost-effectiveness evaluation
~20
HTA bodies benchmarked in a single evidence synthesis
14
data sources integrated into one state evaluation
6
regulators advised on Phase III evidence
Expertise
Selected engagements
How we work
The name is the method. Each engagement follows the same discipline, whatever its scale.
Step 01
Who decides, from whose perspective, against which comparator, at what threshold? We settle the PICO, the perspective and the decision rule before a single cell of the model is built.
Step 02
Every input and structural choice is written down and traced to a source. Evidence grades, exclusion rules and verification logs make the work auditable by someone who was not in the room.
Step 03
Cost-effectiveness, cost-utility and budget-impact models. Real-world evidence from claims, surveys and clinical text. Systematic and targeted reviews. Methods matched to the question, not the other way round.
Step 04
Probabilistic and deterministic sensitivity analysis shows which assumptions actually move the answer. Then briefings, dashboards and workshops put it in front of the people who decide.
Try it: probabilistic sensitivity analysis
A model is run hundreds of times, drawing every uncertain input from its plausible range. Each dot is one run. Drag the willingness-to-pay threshold and watch the answer change. This is the trade-off, made visible.
$100,000
63%
of 360 simulated runs are cost-effective at $100K per QALY.
Cost-effectiveness acceptability curve
Probability cost-effective, by threshold
| Threshold per QALY | Probability cost-effective |
|---|---|
| $0 | 1% |
| $25,000 | 3% |
| $50,000 | 12% |
| $75,000 | 39% |
| $100,000 | 63% |
| $125,000 | 74% |
| $150,000 | 80% |
| $175,000 | 84% |
| $200,000 | 86% |
Who we work with
Evidence for the manufacturers who make the case, and for the public programs that have to weigh it.
01
HTA strategy, value evidence and pricing-policy risk, from Phase III design to launch.
ExampleA Phase III program built for payers as well as regulators02
Program evaluation, cost-effectiveness and strategic planning for programs that must show their value.
ExampleWhat is a school inhaler worth?03
Health-economic methodology and evidence standards for AI products in market access and real-world evidence.
ExampleAn AI platform that reads HTA precedentFounder
Founder & Principal Health Economist
Anmol Kanotra is a health economist who builds, tests and defends the decision-analytic models behind coverage, pricing and public-funding decisions. She founded Assumptions Aside in 2021.
Earlier, she built cost-utility, budget-impact and policy models at FTI Consulting’s Center for Healthcare Economics & Policy and in value, access and outcomes research at Syneos Health in London. She trained in health economics at the London School of Economics.
Insights & publications
Explainer · Real-world evidence
Most of what we know about a patient is buried in free text. How natural language processing gets it out, and why health economists should care.
4 min readWhite paper · In preparation
Revised to CHEERS 2022 reporting standards
Peer-reviewed article · 2023
ClinicoEconomics and Outcomes Research 2023;15:753–764
Read the paperWork with us
Tell us about the launch, the coverage question or the program that needs to show its value. We will tell you what evidence it needs, and what it can do without.