TL;DR
HEOR visuals are not clinical visuals with currency symbols
They carry economic uncertainty, and stripping that uncertainty out to make a slide look decisive is a misrepresentation, not a simplification.
The highest-risk deliverables are easy to over-clean
The cost-effectiveness plane, the cost-effectiveness acceptability curve (CEAC), the tornado diagram and the budget impact cash-flow view are precisely where a slide can look cleaner than the model actually supports.
We work from raw Excel model outputs
Not from a screenshot of a chart, so the visual is traceable back to the cell that produced it.
Overnight, NDA-secured, practitioner-reviewed
Overnight production, NDA-secured handling of unpublished models, and review by a life sciences practitioner rather than a design lead.
Your economic model is defensible. The slide built from it may not be. HEOR outputs carry uncertainty structures - confidence ellipses, acceptability curves, and probabilistic ranges - that a generalist designer will flatten into a clean single number because a clean single number looks better on a slide. That flattening is not a cosmetic decision. It changes what a payer, an HTA committee or a pricing lead believes about your evidence, and it is the failure mode we are built to prevent. For method context, see ISPOR good-practice resources and our related payer engagement deck guidance .
In every advisory board I have sat in, the moment a health economist loses the room is the moment the slide shows a single ICER figure with no visible uncertainty around it. The committee stops asking whether the technology is cost-effective and starts asking what has been left out. The visual job in HEOR is not to make the number look confident - it is to make the uncertainty legible enough that the reviewer trusts the analyst.
- Vaidehi Shukla, Principal, Life Sciences & Market Research, A1 Slides
Clinical data visualization answers a question about effect. HEOR visualization answers a question about resource allocation under constraint - and the audience has budget authority rather than clinical authority. NICE's economic evaluation manual is a useful benchmark for why assumptions, perspective, uncertainty and time horizon must stay visible in the visual.
Three structural differences follow from that.
A Kaplan-Meier curve has its own uncertainty, but the reader expects a curve. An ICER is routinely presented as one number, which invites a designer to treat it as one number. It is the ratio of two uncertain quantities, and probabilistic sensitivity analysis exists precisely because that ratio behaves badly under uncertainty. A design decision that removes the scatter, the ellipse or the acceptability curve removes the analysis.
Clinical charts compare against a protocol-defined arm. Economic models compare against a treatment mix that reflects a specific market, a specific year and a specific payer perspective. The visual must make the comparator basis and the perspective visible on the slide itself, because a reviewer who cannot see the perspective will assume the least favourable one.
Budget impact analysis is short-horizon and affordability-facing; cost-effectiveness analysis is often lifetime-horizon and efficiency-facing. The same intervention can be cost-effective and unaffordable at the same time, and presenting one without the other is where most value decks quietly lose credibility. ISPOR's good practice guidance treats these as complementary analyses answering different questions - the deck has to respect that separation visually, not merge them into a single "value" slide.
For the broader picture on Phase III readouts, forest plots and MLR-facing clinical charts, see our clinical data visualization playbook . This page deals only with the economic layer. Related: payer engagement decks for NICE reviewers and medical affairs presentation design . For budget-impact methodology specifically, see the ISPOR budget impact good-practice report .
Eligible population build-up, uptake scenarios, per-year net budget impact, and the with-versus-without comparison rendered so a budget holder can see the cash-flow shape across the horizon rather than a single aggregate saving.
The cost-effectiveness plane with PSA scatter and confidence ellipse, incremental cost versus incremental QALY positioning, and quadrant logic that stays readable when the cloud straddles more than one quadrant.
Probability cost-effective plotted across willingness-to-pay thresholds, with threshold markers relevant to the target jurisdiction rather than a generic reference line.
Base case, scenario analyses and the deterministic sensitivity tornado - built so the reviewer can see which parameters actually move the result and which are noise.
Health state diagrams, transition logic and cohort trace views for audiences who need to understand model structure before they will accept model output.
The two-to-four slide compression of a full model for a P&T committee, HTA submission support pack, or field access team - where the constraint is what a non-modeller can absorb without the analyst present.
Where the audience is commercial, the question is investment defensibility, and the economics still has to survive scrutiny from the HEOR lead who built it.
Every design decision in an economic visual is also an analytical claim. Four recur.
A cost axis that does not start at zero exaggerates incremental cost differences visually. In a clinical chart this is a readability debate. In a budget impact chart shown to a budget holder, it changes the perceived affordability of the intervention.
The scatter is the analysis. Replacing 1,000 simulation draws with one marker removes the reader's ability to see the proportion of iterations falling in the dominated quadrant - which is often the single most decision-relevant feature of the plane.
A tornado is ranked by influence. Reordering bars for symmetry, or truncating the low-influence tail without saying so, misstates which assumptions the result depends on.
Undiscounted lifetime savings look dramatic. A reviewer who finds the discount rate only in 6-point type at the slide base has already decided how carefully to read everything else on the page.
None of these require bad intent. They are the default output of a competent generalist designer who has been asked to make a dense chart look clean and has no basis for knowing which elements are decorative and which are load-bearing. The fix is not more design polish - it is a production process where someone who understands the model reviews the visual before it ships. NICE HealthTech methods make scenario and sensitivity analysis central to how uncertainty is reviewed, which is why those elements cannot be hidden in the appendix by default.
We start from the model, not a screenshot. Send the workbook - outputs tab, PSA results, scenario table. Rebuilding a chart from an exported image guarantees the visual inherits whatever the original chart got wrong, and makes it impossible to check a figure against the cell that produced it.
Every figure is traceable. Each chart carries an internal reference to its source range, so when a reviewer challenges a number during MLR, HTA prep or an internal pricing review, the answer takes minutes rather than a re-run.
Unpublished models stay unpublished. NDA-ready workflow, encrypted file handling, restricted access on the production side. Pre-submission economic models are among the most sensitive assets a market access team holds; we treat them accordingly. Covered by professional indemnity insurance and a structured compliance framework for vendor and procurement review. See our data protection and secure file handling approach for the operating model behind that workflow.
Overnight production. Brief lands with us in your evening; the built deck is waiting in your morning. For teams working to an HTA submission window or a committee date, that is the difference between iterating twice and iterating once. The same production cadence supports overnight presentation design when market access deadlines move faster than normal agency cycles.
Practitioner review, not design review. Life sciences work is reviewed by our Life Sciences principal before delivery. That is the structural difference between us and a subscription creative service or a template platform - the person checking the visual has sat on the other side of the advisory board table.
Dedicated POD retainer. You work with the same team across the model, the submission pack and the field-facing summary, so the second project does not start from an explanation of what a CEAC is. For adjacent sector context, see our guide to top UK life sciences consulting firms .
Show the base case alongside the uncertainty that produced it - PSA scatter on the cost-effectiveness plane, or a CEAC across the relevant willingness-to-pay range. Where a single figure must appear, it carries the credible interval and the threshold context on the same slide, not in a backup appendix.
Yes, and it is the preferred input. We work from the outputs tab and scenario ranges, not from exported chart images, so each figure remains traceable to its source cell.
They answer different questions and should not share a slide. Budget impact addresses affordability over a short horizon from a named payer's perspective; cost-effectiveness addresses efficiency, usually over a longer horizon. Merging them produces a "value" slide that a reviewer cannot audit.
Yes, under NDA with encrypted handling and restricted internal access. Pre-publication and pre-submission models are routine inputs for us.
Standard overnight cycle - brief in your evening, built deck by your morning. Complex model explainers with new health-state diagrams may run a second cycle.
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