Dimensional Health Partners

Healthcare AI that actually ships.

A boutique product practice for healthcare operators. We turn AI ambition into deployed product — one disciplined experiment at a time.

How we work Start a conversation

The Problem

Most healthcare AI dies in pilot.

Healthcare doesn't lack AI ideas. It lacks the discipline to ship them. Most teams optimize one dimension — a clever model, a slick demo, a willing pilot clinic — and assume the rest will follow. They don't.

The model breaks clinical workflow. The economics don't pencil for the payer. Compliance review takes nine months. The pilot ends, the deck circulates, the work disappears. Most healthcare-AI roadmaps are wishlists pretending to be products.

We build the practice that fixes this — a product discipline grounded in SaaS rigor, boutique-consultancy method, and customer advisory work, applied to the dimensional complexity of healthcare. The result isn't a deck. It's an innovation engine that compounds inside your organization.

The Lens

Six dimensions. Every bet.

We pressure-test every hypothesis across the six dimensions where healthcare AI either earns trust or dies trying. Bets that can't hold all six don't move forward.

Clinical

Does it work, and is it safe?

Evidence pathway, clinician trust, safety review. The model has to earn its place at the point of care.

Economic

Does the math work for everyone touching it?

Unit economics, reimbursement path, ROI for the operator, payer, and provider. If one side loses money, the bet is dead.

Regulatory

HIPAA, FDA SaMD, state-specific rules.

Compliance posture mapped before build, not after. IRB if it crosses into research. We design for the review the buyer will run.

Operational

Does it fit clinician and staff workflow?

Implementation cost, change-management load, training burden. A feature that adds friction loses to no feature at all.

Technological

Is it buildable, maintainable, and integrable?

EHR data access, model lifecycle, observability, fallback paths. We engineer for the boring middle that determines whether the system survives in production.

Human

Do real people actually want to use it?

Adoption, friction, behavior change. Clinicians, staff, patients. The dimension that decides whether the pilot becomes a product.

The Method

Five stages. Pre-committed gates.

We move teams through a deliberate loop. Every stage has success criteria locked in before we start. Bets that miss the gate get sunset fast — no zombie pilots, no roadmap theater.

Discover

Find the friction that isn't in the deck.

Ethnographic research with clinicians, ops, and patients. JTBD interviews. Workflow mapping. The pain audit is grounded in what we observe, not what the roadmap claims.

Artifact

Opportunity brief

Hypothesize

Frame opportunities as testable bets.

Pre-register success metrics. Pressure-test the bet across all six dimensions with the operator's customer advisory board. Surface the riskiest assumption before we spend a sprint.

Artifact

Hypothesis register

Prototype

Build the smallest provable version.

Concierge MVPs, Wizard-of-Oz, AI-assisted lo-fi → mid-fi prototypes. We move faster than the engineering team's sprint cycle and intentionally avoid production code at this stage.

Artifact

Working prototype + signal data

Pilot

Run a controlled live test.

A constrained slice of the business — one market, one specialty, one patient cohort. Measure leading indicators against the metrics we pre-registered, not anecdotes from the most enthusiastic site.

Artifact

Pilot readout against pre-committed gates

Scale or Sunset

Pre-committed gates. No zombie pilots.

If metrics hit, we productize and roll out across the operator's customer base, then position for the broader market. If not, we sunset honestly, document the lesson, and move the team to the next bet.

Artifact

Roll-out plan or sunset memo

On Gates

The discipline isn't the stages — it's the gates between them. A bet that passes Discover still has to clear the Hypothesize review to enter Prototype. Most healthcare-AI programs fail because no one wrote down what passing looks like. We write it down first.

Why This Compounds

An asset. Not a service.

Most innovation consulting resets to zero the day the engagement ends. The method leaves with the consultants, the learnings die in a deck, and the operator funds the next round of discovery from scratch. We build the opposite — a practice that compounds inside the organization with every bet that ships.

Methodology IP

The hypothesis register, dimensional review templates, and gate criteria become institutional IP — owned by the operator, not by us. Year-two engagements run faster than year one. By year three, the lab itself is the asset.

Customer insight

Each customer advisory cohort builds a proprietary view of where the market is actually moving — not where the analyst reports say it is. That insight is exportable across product lines, adjacent markets, and tuck-in acquisitions.

Clinician trust

Products that survive the dimensional review earn clinician trust. Trust compounds: the next launch lands into a customer base that already believes the operator ships things that work.

Portfolio leverage

Discoveries from one bet inform the next. A methodology that ships an MVP for the operator's largest customer transfers, with effort, to adjacent customers, adjacent markets, and adjacent portfolio companies.

Durable. Repeatable. Transferable.

The kind of innovation engine that earns long-dated capital and rolls across markets, customer cohorts, and platforms.

Engagements

Three ways to work with us.

We take on a small number of engagements at a time. Every one runs on the same discipline — only the scope and duration change.

AI Lab as a Service

6–12 months

Stand up and run a disciplined innovation lab inside your organization.

We define the portfolio of bets, run the discovery → pilot loop, build the MVP pipeline, and hand off a practice your team can keep running. By the end of the engagement, the lab is an institutional asset — methodology, IP, customer insight, and operating cadence owned by you.

Best for

Operators with real distribution who want a repeatable innovation muscle
Founding an AI lab from zero, or rescuing a stalled one
Targeting 3–6 deployable MVPs in year one

II.

Healthcare Product Strategy

8 weeks

For operators with ideas but no clarity on which to fund.

Opportunity sizing, dimensional pressure-test, customer advisory work, and a prioritized roadmap of bets with pre-committed gates. Ends with a decision-ready strategy document and a board-grade investment case.

Best for

CEOs and CSOs facing a roadmap of 15 ideas and capital for three
Strategy refreshes after a leadership change or capital event
Pre-fundraising sharpening of an AI thesis

III.

0-to-1 Advisory

Monthly retainer

Fractional product and strategy partnership for founders and operators.

We embed with the build team, hold the discipline, and stay until the bet either ships or sunsets honestly. Best suited for a single AI product moving from idea to first-revenue customer.

Best for

Founders with conviction and a partial team
Operators spinning out an internal bet into a stand-alone product
Teams that have a prototype but no path to deployed

Not sure which fits? Let's talk.→

Who We Partner With

Operators with conviction. Product muscle to build.

Our best engagements share a profile. National tech-enabled VBC operators, MSOs, payer-enablers, and risk-bearing health systems who've already done the hard work of scale — and now need the product discipline to translate AI ambition into deployed product.

Scale already in place

Multi-state footprint. Hundreds of thousands to millions of lives touched. Real distribution that can carry a product when it's ready.

A data asset with more to give

Claims, clinical, encounter, contract data — and the legal right to use it. Most operators are sitting on the raw material; few have refined it.

AI in the marketing, not yet in the product

The deck says AI-powered. The roadmap still treats innovation as a feature list, not a portfolio of bets with pre-committed gates.

A CEO — and capital partners — who fund discipline

Backers who understand that the product muscle, not the model, is the moat. Who measure success in durable growth and repeatable IP, not pilot count or press releases.

If that sounds like your organization, we should talk.

Founder

Rami Rafeh.

Dimensional Health Partners is led by Rami Rafeh — a healthcare operator with twenty years across payers, providers, pharma, and corporate strategy. Senior roles at Healthfirst, Premera Blue Cross, Pfizer, and McKesson. Columbia University faculty. Board member. Investor.

Scaled value-based care across 400K+ members, evaluated 700+ digital health companies, directed $250M+ in capital, and led post-merger integrations at the scale of multi-billion-dollar transactions. Serves on boards including FirstWA and Sound Behavioral Health.

DHP is the synthesis of that operator history: the product disciplines learned shipping inside SaaS-style companies, applied to the dimensional complexity of healthcare.

See the full operator history at ramirafeh.com→

Rami Rafeh, Founder of Dimensional Health Partners

Start

Let's build something that ships.

We take on a small number of engagements at a time. If your team is ready to convert AI ambition into deployed product — and you want partners who'll hold the discipline with you — we'd like to hear from you.

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Engagement Window

Currently engaging with one operator. Limited availability for Q3 2026 — we typically take on two to three engagements per half.