We Know How to Pilot Healthcare Innovation. Why Don’t We Know How to Scale It?

Jessica Lindley

Sep 2

11 min read

At MESC this year, I had the opportunity to ask Daniel Brillman, Deputy Administrator at CMS and Director of the Center for Medicaid and CHIP Services, a question that has stayed with me.

I started with an observation: We are really good at innovating in Medicaid. We are terrible at scaling it.

States are constantly developing new approaches to maternal health, pharmacy, behavioral health, dental care, rural health, technology, member engagement and care delivery.

We know how to innovate. We know how to pilot.

But when something works, moving that innovation beyond the state, community or program that developed it becomes much harder.

So my question to Dan was: What role does CMS play in helping states scale innovation?

His answer was: Governance.

Later, when I met Dan, he told me it was a great question, and I have kept thinking about his answer ever since.

More recently, former Oregon Governor John Kitzhaber article, The Opportunity in the Crisis, pushed me to think about it again from the policy side: when the existing healthcare system is under pressure, do we simply try to preserve it, or do we use the opportunity to rethink how it works?

Because I think Dan is right. Governance gets to the heart of the scaling problem.

But his answer leads me to another question: How can CMS use the governance, policy and implementation infrastructure it already has to make successful innovation easier for states to scale?

I Think We Have the Sequence Backwards

A pilot proves the model. Policy determines whether the model can travel.

We tend to approach healthcare transformation something like this:

We prove something can work. Then we try to scale it.

And that is often when we discover that the policy infrastructure does not support the model.

Who can be served?
What can be paid for?
Who can provide the service?
What data can be exchanged?
What approvals are required?
How can the funding be used?

Then procurement begins. Technology requirements emerge. Governance and reporting structures have to be created. And organizations that were not involved in building the program are suddenly expected to implement it. Scaling fails.

Policy should not be something we discover is a problem when we are already trying to scale. Policy should help make scale possible — and replicable.

So what if we approached transformation differently?

Define → Identify → Enable → Design → Execute → Feedback

Define the transformation → Identify the barriers → Enable through policy and governance → Design the implementation → Execute together → Feedback what we learn into the next implementation.

The Federal Government Has Done This Before

There is an important historical precedent.

In the late 1970s, New Jersey began using Diagnosis-Related Groups (DRGs) as the basis for a different way of paying hospitals. The first large-scale application of DRGs as the basis for hospital payment occurred in New Jersey. Instead of simply reimbursing hospitals retrospectively for their costs, the state used DRGs to establish prospective payments.

The federal government paid attention, and in 1983, Congress established a national DRG-based prospective payment system for Medicare inpatient hospital services. New Jersey's experience became an important precedent demonstrating that prospective payment based on DRGs was feasible.

Think about that sequence:

State innovates → Federal government learns → Policy aligns → Implementation scales

The federal government did not ask every state and every hospital system to independently reinvent the concept. It learned from what had already been done.

The federal government learned from the state — and then policy helped enable broader implementation.

That is the part of the DRG story that I think deserves more attention today.

Scaling Does Not Mean Copying. Scaling Means Replicating.

Copying says: "It worked in Georgia. Let's do exactly what Georgia did."

That rarely works in Medicaid because Medicaid is intentionally state-driven.

California is not Oregon.

Oregon is not Mississippi.

Wyoming has different geography, workforce capacity and healthcare infrastructure than all three.

A maternal health program that succeeds in Mississippi cannot simply be dropped into Oregon.

A rural pharmacy model that works in Wyoming may need significant adaptation somewhere else.

But adaptation should not require reinvention. This is where replication matters.

Replication says:

"We understand why this program worked in Georgia. Now, how do we reproduce the core elements in Florida?"

Replication preserves the elements responsible for the outcome while adapting implementation to local realities — population, culture, workforce, geography, technology, payment structures, community partners and state policy.

And replication needs to be considered while we are designing the model, not after the pilot is over. So when the next state begins implementation, we should already know:

What made the model work?
What policy authority enabled it?
How was it financed?
What did the workflow actually look like?
What technology and data were required?
What did implementation cost?
What failed?
What would the original team do differently?
What is essential to the model?
What needs to be tailored for another state's population, culture, geography, workforce and healthcare delivery system?

Standardize what makes the model work. Tailor what makes it work locally. That is replication.

We Need to Make Implementation More Replicable

There is another barrier to scale that receives far less attention:

The infrastructure required just to implement something.

Depending on the initiative, states may need to navigate federal authorities, develop Advance Planning Documents for certain technology investments, obtain approvals, procure technology or services, negotiate contracts, establish governance, define measures, develop reporting structures and build an implementation organization around the program.

Procurement alone can take years.

Grants create another version of the same challenge.

A state can receive millions of dollars to transform healthcare and still have to create much of the machinery required to turn that funding into an operating program.

Some of this is necessary because these are public dollars and there should be accountability, oversight, beneficiary protections and measurement.

But accountability and replication are not opposites.

A state receiving funding should not have to build an entirely new implementation infrastructure just to spend it successfully.

If an APD structure, procurement approach, technology specification, reporting framework or implementation model has already worked somewhere else, how much can be reused? How much can be standardized? How much can be adapted rather than recreated How much administrative work are we asking states to repeat that adds little to the transformation itself?

CMS is already moving in this direction in Medicaid technology. Its standardized Medicaid Enterprise Systems templates are designed to expedite funding reviews, evaluate reuse opportunities, standardize reporting against APD milestones and reduce administrative burden. That is important.

But why stop at technology?

What if we applied the same philosophy to healthcare transformation itself?

What Retail Health Taught Me About Scale

This is one area where government healthcare can learn something from retail health.

When we take a successful retail health program into another market, we do not start with a blank sheet of paper.

We start with a playbook.

A good implementation playbook answers questions like:

Core offer: What services are we delivering, to whom, and what problem are we solving?
Standardized components: What cannot change — clinical standards, safety requirements, core workflow, service expectations, data requirements and quality measures?
Local adaptation: What should change based on population, culture, language, geography, workforce, community resources and market conditions?
Consumer journey: How does someone discover, access, use and complete the service? Where is the friction?
Workflow: Who does what, in what order, using which systems, with clear handoffs?
Technology: What is required versus optional, and how does it connect with existing infrastructure?
Workforce: What capabilities and roles are actually required rather than assuming every location needs an identical staffing model?
Partnerships: What relationships are needed locally?
Economics: What does it cost to launch and operate? How is it paid for? What volume is required? What makes the model sustainable?
Performance: What common measures allow us to compare implementations?
Feedback loop: What gets measured locally and fed back into the broader model so the playbook keeps improving?

A playbook means we know what has to remain consistent and what needs to change for the local market, so the next market does not have to recreate the operating model.

It configures, adapts, and replicates.

That makes implementation replicable.

Government healthcare is obviously different from retail health. Medicaid operates within federal and state law, serves populations with complex needs and requires public accountability that should never be sacrificed for speed.

But we can borrow the playbook implementation discipline — and apply it through governance.

Imagine a successful Medicaid model with a living implementation playbook:

Relevant federal authorities.
Reusable APD components where applicable.
Procurement and contracting approaches.
Technology and interoperability requirements.
Payment options.
Core workflows.
Staffing models.
Data specifications.
Measures.
Implementation milestones.
Governance approaches.
Known policy barriers.
Lessons learned.
And, critically, a clear distinction between what is core and what should be configured locally.

Then the next state does not start by asking: How do we build this?

It starts by asking: How do we make this work here?

That is a fundamentally different starting point.

Rural Health Transformation Gives Us an Opportunity Right Now

The Rural Health Transformation Program may be one of the best opportunities we have to put this thinking into practice.

CMS is investing $50 billion over five years across all 50 states.

Think about what that represents.

Fifty states simultaneously working on rural workforce, technology, access, innovative care delivery, behavioral health, maternal health, pharmacy, infrastructure and other transformation priorities. This could become one of the largest healthcare learning opportunities we have ever created.

But it could also become 50 separate implementation exercises. Each state developed its own transformation plan. Now states have to turn those plans and federal dollars into operating programs.

Look at Oregon. Oregon received $197.3 million in first-year funding and created multiple pathways to move those dollars into communities and organizations. Its competitive Catalyst Awards generated 583 project proposals from 353 organizations requesting more than $830 million across two budget years. OHA selected 85 organizations representing 103 projects for Catalyst funding. That is an enormous amount of implementation activity.

Now multiply the learning happening in Oregon by 50.

There is and will be tremendous innovation. The question is whether we capture only the outcomes — or whether we also capture the implementation knowledge that produced them.

If Oregon develops an effective rural pharmacy model, what can another state learn from it?

If another state solves a difficult rural workforce problem, how quickly can Oregon adapt that approach?
If a state creates a maternal health model with meaningful results, how do we ensure the next state begins with everything the first state already learned?

If we build the playbook while the transformation is happening, then we do not just have a final report, we have …

The operating model.
The workflow.
The payment approach.
The technology.
The policy authority.
The community partnerships.
The mistakes.
The implementation timeline.
The measures.
The feedback

CMS is already creating some of the infrastructure for this. It has dedicated project officers working with states, provides technical assistance and has brought all 50 states together through the Rural Health Transformation Summit to share lessons and effective models. That creates an enormous opportunity. Rural Health Transformation could become more than 50 state programs.

It could become a national learning system with 50 implementation environments.

I am working on a 50-state RHTP matrix to track what states are funding, who is involved, where implementation stands and what we can learn across states. More on that in the coming weeks.

Use What Already Exists

CMS does not need to build an entirely new scaling infrastructure from scratch. Much of the infrastructure already exists.

CMS has established the Office of Rural Health Transformation within CMCS to guide states in implementing their rural health transformation plans, provide technical assistance and coordinate federal and state partnerships. CMS and CMCS have also used technical assistance, cross-state learning, learning collaboratives, standardized tools and implementation resources to help states build capacity and spread promising practices.

So perhaps the opportunity is not creating more infrastructure.

It is using governance to make the infrastructure we already have work more deliberately as a scaling system.

Use what exists. Capture what works. Remove unnecessary friction. Make implementation replicable. And stop requiring every state to reinvent implementation.

That could mean developing playbooks based on a Transformation Framework.

From Innovation to Scale: A Transformation Framework

Then feed what we learn back into the playbook. The playbook improves.

Policy evolves. Implementation becomes easier.

And the next state starts further ahead.

The People Doing the Work Have to Own It

There is one more piece that I believe is critical. We cannot design transformation at the top and then simply hand implementation off.

Consulting firms can provide tremendous value. They bring expertise, structure, specialized capabilities, facilitation and lessons from other markets. They can help design the strategy, build the implementation model and guide execution. But sustainable transformation cannot depend on the consultant.

(And, um, I’m a consultant. I have a consulting firm. So this is definitely not an argument against consultants.)

The people and organizations responsible for carrying the work forward need to have ownership of it.

Think about a rural health transformation initiative designed to improve access to care.

A state could develop the strategy, issue an RFP, select a vendor and tell rural communities what the new model will look like. (current state)

Or the people who actually have to make the model work could help design it from the beginning. We are already seeing versions of this approach. (future state)

Washington’s Community Information Exchange is being co-designed with the organizations and communities that will ultimately have to make it work. The effort brings CBOs, health systems, health plans, regional organizations, state agencies and other partners together to help shape the model around how care and community services actually operate.

Oregon’s Rural Health Transformation Program is doing something similar. Rather than designing every solution centrally, Oregon is moving funding into communities and organizations that understand their local populations, workforce, infrastructure and access challenges — and allowing those organizations to help shape how transformation happens on the ground.

The models are different, but the principle is the same: The people closest to the work help shape the work.

That does not eliminate the need for state leadership, federal oversight, consultants or a common framework. It makes those things more effective because implementation knowledge is coming from both directions. What does that look like in practice?

The rural hospital can tell you whether the proposed workflow is realistic.
The pharmacist can tell you where medication access actually breaks down.
The behavioral health provider can tell you where referrals are being lost.
The community organization can tell you why people are not using a service that looks accessible on paper.
The technology team can tell you whether the systems can actually exchange the information the model requires.
And the person living in that rural community can tell you something none of them can: whether they would actually use it.

Those are not implementation details to figure out after the strategy is complete.

They are part of the strategy.

The people doing the work need more than an opportunity to review the plan or comment on it after it has been designed.

They need a vested interest in the change.

That means helping define the problem, designing the operating model, identifying what will not work, determining what needs to be adapted locally and sharing accountability for the outcome.

And it fits the same transformation framework:

The people who execute the transformation should be involved in defining and designing it — and what they learn during implementation should feed directly back into what happens next.

That is more than stakeholder engagement. That is shared ownership.

The Opportunity

We are really good at innovating in Medicaid.

Now we need to get much better at making what works easier to use somewhere else.

The goal is not federal standardization.

It is federally enabled replication.

It means the next state should benefit from everything the first state already learned.

Build the playbook.

Make implementation more replicable.

Identify policy barriers early.

Reuse what can be reused.

Adapt what needs to be local.

And keep feeding what we learn back into the system.

We tend to think:

Innovation → Pilot → Scale → Change policy if necessary

Maybe it is time to think about a new framework:

Which brings me back to Dan Brillman's answer at MESC: Governance.

But perhaps the opportunity is not more governance.

It is governance designed for replication.

Governance that recognizes successful innovation early.

Governance that captures what made it work.

Governance that identifies policy barriers before the next state encounters them.

Governance that makes the implementation knowledge replicable.

And governance that creates a feedback loop, so every implementation makes the next one better.

The federal government has learned from state innovation before.

It can do it again.