How Pharma Teams Use Healthcare Data to Prioritize New Market Opportunities

Expansion planning usually starts from the two numbers a pharma team already has, Medicare beneficiaries and physician headcount, and that is where the trouble starts.

Two territories can hold the same number of Medicare beneficiaries and nearly identical physician headcounts, yet differ by a factor of two or more in the procedures and diagnoses your product actually serves.

Population and headcount treat those markets as equivalent, so reps and budget get spread evenly across markets that were never equally valuable. Headcount survives as the default because it is the number every team already has and it feels objective, but it counts the supply of providers rather than the demand for what you sell.

The cost of that error compounds. Consultancy McKinsey has found that about two-thirds of new drugs miss their prelaunch first-year sales forecasts, and products that stumble early tend to keep underdelivering for years.

Where a team chooses to compete, and in what order, is one of the few things it controls before the launch even starts.

What Pharma Teams Need to Know Before Entering a New Market

Before committing coverage, the useful question is less about a market’s size and more about how the opportunity inside it is arranged. A market has a shape. Relevant demand sits unevenly across its providers, and access to those providers runs through specific organizations.

Competitors, meanwhile, already hold relationships you will have to displace. None of that shows up in a population figure, and all of it determines what it costs to win share.

Population Counts Tell You Almost Nothing About Opportunity

Population correlates loosely with demand at best. Age structure, disease prevalence, referral patterns, and site of care all pull the two apart, so a market with many people but little relevant procedure activity is expensive to cover for a thin return.

A mid-sized market dense with the right billing activity can outperform a larger one that looks better on a headcount slide.

The number that matters is how much of the clinical activity your product depends on is actually happening there, which no provider or patient count can tell you.

Every Market You Enter Already Has a Structure

You are rarely entering a blank slate. A 2026 American Medical Association analysis found that virtually all US hospital markets are highly concentrated and have grown more concentrated over the past decade, with a single hospital holding at least half the market in about 78% of them by 2024.

Concentration at that level means access in most markets is gated by a small number of dominant players, and the identity and behavior of those players changes from one market to the next.

Reading that structure before you enter tells you whether you are walking into a market you can work provider by provider or one where a handful of systems set the ceiling.

Competitors Are Already in the Market You Are Sizing

A market’s providers are rarely uncommitted. Many already carry relationships with the manufacturers you will compete against, through existing product use, speaking arrangements, or research collaborations, and those ties raise the cost of switching them.

Financial relationships between manufacturers and providers show up in the federal Open Payments record, which makes competitive incumbency a readable feature of a market rather than something a rep discovers on the third visit.

A market where a rival holds deep, established relationships across the high-volume providers is slower and costlier to win than one where those providers are unattached, even when the two look identical on clinical volume.

Weighing incumbency alongside demand keeps a team from ranking a contested market above a winnable one.

How HCP Concentration Reveals Where Commercial Opportunity Exists

Population misleads because clinical volume does not distribute evenly across providers. In most therapeutic areas a small share of clinicians accounts for a large share of the relevant activity, and those clinicians are not spread uniformly across the country.

Locating where they cluster is most of the work of sizing a market.

A Small Share of Providers Drives Most of the Relevant Volume

The pattern is easy to see in procedure data. A national Medicare analysis of 30,467 radiologists found that only 1,366 did interventional radiology work more than 90% of the time in 2022, and even at a threshold of half their work the count reached just 2,859, few enough that fewer than one such physician practices per US county.

That property runs through procedure and diagnosis records generally, which is that volume concentrates in a small share of providers.

For a commercial team selling into interventional radiology, the real market is those few thousand high-activity physicians, not the full radiologist count a headcount slide would show.

The demand comes from a smaller set of high-volume providers, and a market’s value depends on how many of them sit inside it. Concentration also sets what good coverage costs. When most of a market’s relevant volume runs through thirty providers, a team can put senior reps on those accounts and cover the market well at a low headcount.

Spreading the same volume across three hundred lower-volume providers and reaching it takes far more people for the same return, which quietly makes the second market more expensive to serve even where the topline opportunity looks similar.

High-Volume Providers Cluster in Particular Places

Those high-activity providers are not spread evenly either. When a specialty’s real procedural volume runs through only a few thousand physicians nationwide, whole regions can hold a disproportionate share of them while others have almost none, so some markets are structurally richer than others for a given product.

A region holding a disproportionate share of the high-volume providers you care about rewards each rep more than a region where the same providers are thin and scattered across long distances.

Two markets can post the same physician count and offer completely different returns on the same coverage spend, and only the provider-level activity shows you which is which.

Using Claims and Procedure Data to Understand Local Clinical Demand

Claims data is the closest thing a commercial team has to a direct read on local demand, because it records what providers actually billed rather than what a population model predicts.

Two markets with similar demographics can show very different procedure and diagnosis volumes once you look at the billing record, and that gap separates a market worth entering from one worth skipping.

Claims Data Shows Demand That Population Estimates Miss

Decades of Dartmouth Atlas work found that Medicare spending and utilization vary more than twofold across the 306 hospital referral regions, and most of that gap reflects differences in the volume of services delivered rather than price.

Utilization spread that wide means a forecast built from population can be off by a large margin in any specific market. Billing data corrects it by showing the procedures and diagnoses that are genuinely present, so a team sees the demand as it exists rather than as a per-capita assumption implies it should.

It also sharpens the specialty label, since a physician’s listed specialty only suggests what they might do while the billing record shows what they actually bill, and the two diverge often enough to distort a market sized on specialty headcount alone.

Procedure and Diagnosis Volumes Vary More by Place Than You Expect

The disease burden itself is deeply uneven. Diagnosed diabetes among adults ranges from 6.5% in Colorado to 14.4% in Puerto Rico, and within the mainland runs from about 7% in some northeastern metro counties to nearly 15% in the nonmetro South.

Prevalence that uneven feeds straight into where the patients, and therefore the prescribing and procedures, actually sit. A cardiometabolic product has a materially larger local market in a high-prevalence region, and the claims record tells you how much larger rather than leaving you to guess.

How Physician Affiliations and Organizations Add Market Context

Knowing who the high-volume providers are and where they practice still leaves out how you reach them.

A provider’s affiliation, whether independent, hospital-employed, or owned by a corporate group, changes the path to access and sometimes the channel through which a drug even reaches the patient.

As of January 2026, 82% of US physicians were employed by hospitals or corporate entities and 63.9% of practices were owned by them, according to the Physicians Advocacy Institute and Avalere Health.

An employed physician’s formulary and purchasing choices often run through a system committee rather than the individual, so a market dominated by employed providers demands a different engagement model than one full of independents. Affiliation also reshapes the dispensing channel.

A JAMA analysis found that by 2019, 63% of medical oncologists were employed by organizations operating their own specialty pharmacies, which changes where high-cost drugs are dispensed and who controls that flow.

That national average hides wide regional gaps. A single national trend lands very differently market to market.

A team entering a heavily consolidated southern market is negotiating access with systems and committees, while one entering a less consolidated market is still dealing with independent decision-makers, and the coverage plan has to reflect which situation it is walking into.

Comparing Regional Opportunities Before Expanding Commercial Coverage

No single number ranks markets. A useful comparison lines them up on the same axes and weighs each against what it will cost to cover.

Demand density and provider concentration set the size of the prize. How hard that prize is to capture depends on organizational structure and payer mix, and two of those axes move the economics enough to deserve a closer look.

One or Two Systems Can Control an Entire Market

Market structure can compress the entire access question into a few decisions. KFF found that in 83% of metro areas, one or two health systems control more than 75% of the inpatient hospital market, and nearly one in five metros is dominated by a single system.

In a market where one system holds the majority of relevant sites, a handful of committee decisions determine your ceiling.

A fragmented market offers more independent entry points but asks for more feet on the ground to work them. Neither is automatically the better bet, and the concentration data tells you which one you are choosing.

Payer Mix Changes the Economics of the Same Clinical Opportunity

Who pays in a market shapes how easily clinical demand converts to revenue. Medicare Advantage penetration varies widely by county, with a handful enrolling more than 80% of beneficiaries while 8% of beneficiaries live in counties where fewer than a third are in MA plans.

Payer mix sets reimbursement dynamics and formulary control, so identical clinical demand can be far easier or harder to capture depending on the coverage landscape.

A market rich in the right procedures but locked behind restrictive plan formularies may rank below a smaller market with more favorable coverage, and that ranking only appears when you put payer structure next to clinical volume.

So, a large southern metro can show high procedure volume and a dense field of high-value providers, then slide down the list once you see that two systems control most of the sites and a restrictive plan mix governs access.

But a smaller Midwestern market with moderate volume, more independent providers, and cleaner coverage can be the easier first win, even though it never looked bigger on a population map. The comparison earns its keep in exactly those moments, when it overturns the ranking a headcount would have handed you.

Turning Market-Level Data Into Practical Pharma Expansion Decisions

Market-level data will not make the expansion decision on its own, though it narrows and de-risks that decision, turning a set of even bets into a ranked, sequenced plan.

Consulting firm Deloitte, reviewing 284 US drug launches from 2012 to 2021, found that about a third fell short of expected sales, with an inadequate understanding of the market a recurring cause.

Observed market data addresses that cause at the point of the decision by replacing assumption with billing behavior.

Sequence Markets Instead of Entering Them All at Once

A ranked list lets a team phase entry, concentrating early coverage in the highest-density, most accessible markets and building proof before extending. Sequencing protects budget and gives the sales model time to mature where the return is clearest.

The alternative, even coverage from day one, spreads reps thin and produces much of the underperformance the launch data keeps recording.

Done well, phasing points a launch at its strongest markets first instead of diluting it across all of them at once.

Match the Coverage Model to the Market’s Structure

Structure should decide the model as much as size does. A consolidated market controlled by a few systems may warrant a small, senior team that works committees and value analysis processes, while a fragmented independent market may reward broader field coverage or a digital-first approach.

Reading structure before staffing means the team is sized and shaped to the market it is actually entering, rather than stamped from one template applied everywhere.

That fit is the difference between a rep roster that matches the work and one that is misallocated from the first week.

Revisit the Ranking as Markets Move

A market ranking is a snapshot, and the activity underneath it keeps changing as practices are acquired, providers relocate, and procedure volumes shift.

A region that ranked fourth last year can climb once a competitor loses a key account or a new site opens, and a team working from a stale ranking misses the window. Treating the market map as something to refresh, rather than a one-time input, lets a team redirect coverage while a shift is still early instead of reacting after a rival has already moved.

Teams that hold share across a launch cycle tend to be the ones re-reading the market on each data refresh instead of defending last year’s plan.

How Alpha Sophia Helps Pharma Teams Evaluate and Prioritize Market Opportunities

Building this market-level view means pulling provider activity, affiliations, and geography into one place and comparing markets on consistent terms.

Alpha Sophia supplies that as an external reference layer, anchored to the national provider identifier, that a pharma team queries to see a market before committing to it. The platform provides the observed evidence, and the team keeps the decision.

A Market-Level View Built on Observed Clinical Activity

Alpha Sophia draws on claims across Medicare, Medicaid, and commercial payors for more than 3.9 million active US providers, with procedure and diagnosis detail in CPT, HCPCS, and ICD-10 alongside taxonomy, affiliations, open payments, publications, and clinical trials.

For a market evaluation, that means you can read the actual procedure and diagnosis volumes in a region rather than inferring them from population.

Alpha Sophia’s market intelligence tooling lets a team see a market’s clinical activity and existing competitive relationships directly from the billing record. Because the data is regularly refreshed, a market that was thin last year but is climbing now shows up as it moves rather than after the fact.

Comparing and Ranking Markets Before You Commit Coverage

Cohort analysis lets a team compare provider groups across regions to see where demand concentrates and how it is trending, which is the core of ranking one market against another. Geographic and practice-location filtering surfaces the regions with strong opportunity or underserved gaps, so a shortlist rests on activity rather than intuition.

When it is time to translate a ranked market into coverage, the platform’s territory tools let a team draw and redefine boundaries, run heat map analysis, and view the size of the opportunity alongside the territory design, down to the state-level volumes useful for deciding where a first rep or two should go.

The output is a prioritized map the team can act on and refresh, so coverage decisions rest on current activity instead of a snapshot that has already aged.

Conclusion

The difference between a market that pays back its coverage and one that drains it is rarely visible in a headcount.

Relevant demand concentrates in a small set of providers. Those providers cluster in particular regions, and access to them runs through organizations that differ sharply from one market to the next.

A pharma team that reads those patterns before allocating coverage enters fewer markets first and staffs each to its real structure, putting early spend where the observed opportunity is densest.

Against a competitor still ranking markets by population, that is a materially better starting position, and in a launch environment where most products miss their first year, that starting advantage often decides how the year ends.

FAQs

What is pharma market opportunity analysis?
Pharma market opportunity analysis is the process of evaluating and ranking potential markets or regions by their real commercial value before committing sales and marketing resources. It looks past population size at the clinical demand, provider concentration, and access structure that actually determine how much revenue a market can return.

How can healthcare data help pharma teams identify new market opportunities?
Healthcare data replaces assumptions about a market with observed behavior, showing which procedures and diagnoses are billed in a region and which providers drive that volume. That lets a team spot high-value markets a population or physician-count estimate would miss, and skip markets that look attractive on paper but produce little relevant activity.

What healthcare data should pharma companies use for market analysis?
The most useful sources are claims-based procedure and diagnosis data in CPT, HCPCS, and ICD-10, along with provider taxonomy, organizational affiliations, and geographic distribution. Together these show where clinical demand sits, who serves it, and how access to those providers is structured across regions.

How can pharma teams compare market opportunities across regions?
Teams compare regions on consistent axes such as procedure and diagnosis volume, the concentration of high-volume providers, organizational and payer structure, and the cost of coverage. Cohort and geographic analysis let them line markets up side by side and rank them rather than leaning on a single figure.

How does HCP data support pharma market expansion?
HCP data shows how relevant clinical volume is distributed across providers and where the high-volume ones practice, which sets how concentrated and reachable a market’s opportunity is. It also reveals affiliations and existing manufacturer relationships, so a team can see how access works in each market before it expands.

How does Alpha Sophia help pharma teams evaluate market opportunities?
Alpha Sophia is an external, NPI-anchored reference layer that supplies claims-based provider data across Medicare, Medicaid, and commercial payors for more than 4 million US providers. Teams use its cohort analysis, geographic filtering, and territory tools to compare markets on observed clinical activity and structure, then make and own the expansion decision themselves.