How MSOs Use Claims Data to Identify Potential Acquisition Targets

A brokered sale puts an MSO in front of a practice that has already decided to sell, alongside the other buyers on the broker’s list. The deal team gets that competition along with the teaser. Practices that have not hired an advisor never enter the process at all, so the buyer that identifies them first gets a conversation with no auction attached.

In the AMA’s Physician Practice Benchmark Survey, the share of physicians in practices wholly owned by physicians declined in every round since 2012, falling from 49.1% in 2020 to 42.2% in 2024. Competing buyers have accelerated over the same period. Private equity-owned practices grew from about 4.5% of physicians in 2022 to 6.5% in 2024, and 38% of physicians in those practices said their practice was acquired after 2019.

Claims data changes where that search starts. Every practice that bills Medicare, Medicaid, or a commercial plan leaves a record of what its physicians do, how often, for which conditions, and where.

For an MSO building density in a specialty, that record comes closer to a census of healthcare acquisition targets than anything available in a private-company database. It shows which practices already perform the procedures a platform is built around, which have the volume to justify integration costs, and which sit inside the geography the MSO wants to own.

That said, claims data answers a narrower question than many deal teams want it to. It describes clinical activity. It says nothing about EBITDA, payer contract rates, partner dynamics, or whether an owner is ready to sell.

MSOs get the most from it when they use it to decide where to look and whom to call first, and then let financial and legal diligence carry the deal from there.

Why Claims Data Can Support MSO Acquisition Research

An MSO acquisition strategy depends on finding practices that fit a clinical thesis, operate in the right markets, and can be integrated without disrupting patient care.

Claims data supports each of those judgments at the research stage, well before anyone signs a confidentiality agreement. Its value rests on coverage of practices that never reach a broker, a consistent record of clinical activity across an entire market, and a clear view of where that record ends.

The Strongest Practice Acquisition Targets Are Often Not for Sale Yet

Medical practice acquisition is a crowded field built mostly on small deals. The FTC’s study of physician mergers identified roughly 2,000 transactions across 15 states between 2015 and 2020 and found that the typical merger involved a much larger firm acquiring a much smaller one.

Deals of that size rarely surface through formal channels. Most fall below the federal premerger reporting threshold, which the GAO’s 2025 review of physician consolidation put at $126.4 million, so regulators and rival buyers often learn about them only after closing.

The motivation to sell is widespread, too. In the AMA survey, 70.8% of physicians whose practices had been acquired in the prior decade rated better leverage in payer negotiations as an important reason for the sale, ahead of access to costly resources and relief from administrative requirements.

Those pressures apply to many practices that have not yet hired an advisor.

So an MSO that waits for marketed inventory ends up competing for the same assets as every other buyer, usually at a higher multiple. Claims data lets the deal team build its own map instead. It starts from every physician billing for the services in the MSO’s thesis and works backward to the practices those physicians belong to, which surfaces single-site groups with no presence in any deal database.

Alpha Sophia’s review of tools for healthcare private equity roll-ups makes the same point from the sponsor side of the market.

What Claims Data Can Reveal About Physician Practices

Claims are billing records, so they describe a practice in the vocabulary payers use to reimburse it. CPT® and HCPCS Level II codes record procedures and services. ICD-10 codes record the diagnoses attached to each encounter.

The rendering provider’s NPI identifies the physician who delivered the service, while the billing identifier points to the organization that was paid. Place-of-service codes show whether the work happened in an office, an ambulatory surgery center, or a hospital outpatient department.

Taken together, those fields support healthcare claims data analysis at the level an acquisition team actually needs. A deal team can see how many physicians bill under a practice, which procedures dominate its volume, which patient conditions it manages, which sites of care it relies on, and how each of those patterns has shifted over several years.

Worth noting, the same analysis runs across every practice in a market at once, so the work that profiles one target also benchmarks it against every competitor nearby.

Where Claims Data Stops and Diligence Has to Begin

Even good claims data has edges, and an MSO should understand them before building a thesis on top of it.

Public Medicare files make the point clearly. CMS states that its Physician and Other Supplier data contains only fee-for-service Medicare claims, excludes Medicare Advantage, Medicaid, and commercial payers, redacts any data element representing fewer than 11 beneficiaries, and cannot separate services delivered at different practice locations.

A dermatology or orthopedic group with a large commercial book will look meaningfully smaller in that file than it is.

All-payor claims close much of that gap. Even so, no claims source shows profitability, negotiated rates, physician compensation, lease obligations, or compliance history.

The same GAO review also cautions that claims-based research has to infer practice membership from tax identification numbers and place-of-service codes, which can classify an affiliated physician differently from how that physician would describe their own practice.

So claims data works as a screening and prioritization layer. Valuation, quality of earnings, and legal structure remain the work of the MSO’s diligence team and its advisors.

Using Procedure Volume and Clinical Activity to Compare Practices

Once the universe of candidates exists, the work shifts to comparison. Procedure volume is the most direct evidence that a practice does the work an MSO’s platform is designed to support, though raw totals mislead without context.

Procedure mix, multi-year trends, and the combination of specialty and location each add the context that turns volume into a usable signal for healthcare acquisition analysis.

Procedure Mix Shows Whether a Practice Fits the Platform’s Service Lines

An MSO’s economics usually rest on a defined set of services. A gastroenterology platform with ambulatory surgery center capacity cares about diagnostic colonoscopy (CPT 45378), colonoscopy with biopsy (CPT 45380), and colonoscopy with snare polypectomy (CPT 45385). An ophthalmology platform cares about cataract surgery with lens implant (CPT 66984).

An orthopedic group investing in outpatient joint replacement cares about total knee arthroplasty (CPT 27447). Filtering for the physicians who bill those codes, and ranking their practices by volume, separates groups that match the operating model from groups that only share a specialty label.

Mix matters as much as totals. Two gastroenterology practices with similar colonoscopy counts can look very different once diagnosis codes are layered in, because one may concentrate on routine screening while the other manages a large inflammatory bowel disease population that drives infusion and follow-up visits.

Neither profile is better in the abstract. The right fit depends on what the platform already does well and which service lines it intends to grow.

Multi-Year Trends Say More About a Practice Than One Year of Volume

A single year of claims is a snapshot, while three to five years show direction. A practice whose core procedure volume has climbed while its physician count stayed flat is adding capacity per physician.

A practice whose volume fell after a partner departed may be carrying a dependency that a seller is unlikely to volunteer.

Year-over-year comparisons also reveal practices that recently added a service line, such as in-office procedures or access to an ASC, which changes both the integration plan and the seller’s price expectations.

Trend data also exposes concentration risk. When most of a practice’s procedure volume traces back to one or two physicians, the acquisition is effectively a bet on those physicians staying after close.

Retention terms, earnout structures, and the order in which the MSO approaches partners all need to reflect that before the first conversation, so the analysis belongs at the research stage.

Finding Practices With Relevant Specialty and Geographic Presence

Specialty fit and location together decide whether a practice can become an add-on or only a standalone investment. Density drives MSO economics, since shared call coverage, centralized scheduling, ASC utilization, and payer negotiating leverage all depend on practices sitting close enough to operate as one network.

The Milbank Memorial Fund’s analysis of MSOs describes markets attractive for consolidation as those with a large platform practice available alongside multiple add-on practices, which makes geographic clustering a core screening criterion.

Claims data supports this at two levels. At the market level, it shows how much procedure volume exists in a metro or county and how fragmented that volume is across practices. At the practice level, it shows where each candidate’s physicians actually deliver care, which often differs from the address on the practice website.

Specialty filters work best when taxonomy is checked against billing behavior, since a physician’s registered specialty and the procedures they perform do not always line up.

Independent supply also varies sharply by specialty and market.

The AMA found that 70.4% of ophthalmologists remained in private practice in 2024, compared with 54.0% of orthopedic surgeons and less than half of physicians in every specialty group outside the surgical subspecialties.

The GAO review reports that private equity firms had invested in practices employing more than 30% of gastroenterologists in 11% of metropolitan areas. An MSO entering a market should know early whether the remaining independent supply is deep or largely spoken for.

Combining Claims Data With Organization and HCP Intelligence

Claims describe services, but acquisitions happen at the level of organizations and the people inside them. The claims picture becomes useful for MSO growth strategy only after it is connected to the practice entity and enriched with physician-level context.

Rolling physicians up to their practices, profiling the people inside them, and scoring the result consistently turns a list of high-volume physicians into a list of practices worth researching.

Rolling Individual NPIs Up to the Practice Level Reveals the Real Target

Under CMS rules, an individual physician holds a single Type 1 NPI, while organizations such as physician groups receive Type 2 NPIs and can hold more than one. Claims connect the two, because each service records the physician who performed it and the entity that billed for it.

Aggregating physician-level activity up to the billing organization shows the practice the way an acquirer sees it, with total procedure volume, the number of contributing physicians, and the share of volume each one carries.

This step catches structure that is easy to miss. A group may bill under several organizational identifiers across its locations, or one tax identification number may cover multiple sites.

A study published in Health Affairs Scholar in July 2026 mapped dermatology and gastroenterology ownership using this kind of NPI-to-TIN linkage, and its authors cautioned that a TIN reflects a billing relationship that may not match a single clinical entity. An MSO should treat each rolled-up practice as a working hypothesis and confirm its structure during outreach.

The same study also shows why size matters for competition. Large physician-owned groups, which the authors call supergroups, were far more likely to change hands than smaller independents.

Between 2012 and 2022, 32% of dermatology supergroups and nearly 43% of gastroenterology supergroups experienced at least one ownership change, compared with around 11% of other independent practices. An MSO screening for scale should assume rival buyers are screening for it as well.

Physician Profiles Add the Signals That Claims Volume Cannot Supply

Once practices are defined, HCP intelligence fills in the human side of a medical practice acquisition. Affiliations show whether physicians already hold relationships with a hospital or health system, which can complicate a deal or signal an established referral base. Taxonomy, education, and training history describe the clinical team.

Publications and clinical trial participation identify physicians with academic standing, which matters to platforms that want clinical leadership or research capacity. Open Payments records show existing financial relationships with manufacturers, which diligence teams will want to understand early.

For MSOs evaluating patient flow between practices, Alpha Sophia’s overview of referral intelligence covers how referral patterns add a further layer of context.

Physician age deserves attention as well. The GAO notes that selling can be an attractive option for physicians approaching retirement, and AAMC workforce data shows that 23.9% of active physicians were 65 or older in 2024.

A practice whose highest-volume physicians are nearing retirement presents a different opportunity from one led by physicians in mid-career, and the difference shows up in deal structure, recruitment plans, and integration risk.

Turning Claims-Based Insights Into an Acquisition Research Shortlist

A shortlist holds up when every practice on it has passed the same tests. Most MSO deal teams can score candidates on clinical fit with the platform’s procedure mix, scale and direction of volume, proximity to existing sites, physician depth and concentration, and visible complications such as hospital affiliations or recent ownership changes.

Weighting those factors explicitly keeps the list consistent as it grows and makes the reasoning behind each ranking easy to defend in front of an investment committee.

Regulatory exposure belongs in the scoring too. The Milbank brief reported that 10 states required prior notice of transactions involving provider organizations as of its April 2025 publication, with Oregon also requiring prior approval.

Oregon’s Health Care Market Oversight program reported that it attached conditions to 13 of the 36 transactions it had approved through 2025, and that California expanded its notice requirement in 2025 to cover private equity firms and management services organizations. Federal scrutiny of serial acquisitions is real as well.

The FTC’s 2023 complaint against U.S. Anesthesia Partners alleged that the group bought more than a dozen Texas anesthesiology practices and moved each acquired group to its own higher rates.

An MSO planning to concentrate in one market should know its likely share of procedure volume before outreach begins, and claims-based market sizing supplies that number early.

The finished shortlist is a ranked set of practices worth contacting, each with the reason it ranked where it did. From there, the list hands off to outreach and then to the financial and legal diligence where the deal is actually decided.

How Alpha Sophia Helps MSOs Research Healthcare Practices With Claims Data

Alpha Sophia is a healthcare commercial intelligence platform built on all-payor US medical claims spanning Medicare, Medicaid, and commercial payors, covering more than 3.9 million providers.

For an MSO, it serves as the healthcare market intelligence layer that sits ahead of diligence.

The deal team uses it to define markets, find and rank candidate practices, and understand the physicians inside them. Valuation, deal structure, and the decision to proceed stay with the MSO and its advisors.

Procedure and Diagnosis Filters Turn an Investment Thesis Into a Query

Deal teams can filter providers by CPT® and HCPCS codes, ICD-10 diagnosis codes and CCSR categories, taxonomy, affiliations, and location, then rank the results by procedure volume.

A gastroenterology platform can pull every physician billing the colonoscopy codes in its thesis within its target states, review their volumes, and see the organizations and sites of care they are affiliated with.

Because the data is all-payor, practices with heavy commercial volume appear much closer to their real scale than they do in public Medicare files.

Provider profiles bring together specialty and taxonomy, affiliations, Open Payments, publications, and clinical trial activity, which supports the physician-level review described above without a separate research project for each candidate.

Territory Manager and Cohort Analysis Answer the Density Question

Alpha Sophia’s Territory Manager lets teams draw and redefine geographic boundaries, run heat map analysis, view opportunity size alongside the boundaries they set, and measure driving distance in miles. That maps directly onto the density question at the center of most MSO growth strategy.

A team can see how candidate practices cluster around existing sites and how much procedure volume sits within a realistic drive of each location.

Cohort analysis then lets the team compare groups of providers, such as independent physicians in two candidate metros, and review trend data across them before deciding where to concentrate outreach.

Shortlists Move Into the Tools the Deal Team Already Uses

Results export to Excel or CSV, sync natively with HubSpot, and are available through Alpha Sophia’s Provider API for teams that want the data inside their own systems.

Teams that work in AI tools can query the same data through the in-app Alpha Sophia Assistant or connect Claude, ChatGPT, or Cursor through the Model Context Protocol and ask in plain English for a ranked list of high-volume orthopedic surgeons performing total knee replacement near a target metro.

Autonomous workflows can then carry that list into the CRM and documents the deal team already maintains.

Conclusion

Healthcare practice acquisitions reward the MSOs that see a market first. Claims data gives a deal team that view by showing which practices already perform the work a platform is built on, where they operate, how their volume is moving, and which physicians carry it.

It shortens the distance between a clinical thesis and a ranked list of practices worth calling, and it covers practices that would never appear in a broker’s book.

Its limits matter just as much. Claims cannot value a practice, read its contracts, or predict whether its physicians will stay after close. The strongest MSO acquisition strategy treats claims-based research as the front end of the process and lets diligence test every assumption the data suggests.

Teams that want to see that front end applied to their own specialty and markets can book a demo with Alpha Sophia.

FAQs

What is an MSO acquisition target?

An MSO acquisition target is a physician practice that a management services organization plans to acquire or bring into its network. In states with corporate practice of medicine laws, the MSO typically acquires the practice’s non-clinical assets and signs a management services agreement while licensed physicians keep ownership of the clinical entity. The exact structure varies by state and should be set with legal counsel.

How can MSOs use claims data to identify acquisition targets?
MSOs filter claims by procedure codes, diagnosis codes, specialty, and geography to find physicians whose clinical activity matches their platform, then roll those physicians up to the practices that bill for their services. Ranking those practices by volume, growth, location, and physician depth produces a shortlist for outreach, often before a practice is formally marketed.

What can healthcare claims data reveal about physician practices?
Claims data shows which procedures a practice performs, how often, for which diagnoses, at which sites of care, and how those patterns change over time. It also shows how many physicians bill under a practice and how procedure volume is distributed among them.

Can claims data determine whether a practice is a good acquisition target?
Not on its own. Claims data shows whether a practice fits clinically and geographically, but it cannot show profitability, payer contract terms, compliance history, or whether physicians will stay after a sale. It narrows the field, while financial, legal, and operational diligence decide the deal.

What other data should MSOs consider when evaluating practices?
Financial statements, payer contracts, coding and compliance audits, physician employment and non-compete terms, leases, and billing and EHR systems all belong in diligence. MSOs should also review state transaction notice rules and antitrust exposure in markets where they already hold significant share.

How does Alpha Sophia help MSOs research potential acquisition targets?
Alpha Sophia provides all-payor claims data across more than 3.9 million providers, with filters for procedures, diagnoses, specialty, location, and affiliations. MSO teams can rank practices by volume, map density with Territory Manager, compare markets with cohort analysis, and move shortlists into their own workflows through export, HubSpot, the Provider API, or connected AI tools.