Medical and Dental Office Demand: Provider and Payor Data

Medical office demand analysis, as usually published, is a genre of reassurance: the asset is defensive, the tenants renew, the demographics help. All of it may be true and none of it is checkable, which makes it the wrong foundation for a credit file. This article builds the checkable version from the two data families its manifest title names. The provider side: the federal censuses that count physician and dentist offices, their payrolls and their growth, and the registries that locate every practitioner at an address. The payor side: the insurance-coverage tables that say who in a catchment can pay for care and through what channel, at exactly the age structure that decides utilization. Together they replace the genre's adjectives with a demand machine a lender can inspect part by part, and nothing in what follows quotes an occupancy rate, an absorption figure or anyone's outlook. The genre's figures are also, without exception, someone else's aggregation of markets the reader's deal is not in; the method's figures are the reader's catchment, from files that publish for it directly.

The offices, censused and growing

County Business Patterns counts 204,617 offices of physicians with paid employees in 2023, employing 2,706,297 people, and 135,665 offices of dentists employing 1,028,889 (U.S. Census Bureau, County Business Patterns 2023, NAICS 621111 and 621210, 2025). The size structures differ instructively: 52.7% of physician offices have fewer than five employees against 37.7% of dental offices, because dentistry's operatory model needs a minimum crew while a solo physician practice can run lean. The employment-insurance series adds the arc: physicians' offices grew from 204,988 reporting units in 2019 to 224,051 in 2024, up 9.3%, with employment up 9.9% to 2,871,838 and average pay up 18.4% to $111,440; dentists' offices grew 3.1% to 136,040 units with employment up 6.9% and average pay up 23.6% to $65,547 (BLS, QCEW annual averages, NAICS 621111 and 621210, 2020 and 2025). Set those payroll lines beside the series' other chapters and the defensive reputation acquires its measured form: through the same five years in which hotel employment fell 7% and skilled nursing shrank, the outpatient office sector added establishments, staff and pay without a visible cycle, which is what need-based demand looks like in a payroll census, and which no narrative needed to assert once the two rows were printed side by side.

What an office is not: the site-against-provider trap

Before the density maps, the trap that invalidates half the casual analyses in this asset class. The establishment censuses count practice sites with payroll, not clinicians, and the two diverge wherever health systems employ physicians directly, because a doctor on a hospital's payroll practices at a site the office code never sees. The state figures make the trap visible: physician-office density runs from 87.2 per 100,000 residents in Florida down to 26.0 in Minnesota and 21.1 in North Dakota (MMCG computation from CBP 2023 and Vintage 2025 populations), and no one believes the upper Midwest has a third of Florida's doctors. What it has is consolidated systems, physicians practicing inside hospital-coded entities, so its outpatient care runs through fewer, larger, differently coded sites. The provider-grain correction is public: the National Plan and Provider Enumeration System registers every practitioner with practice addresses, keyless and current, and the Area Health Resources Files aggregate providers per county from more than 60 sources (CMS NPPES, 2026; HRSA AHRF, 2024 release of 29 January 2026). The method rule for this asset class, unique in the series, is that the establishment census supplies the real estate layer, the sites, while the registries supply the demand layer, the providers, and a market where the two diverge is telling the analyst its delivery structure, not lying to either instrument. The divergence is itself a leasing variable: system-employed markets fill campus and system-owned buildings, independent-practice markets fill the multi-tenant stock this asset class mostly means, and the ratio of registry clinicians to census office employment is a one-line proxy for which kind of market a catchment is.

The payor structure: who can pay, at which ages

Health care demand is insurance-mediated, and the coverage table is therefore the payor half of the model. From the 2024 ACS: of 335,190,522 civilian noninstitutionalized Americans, the uninsured share runs 6.0% under 19, peaks at 14.1% among 19-to-34-year-olds, eases to 9.7% at 35 to 64, and collapses to 0.8% at 65 and over, where Medicare is effectively universal (MMCG computation from ACS 2024 1-year table B27010, 2025). The age gradient is the asset class's quiet engine: the cohort whose coverage is universal is the cohort whose utilization is highest and whose numbers are compounding, 65-and-over up 16.2% since 2020 and the 75-to-79 band up 29.6%, per the cohort arithmetic worked in this series' senior housing article. A medical office catchment therefore has two payor-relevant gradients the same tables publish to the tract: the age mix, which sets utilization and the Medicare share, and the working-age uninsured rate, which caps commercial demand and predicts the payer mix every practice manager already knows. Dentistry inverts part of the logic, which is why it gets its own section below.

The two engines, joined

Provider and payor multiply rather than add, and the joined arithmetic is the model. A catchment's outpatient demand scales with covered utilization, age-weighted people times coverage; its captured demand depends on the roster available to serve it; and the gap between the two, covered demand per clinician, is the single ratio that ranks catchments for a new clinical building better than any density map alone. Both terms are local, both are public, and the ratio's two failure modes are instructive: a high ratio from a thin roster is an under-served market if clinicians can be recruited and a stranded one if they cannot, which is the health-sector version of the staffing gate this series measured in senior housing and childcare, read here from the registry's own trend instead of from payrolls.

Two maps, two markets

The physician-office map, read with the site-against-provider caution, still carries real information. Florida's 87.2 offices per 100,000 residents against the national 60.2 reflects both its senior-heavy, utilization-heavy population and a delivery culture of independent practices; Nevada at 78.5, New Jersey at 78.1 and California at 75.6 follow; the bottom of the map, the Dakotas, Minnesota and Iowa, marks system-employed medicine, not scarcity (MMCG computation from CBP 2023 state file and Vintage 2025 populations, 2025 to 2026). The dental map runs on different rails: a national 39.9 offices per 100,000, California at 58.1 leading with Utah, Colorado, New Jersey and Idaho above 47, and the Deep South and West Virginia in the twenties. Dental delivery never consolidated into hospital systems, so its office map tracks its provider map far more faithfully, and its state spread reads as the real geography of dental supply in a way the physician map does not. For any specific catchment, both maps are context; the county AHRF variables and an NPPES pull are the measurement.

One reading habit for both maps: divide before comparing. Office density mixes practice scale into every figure, so a state of large group practices shows fewer, bigger sites at identical provider supply; the companion ratio, employees per office (13.2 nationally for physicians' offices against 7.6 for dentists'), separates the scale effect from the supply effect, and the pair together read a state's delivery structure the way the size classes read an industry's format everywhere else in this series.

The federal shortage layer: designated, not inferred

Where this series' other asset classes compute their shortage maps, health care's carries an official one. The Health Resources and Services Administration designates Health Professional Shortage Areas for primary care, dental care and mental health, by geography, population group and facility, with scores, and publishes the designations as data anyone can query; the same agency's shortage machinery drives federal placement and payment programs, which makes a designation a fact with money attached rather than an advocacy statistic. For the demand analyst the HPSA layer does two jobs. As a screen, a catchment inside or beside a primary-care or dental HPSA has a federally attested demand gap, scored, dated and citable in one line. As a caution, the designation reflects providers per population under federal rules, not commercial viability, and a shortage of providers who could be paid is not automatically a market for a building that must be; the payor profile decides that second question, which is why this article carries both layers rather than either alone.

Dental's different market

Dentistry deserves its separate paragraph because its economics answer to a different payor logic. Dental coverage is not health coverage: Medicare's core program historically excludes routine dental care, so the 65-and-over cohort that anchors medical demand arrives at the dentist with a benefits cliff, and dental demand tracks commercial coverage and household cash flow more than any other health segment. The consequences show in the series this article has already cited: dental office counts grew a modest 3.1% over five years against 9.3% for physicians, while dental pay grew faster, 23.6%, off a lower base, a sector expanding carefully in a payor environment it cannot take for granted. For a dental-anchored property the demand model therefore weights the working-age insured share and the income tables more heavily, and the age gradient less, than the identical analysis next door for a medical tenant, one more case of this series' standing lesson that the demand unit, not the building, defines the asset class. The federal shortage layer runs parallel here too: dental HPSAs are designated separately from primary care, and the dental map's honest low end, the twenties per 100,000 across several Southern states, generally coincides with broad dental-shortage designations, two instruments agreeing about the same gap from different directions.

The senior linkage, quantified

The demographic engine driving outpatient demand is the one this series has already measured to the single year of age: 64.6 million Americans 65 and over, up 16.2% since 2020, with the 75-and-over band up 23.0% and its leading edge growing fastest. Against that denominator the office sector's growth, 9.3% more physician-office sites and 9.9% more employment in five years, reads as expansion trailing its driver, which is the structural claim behind every defensive-asset narrative, here stated from two public series instead of asserted. The linkage sharpens at catchment grain: the same single-year county files that locate senior-housing demand locate outpatient demand, because the 75-and-over stock that fills assisted living fills waiting rooms first, and a medical office analysis that borrows the senior article's cohort table wholesale has borrowed correctly. What this article adds to that table is the payor overlay, near-universal coverage in exactly the compounding cohort, and the provider overlay, where the registries say the clinicians to serve it actually practice.

The advanced-practice shift, visible in the registry

The clinician mix inside the offices is changing faster than the office counts, and the registry sees it where the establishment census cannot. Nurse practitioners and physician assistants now carry a large and growing share of primary care visits, each registered in NPPES under their own taxonomies at their practice addresses, so a catchment's true clinical capacity is the full roster, not the physician count, and two catchments with identical physician density can differ by half in advanced-practice depth. The space consequence runs through program design: team-based primary care uses more exam rooms per physician and more shared clinical support space, which is part of why outpatient employment grew 9.9% against 9.3% site growth, staffing densifying inside the walls. For the analyst the instruction is mechanical: pull the catchment roster by taxonomy group, physicians, advanced practice, dental, behavioral, and report capacity in clinicians rather than in doctors, because the demand walks in the door for whoever can see it.

The building itself: what clinical grade means in public records

The site inventory sharpens once the parcel and permit records are read for clinical signatures. Purpose-built medical space leaves traces no listing needs to disclose: construction-era permits for medical gas, emergency power and imaging shielding; parking ratios sized to patient turnover rather than office headcounts; single-story or elevator-served layouts with door and corridor dimensions accessibility codes fixed long ago; and assessor use codes that most counties assign to clinical buildings specifically. The converted house on the hospital's approach road licenses the same practice but carries none of the signatures, and the difference prices differently at every re-tenanting, because clinical-grade space re-lets to the next practice while converted space competes with every small office in town. An inventory column for clinical signatures, filled from permits and the roll in an afternoon, is the supply-quality layer this asset class usually asserts from finishes; here it comes from filings.

The anchor economics, mapped from public lists

Outpatient real estate organizes around anchors whose locations are entirely public: every hospital in the CMS provider files with its address and system ownership, every campus expansion in the permit record before it opens. The anchor map does three jobs in the demand file. It states the referral geography, because practices cluster on the approach corridors and campus perimeters where their admitting and imaging relationships live, and a building's position on or off those corridors is a fact a map states without an interview. It flags the system-competition dynamic the density maps already hinted at: a market whose anchor system employs its physicians fills campus buildings first, and the independent-practice demand that multi-tenant buildings live on is thinner than the raw provider count implies. And it dates supply risk, because the system's own outpatient pavilion, visible in permits quarters ahead, is the one competitor that arrives with its tenancy pre-committed. None of this requires proprietary data; it requires reading three public lists against one map.

Reading a catchment at provider grain

The catchment method assembles four public layers, each finer than anything in the genre's market reports. The demand base: population by age band and the two payor gradients from the ACS, at tract grain per the trade-area method. The provider stock: an NPPES pull for the catchment's ZIP codes, by taxonomy, deduplicated to practice addresses, which yields the working roster of physicians, dentists and the advanced-practice clinicians who increasingly carry primary care; the AHRF county variables benchmark the roster against peers. The site stock: the establishment censuses and the County Business Patterns method for the employer layer, joined to the assessor roll for the buildings themselves, where the parcel record distinguishes the purpose-built clinical building from the converted house that licenses the same practice. And the anchor structure: outpatient care clusters around hospitals and health-system campuses whose locations are public, and a catchment's position relative to those anchors, on the referral paths rather than off them, is readable from a map once the anchors are named. The output is a provider-to-population ratio by specialty group, a payor profile, and a site inventory, all sourced, which is the demand half of any medical office underwriting stated in checkable parts. As arithmetic, the joined ratio from the earlier section closes the file: covered, age-weighted population over rostered clinicians, computed for the catchment and for two or three peer catchments from the same files, so the subject market's position is stated relatively as well as absolutely, and the peer set is chosen by the analyst in daylight rather than by a vendor's market definition.

The telehealth boundary, stated without a forecast

Every medical office analysis since 2020 owes the reader one honest paragraph on virtual care, and the honest version is short. Telehealth moved a share of visits out of rooms, concentrated in behavioral care and routine follow-up; procedures, diagnostics, dentistry and anything involving hands stayed physical; and the durable division of labor between screen and room is still settling. The public evidence for any strong quantitative claim is thinner than the claims usually made from it, so this article makes none; what it notes instead is where the boundary lands hardest, which is the behavioral segment whose facility demand the behavioral health article reads from federal facility censuses. For the space model the practical translation is program-level, not market-level: exam-room counts per clinician have drifted down in new layouts, and the parcel and permit records show which local buildings were designed for the new program and which await conversion, a supply-quality distinction no vacancy statistic captures. The behavioral case also illustrates the general rule for reading virtual care in a demand file: state the affected visit types, check whether the catchment's roster in those taxonomies is growing or shrinking in the registry, and let the building's program answer the question the national statistics cannot, which is whether this space serves the visits that stayed physical.

The tier below payroll

As everywhere in this series, the employer census has a floor beneath it. The solo practitioner with no staff, common in behavioral care, in part-time and late-career practice and in cash-pay niches, files as a nonemployer and appears in the Nonemployer Statistics rather than in any establishment count (U.S. Census Bureau, Nonemployer Statistics 2023, 2025), while still occupying real suites in real buildings. The NPPES roster catches these clinicians where the censuses cannot, one more reason the registry anchors the demand layer, and the reconciliation of roster against establishment counts measures the tier's local size: a catchment whose registered clinicians far exceed its census-visible office employment is a market of small suites and short leases, with the tenancy risk and the resilience that structure implies.

Two payor caveats that keep the table honest

The coverage table earns two disciplines in use. Coverage types overlap, one person can carry Medicare and a supplement, employer coverage and Medicaid in a year, so the clean local statistics are the uninsured share and the broad program mix, not a false precision of exclusive categories. And the Medicaid layer is state policy: eligibility rules and reimbursement levels differ across state lines in ways that change what a covered patient is worth to a practice, so two counties with identical coverage tables on opposite sides of a state border can support different clinical economics. The memo handles both the same way, by stating shares from the table and naming the state programs behind them, letting policy risk sit in its own labeled line rather than dissolving into the demographics.

A third habit costs one sentence in the memo and pays repeatedly: date the coverage table to its survey year and note that coverage composition moves with law, not with markets. The uninsured gradient this article reports is 2024's; the gradient a workout committee reads in 2029 will be whatever the intervening policy made it, and the file that stated its vintage plainly ages into a record instead of an embarrassment.

What the lender reads

Medical and dental offices are the archetypal small-balance owner-occupied credit: a practice buying its building, an SBA structure, a loan whose repayment rides the practice more than the parcel. The demand file this article builds is therefore also a practice-durability file: a provider roster that shows whether the catchment is gaining or losing clinicians, a payor profile that prices the revenue's stability, an age structure that projects utilization, and a site inventory that says what competes. The public SBA 7(a) and 504 datasets, which MMCG Analytics' SBA layer is built on, carry decades of physician and dentist office lending, among the deepest cohorts in the register, subject to the standing rule that no performance rate is shown for any cohort of fewer than ten loans; the small-balance performance article reads that record by property type. MMCG Analytics supplies the data and the analysis; the credit decision rests with the lender.

The same file serves the investor case with one reweighting. Where the owner-occupier loan rides a single practice, the multi-tenant building rides the catchment's practice formation and mobility, so the investor's version of the roster pull is longitudinal: the count of new NPIs at addresses in the polygon over the past three years, the practices that moved in and out, the taxonomy mix shifting toward or away from the building's program. The registry's monthly cadence makes that churn measurable in a way no other asset class in this series can match, and a multi-tenant medical building whose catchment shows steady NPI formation has a leasing thesis written by a federal database.

Method: the five numbers a medical office memo should carry

First, the age engine: the catchment's 65-and-over and 75-and-over stocks and five-year trends from the county single-year files. Second, the payor profile: uninsured shares by age band and the implied Medicare, commercial and gap structure from B27010 at tract grain. Third, the provider roster: NPPES counts by taxonomy at practice addresses in the catchment, benchmarked per 1,000 residents against the AHRF county variables. Fourth, the site inventory: establishment counts joined to parcels, with clinical-grade buildings distinguished from converted stock. Fifth, the anchor map: the hospital and system campuses whose referral geography the site lives in, named and mapped. Each carries a source and a date; the tenant's own volumes and payer mix are the operator's disclosure, not the analyst's estimate; and the provenance standard draws the line, as it does across the whole pillar.

A worked sequence for one building

Run for a 14,000-square-foot multi-tenant medical building a mile from a regional hospital, the sequence goes as follows. The county single-year file puts 11,900 residents 65 and over in the drive-time polygon, up 21% in five years, 4,800 of them 75 and over. B27010 for the tracts shows 4% uninsured at 65-plus rounding to the universal, 11% at working ages, a commercial base consistent with the county's employer mix. The NPPES pull returns 74 physicians and 31 dentists at addresses inside the polygon; against population, the physician figure sits 15% below the AHRF benchmark for peer counties, a supply gap with names and suites attached. The parcel join finds nine clinical-grade buildings, one under construction by the hospital system itself, which the anchor map places on the campus's main approach. The memo that results states: an age engine above trend, a payor profile stable by construction, a measured provider shortfall, and a supply pipeline of one known project, with the subject building's position on the referral path stated from the map. Whether the practice tenants' volumes justify their rents is then their disclosure against a demand base the file has already proven, and the whole exercise consumed one afternoon and no budget.

The protective reading runs the same pull the other way: a catchment whose NPPES roster has thinned for three consecutive years is exporting its demand to wherever those clinicians went, and no amount of favorable demography rescues a building the referral paths have rerouted around.

A dental variant of the sequence reweights rather than rewrites: the same polygon, the roster filtered to dental taxonomies, the payor line led by working-age commercial coverage and median income, the HPSA check against the dental designations, and the anchor map replaced by the retail-visibility logic dental practices actually site on. Ten of the twelve inputs are the same files, which is the point of building the method once: asset variants become parameter changes, not new projects.

The 2026 read, and the cadence

Read in August 2026, the provider-and-payor picture is the least dramatic in this series, which is its content: office counts and payrolls compounding mid-single digits through every disruption the half-decade offered, coverage structure stable with its senior anchor strengthening, and the delivery-structure shift toward systems visible in the maps rather than hidden. The cadence is generous: NPPES updates monthly, the QCEW quarterly, the coverage tables and censuses annually, the AHRF each winter, and every one of them is free. A medical office position reviewed on that calendar is watched by the same instruments that justified it, and the genre's adjectives, defensive, durable, needs-based, turn out to be things a lender can simply count. The genre will keep publishing its trackers and outlooks, and a reader who has built this file can meet them the right way, checking any claim that matters against the registry, the coverage table and the censuses, and letting the rest pass as weather.

Frequently asked questions

What public data measures medical office demand?

Provider and payor layers: the NPPES registry locates every practitioner at practice addresses (monthly, keyless), the HRSA Area Health Resources Files benchmark providers per county, ACS table B27010 gives insurance coverage by age to the tract, and the establishment censuses (County Business Patterns, QCEW) count office sites and payrolls.

How many medical and dental offices are there?

County Business Patterns counts 204,617 physician offices (2.7 million employees) and 135,665 dental offices (1.0 million) for 2023. On the QCEW basis, physician offices grew 9.3% from 2019 to 2024 and dental offices 3.1%, with pay up 18.4% and 23.6% respectively.

Why do office counts understate doctors in some states?

The censuses count practice sites with payroll, not clinicians; where health systems employ physicians, doctors practice at hospital-coded sites the office code never sees. Physician-office density runs from 87.2 per 100,000 in Florida to 21.1 in North Dakota, a spread that maps delivery structure, not physician supply; the NPPES registry corrects to provider grain.

What does insurance coverage add to the analysis?

The payor structure: uninsured shares in 2024 ran 6.0% under 19, 14.1% at 19 to 34, 9.7% at 35 to 64 and 0.8% at 65 and over. The compounding senior cohort is effectively universally covered, which stabilizes medical demand; dental demand, facing Medicare's routine-care exclusion, tracks commercial coverage and income instead.

How is dental office demand different?

Dental coverage is separate from health coverage and thinner at older ages, so dental demand weights working-age insured shares and household income where medical demand weights the age engine. The sector's own series match the logic: office counts up a careful 3.1% in five years against 9.3% for physicians.

Is medical office really a defensive asset class?

The payroll record supports the reputation without adjectives: physician-office employment grew 9.9% from 2019 to 2024, through a period when hotel employment fell 7% and skilled-nursing employment shrank, and the 65-and-over demand base grew 16.2% with near-universal coverage. Whether a specific building shares that stability depends on its providers, payors and referral position, all checkable.

Sources

1. U.S. Census Bureau, County Business Patterns 2023, national and state files, NAICS 621111 and 621210, released 26 June 2025. https://www2.census.gov/programs-surveys/cbp/datasets/2023/
2. U.S. Bureau of Labor Statistics, Quarterly Census of Employment and Wages, annual averages 2019 and 2024, NAICS 621111 and 621210, private, United States, 2020 and 2025. https://data.bls.gov/cew/data/api/2024/a/industry/621111.csv
3. U.S. Census Bureau, American Community Survey 2024 1-year estimates, table B27010, types of health insurance coverage by age, released 11 September 2025; uninsured shares computed by MMCG. https://www2.census.gov/programs-surveys/acs/summary_file/2024/table-based-SF/data/1YRData/acsdt1y2024-b27010.dat
4. Centers for Medicare and Medicaid Services, National Plan and Provider Enumeration System, NPI registry and public API (provider practice addresses, monthly), 2026. https://npiregistry.cms.hhs.gov/
5. Health Resources and Services Administration, Area Health Resources Files, 2024 release (29 January 2026): county, state and national provider variables from more than 60 sources. https://data.hrsa.gov/topics/health-workforce/ahrf
6. U.S. Census Bureau, Vintage 2025 Population Estimates (65-and-over and band growth; state population denominators), 2026. https://www.census.gov/newsroom/press-releases/2026/vintage-2025-pop-estimates.html
7. MMCG computation: state office densities per 100,000 residents from County Business Patterns 2023 state files and Vintage 2025 July 2023 populations, 2026 (method in text). https://www2.census.gov/programs-surveys/popest/datasets/2020-2025/state/totals/NST-EST2025-ALLDATA.csv
8. 504 Capital Corporation, SBA 504 Loans for Special Purpose Properties and Real Estate (guidance on SOP 50 10 8 classifications), 2025. https://504capital.com/blog/financing-special-purpose-properties-sba-504-loans/
9. National Association of Government Guaranteed Lenders, SBA Notice Revising SOP 50 10 8 (Procedural Notice 5000-872764), 2025. https://www.naggl.org/sba-notice-revising-sop-50-10-8/
10. MMCG Research, SBA 7(a) Performance Series: MMCG analysis of the public SBA 7(a) loan register, 2026. https://mmcganalytics.com/sba-default-rates/
11. U.S. Census Bureau, Nonemployer Statistics 2023 (solo practices without payroll), released 15 May 2025. https://www.census.gov/newsroom/press-releases/2025/2023-nonemployer-statistics.html
12. Health Resources and Services Administration, Health Professional Shortage Area designations (primary care, dental and mental health; scored designations, public data query), current designations, 2026. https://data.hrsa.gov/topics/health-workforce/shortage-areas