Quick reference: U.S. credentialing authorities

How federal and state authorities interact

The CMS National Plan and Provider Enumeration System assigns a single 10-digit National Provider Identifier that follows a clinician across state moves and employer changes. The NPI is necessary for every Medicare and Medicaid claim, but it does not, by itself, confirm that the provider currently holds an active state license, that authorization is delegated to each state medical board under the Tenth Amendment. Browse PlainDoctor by state to see how providers register practice locations.

Why specialty board certification matters

Board certification by an American Board of Medical Specialties member board signals voluntary post-licensure examination and ongoing Maintenance of Certification cycles. It is not legally required to practice medicine, but health plans, hospital credentialing committees, and patients increasingly use it as a quality signal. View specialty-level data through PlainDoctor specialty pages showing certification rates by jurisdiction.

Reading disciplinary records responsibly

State medical board orders are public legal documents that describe the factual findings, conclusions of law, and disciplinary action taken. A single malpractice payment does not necessarily indicate poor practice, high-risk specialties (neurosurgery, obstetrics) have higher baseline payment rates than primary care. Patterns of multiple actions, license restrictions, or revocations are the meaningful signals to weigh. Read the PlainDoctor methodology for how disciplinary data integrates into provider profiles.

What Is Medicare Part B Claims Data?

Medicare Part B is the component of traditional Medicare that covers outpatient services, physician visits, diagnostic tests, and durable medical equipment. When a provider treats a Medicare patient and submits a claim, that claim becomes part of a massive dataset maintained by the Centers for Medicare & Medicaid Services.

Each year, CMS aggregates and de-identifies this claims data and publishes it as the Medicare Physician & Other Practitioners (PUF) dataset. The dataset groups claims by provider NPI and procedure code, showing how many Medicare beneficiaries a provider treated, how many times they billed each procedure code (HCPCS/CPT code), and how much Medicare paid. As of the most recent release, the dataset covers over 1 million individual providers and 10,000+ procedure codes.

PlainDoctor incorporates this data into provider profiles. Use the provider search to find any doctor and view their Medicare utilization summary alongside their NPI record, specialty, and practice location.

How to Read the Data: Key Fields Explained

The Medicare claims dataset contains a number of fields that may look intimidating at first. Here is what each one means in practical terms:

What High Volume Actually Means

One of the most striking things in the Medicare data is the enormous range in procedure volumes. Some providers bill the same procedure code hundreds or even thousands of times per year. Before drawing any conclusions, understand what volume can and cannot tell you.

High volume may indicate expertise. Surgeons who perform a procedure frequently tend to have better outcomes, this is one of the best-documented findings in surgical outcomes research. A cardiologist who implants 200 stents per year has more practice than one who implants 15. For complex elective procedures, seeking a high-volume provider at a high-volume hospital is a legitimate evidence-based strategy.

High volume may also indicate overutilization. Certain procedure codes have historically been flagged by CMS as prone to over-billing, spinal injections, certain imaging studies, skin lesion removals. A provider billing these codes at rates far above their peers may warrant more scrutiny. CMS publishes annual lists of procedure codes under review for this reason.

Context is essential. A high-volume spine surgeon at an academic medical center in a major city is very different from a solo practitioner in a rural area billing the same volume. Specialty, practice setting, patient demographics, and referral patterns all affect volume independently of quality. Always compare within specialty and geography.

Understanding Procedure Mix and Practice Patterns

The procedure mix, which CPT codes a provider bills most often, tells you what they actually do in practice. This can be surprisingly revealing. A physician listed as a primary care doctor who predominantly bills high-complexity evaluation and management codes (99215) plus multiple diagnostic procedures may be running a high-churn practice model very different from a physician billing predominantly preventive care codes.

Here are some specific patterns worth noting when reviewing a provider's claims data:

• Evaluation & Management (E&M) code distribution: Medicare pays different rates for office visits based on complexity (99202–99215). Providers who almost exclusively bill the highest-complexity codes are either seeing unusually sick patients or may be upcoding. A mix across complexity levels is normal.
• Procedure-to-visit ratio: Specialists who perform procedures should have a reasonable ratio of procedures to office visits. An interventional cardiologist who bills almost exclusively office visits but very few catheterizations may have limited procedural experience.
• Telehealth codes: Since 2020, telehealth claims have become visible in Medicare data. Providers with high telehealth utilization may offer more access but less in-person care.
• Ancillary services: Some practices own diagnostic equipment (imaging, lab) and bill for services performed in-office. High volumes of these ancillary codes can reflect either a well-equipped practice or a concern about self-referral incentives.

Medicare Spending Variation: What the Numbers Show

One of the landmark uses of Medicare data was the Dartmouth Atlas, which documented massive geographic variation in Medicare spending, with little corresponding difference in outcomes. Some regions spend twice as much per Medicare beneficiary as others, even after adjusting for age and illness burden.

This variation exists at the provider level too. Two cardiologists treating similar patients may generate dramatically different Medicare spending based on their practice style, how aggressively they test, how quickly they refer for procedures, how often they hospitalize patients. Neither pattern is automatically better; the evidence on appropriate utilization in many areas remains contested.

When reviewing a provider's Medicare payment totals, compare them to peers in the same specialty and ZIP code region. Browse providers by specialty or state to see how an individual provider's metrics stack up against their local peers.

Part D Prescribing Data: Prescription Patterns

In addition to Part B claims, CMS also publishes Medicare Part D prescribing data, showing which drugs providers prescribed to Medicare patients and in what volumes. This data can be equally informative:

Brand vs. generic rates: Providers who prescribe brand-name drugs when generics are available at a fraction of the cost may be influenced by pharmaceutical marketing rather than clinical guidelines. High brand-name prescribing rates relative to peers in the same specialty are worth noting.

Controlled substance prescribing: CMS publishes opioid prescribing rates at the provider level. Providers whose opioid prescribing rates far exceed their specialty peers in the same geography represent elevated risk. Some states have used this data to trigger prescribing reviews and investigations.

Specialty consistency: A dermatologist prescribing large volumes of antidepressants, or a primary care doctor prescribing large volumes of chemotherapy agents, is a pattern inconsistent with typical specialty practice and worth investigating. These anomalies can indicate scope-of-practice concerns or specialty billing fraud.

What Medicare Claims Data Cannot Tell You

Medicare data is powerful but has real limitations that users must understand:

• No outcomes data: Claims data shows what was done, not whether it worked. A surgeon with 500 procedures may have excellent outcomes or terrible ones, claims data alone cannot distinguish them.
• Medicare only: The data covers only the roughly 65+ population on traditional (fee-for-service) Medicare. Providers who primarily see younger patients or Medicare Advantage enrollees will appear to have low volume even if they are extremely active practitioners.
• No patient context: A provider seeing the sickest patients in a region will naturally have different billing patterns than one seeing healthy patients for routine care. Case mix adjustment is critical and not always available in public data.
• Lag time: CMS publishes claims data with a 1–2 year lag. The 2023 dataset reflects 2023 practice patterns, which may not reflect current staffing, procedures offered, or quality metrics.
• Aggregation suppression: CMS suppresses data for providers with fewer than 11 beneficiaries for a given service to protect patient privacy. Lower-volume providers may have incomplete profiles as a result.

For a complete picture, combine Medicare claims data with credential and license verification, hospital quality scores (available from CMS Hospital Compare), patient experience surveys (CAHPS), and peer-reviewed outcomes data for specific procedures.

Open Payments: Following the Money

One more dataset deserves mention alongside Medicare claims data: the CMS Open Payments program. Under the Physician Payments Sunshine Act, pharmaceutical and medical device companies must report all transfers of value to physicians and teaching hospitals. This includes speaking fees, consulting contracts, research payments, meals, travel, and royalties.

Open Payments data is searchable at openpaymentsdata.cms.gov. When reviewing a provider's prescribing patterns or procedure preferences in Medicare data, cross-referencing Open Payments can reveal whether those patterns align with significant financial relationships with the companies whose products they favor.

Financial relationships are not automatically disqualifying, many are legitimate. But a provider receiving substantial consulting fees from a device company and implanting that company's devices at above-average rates is a pattern worth understanding. Browse PlainDoctor's specialty directory to find and compare providers in any area. You can also explore nursing home quality ratings for facility-level CMS data including staffing, health inspections, and quality measures.

Frequently Asked Questions

Using Medicare Data as Part of a Complete Provider Evaluation

Medicare claims data is most powerful when combined with other public information sources. Here is a practical checklist for evaluating a provider you are considering:

No single data source gives a complete picture of a provider's quality. Medicare claims data is a powerful starting point, but it measures what was done, not how well it was done. The goal is to combine multiple signals into a well-informed choice, not to replace the clinical judgment of a physician or the patient relationship built through direct care.

Frequently Asked Questions