Centers for Medicare & Medicaid Services - Nursing HomesThis feature layer, utilizing data from the Centers for Medicare & Medicaid Services (CMS), displays the locations of nursing homes in the U.S. Nursing homes provide a type of residential care. They are a place of residence for people who require constant nursing care and have significant deficiencies with activities of daily living. Per CMS, "Nursing homes, which include Skilled Nursing Facilities (SNFs) and Nursing Facilities (NFs), are required to be in compliance with Federal requirements to receive payment under the Medicare or Medicaid programs. The Secretary of the United States Department of Health & Human Services has delegated to the CMS and the State Medicaid Agency the authority to impose enforcement remedies against a nursing home that does not meet Federal requirements." This layer includes currently active nursing homes, including number of certified beds, address, and other information.Bridgepoint Sub-Acute and Rehab Capitol HillData downloaded: August 1, 2024Data source: Provider InformationData modification: This dataset includes only those facilities with addresses that were appropriately geocoded.For more information: Nursing homes including rehab servicesFor feedback, please contact: ArcGIScomNationalMaps@esri.comCenters for Medicare & Medicaid ServicesPer USA.gov, "The Centers for Medicare and Medicaid Services (CMS) provides health coverage to more than 100 million people through Medicare, Medicaid, the Children’s Health Insurance Program, and the Health Insurance Marketplace. The CMS seeks to strengthen and modernize the Nation’s health care system, to provide access to high quality care and improved health at lower costs."

The Share of Medicaid Enrollees in any Managed Care and in Comprehensive Managed CaAre profiles state-level enrollment statistics (numbers and percentages) of total Medicaid enrollees in any type of managed care as well as those enrolled specifically in comprehensive managed care programs. The report provides managed care enrollment by state with all 50 states, the District of Columbia and the US territories are represented in these data. Note: "n/a" indicates that a state or territory was not able to report data or does not have a managed care program. The “Total Medicaid Enrollees” column represents an unduplicated count of all beneficiaries in FFS and any type of managed care, including Medicaid-only and dually eligible individuals receiving full Medicaid benefits or Medicaid cost sharing. The “Total Medicaid Enrollment in Any Type of Managed Care” column represents an unduplicated count of beneficiaries enrolled in any Medicaid managed care program, including comprehensive MCOs, limited benefit MCOs, PCCMs, and PCCM entities. The “Medicaid Enrollment in Comprehensive Managed Care” column represents an unduplicated count of Medicaid beneficiaries enrolled in a managed care plan that provides comprehensive benefits (acute, primary care, specialty, and any other), as well as PACE programs. It excludes beneficiaries who are enrolled in a Financial Alignment Initiative Medicare-Medicaid Plan as their only form of managed care.

The dataset contains information about the prevalence of chronic conditions among Original Medicare beneficiaries as well as about the spending and co-occurring conditions for those with each condition. The data are available for California and for the rest of the United States, overall and by demographic and geographic groups. Additionally, the data are available for each of 19 California geographic regions overall and by demographic and geographic groups. The data represent Medicare beneficiaries who are in the Original Medicare program. Medicare offers health care coverage for older adults and certain individuals with disabilities. The Original Medicare program is Parts A and B of Medicare, administered by the U.S. Centers for Medicare & Medicaid Services. The analysis excludes enrollees of the Medicare Advantage program, administered by private insurers, because Medicare Advantage data are incomplete.

The MarketScan health claims database is a compilation of nearly 110 million patient records with information from more than 100 private insurance carriers and large self-insuring companies. Public forms of insurance (i.e., Medicare and Medicaid) are not included, nor are small (< 100 employees) or medium (1000 employees). We excluded the relatively few (n=6735) individuals over 65 years of age because Medicare is the primary insurance of U.S. adults over 65. The EQI was constructed for 2000-2005 for all US counties and is composed of five domains (air, water, built, land, and sociodemographic), each composed of variables to represent the environmental quality of that _domain. Domain-specific EQIs were developed using principal components analysis (PCA) to reduce these variables within each _domain while the overall EQI was constructed from a second PCA from these individual domains (L. C. Messer et al., 2014). To account for differences in environment across rural and urban counties, the overall and _domain-specific EQIs were stratified by rural urban continuum codes (RUCCs) (U.S. Department of Agriculture, 2015). This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Human health data are not available publicly. EQI data are available at: https://edg.epa.gov/data/Public/ORD/NHEERL/EQI. Format: Data are stored as csv files. This dataset is associated with the following publication: Gray, C., D. Lobdell, K. Rappazzo, Y. Jian, J. Jagai, L. Messer, A. Patel, S. Deflorio-Barker, C. Lyttle, J. Solway, and A. Rzhetsky. Associations between environmental quality and adult asthma prevalence in medical claims data. ENVIRONMENTAL RESEARCH. Elsevier B.V., Amsterdam, NETHERLANDS, 166: 529-536, (2018).

About this dataset:

-This data is a compilation of the CMS Medicare Part B National Summary Data for CPT/HCPCS Medicine Codes 90281-99xx for 2000-2022. - The information in Part B National Summary Data Files is limited to Medicare Fee-For- Service (FFS) Part B Physician/Supplier data. It does not include information on physician/supplier services for beneficiaries in the managed care portion of the program (Medicare Advantage). -Items/columns include: year, HCPCS/CPT, total annual allowed services, total annual allowed charges, and total annual allowed payment. - These are national annual aggregates. - Note that, per CMS, fields labeled “N/A” mean that the data cannot be disclosed due to Privacy rules. Cell sizes less than 11 have been screened for privacy and replaced with N/A. A zero indicates there were no services or payments rendered for a particular code. - The .csv and .xlsx files hold the same data, just in different formats. - CPT only copyright 2000-2022 American Medical Association. All rights reserved.

Column Descriptions:

Allowed Services: A count of the number of services performed for a procedure.

Allowed Charges: The amount Medicare determines to be reasonable payment for a provider or service covered under Part B. This includes the coinsurance and deductible amounts.

Description: The category corresponding to the HCPCS code, for example: Evaluation and Management, Anesthesia, Dental Services, Pathology/Lab Tests, Chemotherapy Drugs, Medicine, etc

HCPCS (Healthcare Common Procedure Coding System): The HCPCS is a coding system for all services performed by a physician or supplier. It is based on the American Medical Association Physicians Current Procedural Terminology (CPT) codes and is augmented with codes for physician and non-physician services (such as ambulance and durable medical equipment (DME), which are not included in CPTs.

Modifiers: Modifiers denote that a certain procedure/service has been altered by a particular circumstance, but not changed in its definition, therefore the same code is used and a modifier is added to denote what has been altered.

Payment: In the Original Medicare Plan, this is the amount a doctor or supplier that accepts assignment can be paid. It includes what Medicare pays and any deductible, coinsurance, or copayment that the beneficiary must pay. It may be less than the actual amount a doctor or supplier charges.

Additional details can be found in the Medicare Part B National Summary Data Read Me files: file:///C:/Users/sybil/AppData/Local/Temp/3dce003b-ea02-4b37-aaae-c4ef3e6f43a9_PartBNational2010.zip.3a9/PartBNationalSummaryReadmeFile2010.pdf

CMS Data Disclaimer

CMS has no responsibility for the data after it has been converted, processed or otherwise altered. Data that has been manipulated or reprocessed by the user is the responsibility of the user. The user may not present data that has been altered in any way as CMS data. Any alteration of the original data, including conversion to other media or other data formats, is the responsibility of the requestor. Cell sizes less than 11 have been screened for privacy and replaced with N/A. A zero indicates there were no services or payments rendered for a particular code.

ANY USE OF THIS DATA IS AN ACCEPTANCE OF THE FOLLOWING END USER AGREEMENT:

*End User Agreement:

License for Use of Current Procedural Terminology, ANY Edition ("CPT®")

CPT codes, descriptions and other data only are copyright 1995 - 2023 American Medical Association. All rights reserved. CPT is a registered trademark of the American Medical Association (AMA).

You, your employees and agents are authorized to use CPT only as contained in the following authorized materials of Centers for Medicare and Medicaid Services (CMS) internally within your organization within the United States for the sole use by yourself, employees and agents. Use is limited to use in Medicare, Medicaid or other programs administered by CMS. You agree to take all necessary steps to insure that your employees and agents abide by the terms of this agreement.

Any use not authorized herein is prohibited, including by way of illustration and not by way of limitation, making copies of CPT for resale and/or license, transferring copies of CPT to any party not bound by this agreement, creating any modified or derivative work of CPT, or making any commercial use of CPT. License to use CPT for any use not authorized herein must be obtained through the AMA, CPT Intellectual Property Services, AMA Plaza, 330 N. Wabash Ave., Suite 39300, Chicago, IL 60611-5885. Applications are available at the AMA Web site, http://www.ama-assn.org/go/cpt. Applicable FARSDFARS Restrictions Apply to Government Use

This product includes CPT which is commercial technical data and/or computer data bases and/or commercial computer software and/or commercial c...

1. Enrollment includes both Medicaid-only and Medicare-Medicaid (“dual”) enrollees. For both types of enrollees, Medicaid covers LTSS. For dual enrollees, Medicaid may also cover Medicare cost-sharing for acute, primary care, and specialty services covered by Medicare, and other non-LTSS services that are not covered by Medicare.
2. Some comprehensive managed care programs enroll beneficiaries who may be at risk of needing LTSS but do not receive any LTSS. These counts only include individuals that receive LTSS. Moreover, states differ in their ability to report individuals who use MLTSS versus those who are enrolled (and may or may not be using LTSS). This table reports MLTSS users unless otherwise noted.
3. Comprehensive Managed Care Including LTSS does not include PACE programs.
4. MLTSS Only programs cover LTSS under capitation; acute, primary, and specialty care services for these enrollees may be covered by another Medicaid MCO, Medicaid FFS, or by Medicare for dual enrollees. These data include states that provide MLTSS plus other benefits in a package that does not include inpatient medical care.
5. The indicated territory was not able to supply data for this report. The Northern Mariana Islands reported that they have no Medicaid managed care enrollment, but they did not report total Medicaid enrollees.
6. Enrollment and user counts include both Medicaid-only enrollees and dually eligible individuals. For both types of enrollees, Medicaid covers LTSS. For dually eligible individuals, Medicaid may also cover Medicare cost-sharing for acute, primary care, and specialty services covered by Medicare, and other non-LTSS services that are not covered by Medicare.

Abstract (en): This data collection is the second in a series of data releases from the Medicare Current Beneficiary Survey (MCBS) relating to beneficiary access to medical care. The MCBS is a continuous, multipurpose survey of a representative sample of the Medicare population, both aged and disabled. Sample persons are interviewed three times a year over several years to form a continuous profile of their health care experience. Interviews are conducted regardless of whether the sample person resides at home or in a long-term care facility, using the questionnaire version appropriate to the setting. The MCBS also collects a variety of information about demographic characteristics (date of birth, sex, race, education, military service, and marital status), health status and functioning, access to care, sources of and satisfaction with care, insurance coverage, financial resources, and family supports. The 1992 interview data were collected during September through December of 1992, the fourth round of data collection. The 1992 data are designed to stand alone for cross-sectional analysis, or they can be used for longitudinal analysis. Weights are provided for both cross-sectional and longitudinal analysis. Medicare beneficiaries. Respondents were sampled from the Medicare enrollment file to be representative of the Medicare population as a whole and by age group: under 45, 45-64, 65-69, 70-74, 75-79, 80-84, and 85 and over. Because of interest in their special health care needs, the oldest old (85 and over) and the disabled (64 and under) were oversampled to permit detailed analysis of these subpopulations. The sample was drawn from 107 primary sampling units (PSUs). The 1992 Round 4 data include interviews for 10,388 persons who were interviewed in 1991 and for 1,995 new people added to the survey during the current round. The 1992 supplementary sample included newly enrolled beneficiaries, as well as previously enrolled beneficiaries who were included to improve coverage or to maintain the desired sample size. 2006-01-12 All files were removed from dataset 25 and flagged as study-level files, so that they will accompany all downloads.1997-04-22 Part 7 (Health Status and Functioning Record File) and Part 11 (Health Insurance Record File) have been resupplied by the principal investigator to correct several variables. In addition, the billing records data (Parts 25-30) were withdrawn from distribution by the principal investigator. On March 13, 1997, the HCFA withdrew the billing records data (Parts 25-30) from distribution.

This report tracks the number of people covered by private health insurance in the United States. The data includes coverage either provided by employers or purchased directly from an insurer or a health maintenance organization. The data does not include government-provided health insurance such as Medicaid, Medicare and military health care. Data is sourced from the US Census Bureau.

Over ** million Americans were estimated to be enrolled in the Medicaid program as of 2023. That is a significant increase from around ** million ten years earlier. Medicaid is basically a joint federal and state health program that provides medical coverage to low-income individuals and families. Currently, Medicaid is responsible for ** percent of the nation’s health care bill, making it the third-largest payer behind private insurances and Medicare. From the beginning to ObamacareMedicaid was implemented in 1965 and since then has become the largest source of medical services for Americans with low income and limited resources. The program has become particularly prominent since the introduction of President Obama’s health reform – the Patient Protection and Affordable Care Act - in 2010. Medicaid was largely impacted by this reform, for states now had the opportunity to expand Medicaid eligibility to larger parts of the uninsured population. Thus, the percentage of uninsured in the United States decreased from over ** percent in 2010 to *** percent in 2022. Who is enrolled in Medicaid?Medicaid enrollment is divided mainly into four groups of beneficiaries: children, adults under 65 years of age, seniors aged 65 years or older, and disabled people. Children are the largest group, with a share of approximately ** percent of enrollees. However, their share of Medicaid expenditures is relatively small, with around ** percent. Compared to that, disabled people, accounting for **** percent of total enrollment, were responsible for **** percent of total expenditures. Around half of total Medicaid spending goes to managed care and health plans.

This map shows where people have Medicaid or means-tested healthcare coverage in the US (ages under 65). This is shown by State, County, and Census Tract, and uses the most current ACS 5-year estimates.

Home Health Care Agency Ratings

Quality Measurements, Types of Services and More

By US Open Data Portal, data.gov [source]

About this dataset

This dataset provides a list of all Home Health Agencies registered with Medicare. Contained within this dataset is information on each agency's address, phone number, type of ownership, quality measure ratings and other associated data points. With this valuable insight into the operations of each Home Health Care Agency, you can make informed decisions about your care needs. Learn more about the services offered at each agency and how they are rated according to their quality measure ratings. From dedicated nursing care services to speech pathology to medical social services - get all the information you need with this comprehensive look at U.S.-based Home Health Care Agencies!

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

Are you looking to learn more about Home Health Care Agencies registered with Medicare? This dataset can provide quality measure ratings, addresses, phone numbers, types of services offered and other information that may be helpful when researching Home Health Care Agencies.

This guide will explain how to use the data in this dataset to gain a better understanding of Home Health Care Agencies registered with Medicare.

First, you will need to become familiar with the columns in the dataset. A list of all columns and their associated descriptions is provided above for your reference. Once you understand each column’s purpose, it will be easier for you to decide what metrics or variables are most important for your own research.

Next, use this data to compare various facets between different Home Health Care Agencies such as type of ownership, services offered and quality measure ratings like star rating or CMS certification number (from 0-5 stars). Collecting information from multiple sources such as public reviews or customer feedback can help supplement these numerical metrics in order to paint a more accurate picture about each agency's performance and customer satisfaction level.

Finally once you have collected enough data points on one particular agency or a comparison between multiple agencies then conduct more analysis using statistical methods like correlation matrices in order to determine any patterns that exist within the data set which may reveal valuable insights into topic of research at hand

Research Ideas

• Using the data to compare quality of care ratings between agencies, so people can make better informed decisions about which agency to hire for home health services.
• Analyzing the costs associated with different types of home health care services, such as nursing care and physical therapy, in order to determine where money could be saved in health care budgets.
• Evaluating the performance of certain agencies by analyzing the number of episodes billed to Medicare compared to their national averages, allowing agencies with lower numbers of billing episodes to be identified and monitored more closely if necessary

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

Unknown License - Please check the dataset description for more information.

Columns

File: csv-1.csv | Column name | Description | |:----------------------------------------...

Graph and download economic data for Personal current transfer receipts: Government social benefits to persons: Medicare (W824RC1) from Jul 1966 to May 2025 about social assistance, benefits, government, personal, and USA.

As of 2023, nearly *** million people in the United States had some kind of health insurance, a significant increase from around *** million insured people in 2010. However, as of 2023, there were still approximately ** million people in the United States without any kind of health insurance. Insurance coverage The United States does not have universal health insurance, and so health care cost is mostly covered through different private and public insurance programs. In 2021, almost ** percent of the insured population of the United States were insured through employers, while **** percent of people were insured through Medicaid, and **** percent of people through Medicare. As of 2022, about *** percent of people were uninsured in the U.S., compared to ** percent in 2010. The Affordable Care Act The Affordable Care Act (ACA) significantly reduced the number of uninsured people in the United States, from **** million uninsured people in 2013 to **** million people in 2015. However, since the repeal of the individual mandate the number of people without health insurance has risen. Healthcare reform in the United States remains an ongoing political issue with public opinion on a Medicare-for-all plan consistently divided.

No research to date has examined antipsychotic (AP) use, healthcare resource use (HRU), costs, and quality of care among those with schizophrenia in the Medicare program despite it serving as the primary payer for half of individuals with schizophrenia in the US. To provide national estimates and assess regional variation in AP treatment utilization, HRU, costs, and quality measures among Medicare beneficiaries with schizophrenia. Cross-sectional descriptive analysis of 100% Medicare claims data from 2019. The sample included all adult Medicare beneficiaries with continuous fee-for-service coverage and ≥1 inpatient and/or ≥2 outpatient claims with a diagnosis for schizophrenia in 2019. Summary statistics on AP use; HRU and cost; and quality measures were reported at the national, state, and county levels. Regional variation was measured using the coefficient of variation (CoV). We identified 314,888 beneficiaries with schizophrenia. About 91% used any AP; 20% used any long-acting injectable antipsychotic (LAI); and 14% used atypical LAIs. About 28% of beneficiaries had ≥1 hospitalization and 47% had ≥1 emergency room (ER) visits, the vast majority of which were related to mental health (MH). Total annual all-cause, MH, and schizophrenia-related costs were $23,662, $15,000 and $12,109, respectively. Among those with hospitalizations, 18.4% and 27.3% had readmission within 7 and 30 days and 56% and 67% had a physician visit and AP fill within 30 days post-discharge, respectively. Overall, 81% of beneficiaries were deemed adherent to their AP medications. Larger interstate variations were observed in LAI use than AP use (CoV: 0.21 vs 0.02). County-level variations were larger than state-level variations for all measures. In this first study examining a national sample of Medicare beneficiaries with schizophrenia, we found low utilization rates of LAIs and high levels of hospital admissions/readmissions and ER visits. State and county-level variations were also found in these measures.

Note - this is not real-time status information, the data represents bed utilization based on annual estimates of how many beds are used versus available.Definitive Healthcare is the leading provider of data, intelligence, and analytics on healthcare organizations and practitioners. In this service, Definitive Healthcare provides intelligence on the numbers of licensed beds, staffed beds, ICU beds, and the bed utilization rate for the hospitals in the United States. Please see the following for more details about each metric, data was last updated on 17 March 2020:

Number of Licensed beds: is the maximum number of beds for which a hospital holds a license to operate; however, many hospitals do not operate all the beds for which they are licensed. This number is obtained through DHC Primary Research. Licensed beds for Health Systems are equal to the total number of licensed beds of individual Hospitals within a given Health System.

Number of Staffed Bed: is defined as an "adult bed, pediatric bed, birthing room, or newborn ICU bed (excluding newborn bassinets) maintained in a patient care area for lodging patients in acute, long term, or domiciliary areas of the hospital." Beds in labor room, birthing room, post-anesthesia, postoperative recovery rooms, outpatient areas, emergency rooms, ancillary departments, nurses and other staff residences, and other such areas which are regularly maintained and utilized for only a portion of the stay of patients (primarily for special procedures or not for inpatient lodging) are not termed a bed for these purposes. Definitive Healthcare sources Staffed Bed data from the Medicare Cost Report or Proprietary Research as needed. As with all Medicare Cost Report metrics, this number is self-reported by providers. Staffed beds for Health Systems are equal to the total number of staffed beds of individual Hospitals within a given Health System. Total number of staffed beds in the US should exclude Hospital Systems to avoid double counting. ICU beds are likely to follow the same logic as a subset of Staffed beds.

Number of ICU Beds - ICU (Intensive Care Unit) Beds: are qualified based on definitions by CMS, Section 2202.7, 22-8.2. These beds include ICU beds, burn ICU beds, surgical ICU beds, premature ICU beds, neonatal ICU beds, pediatric ICU beds, psychiatric ICU beds, trauma ICU beds, and Detox ICU beds.

Bed Utilization Rate: is calculated based on metrics from the Medicare Cost Report: Bed Utilization Rate = Total Patient Days (excluding nursery days)/Bed Days Available

Potential Increase in Bed Capacity: This metric is computed by subtracting “Number of Staffed Beds from Number of Licensed beds” (Licensed Beds – Staffed Beds). This would provide insights into scenario planning for when staff can be shifted around to increase available bed capacity as needed.

Hospital Definition: Definitive Healthcare defines a hospital as a healthcare institution providing inpatient, therapeutic, or rehabilitation services under the supervision of physicians. In order for a facility to be considered a hospital it must provide inpatient care.

Hospital types are defined by the last four digits of the hospital’s Medicare Provider Number. If the hospital does not have a Medicare Provider Number, Definitive Healthcare determines the Hospital type by proprietary research.

Hospital Types:

·
Short Term Acute Care Hospital (STAC)

o
Provides inpatient care and other services for surgery, acute medical conditions, or injuries

o
Patients care can be provided overnight, and average length of stay is less than 25 days

·
Critical Access Hospital (CAH)

o
25 or fewer acute care inpatient beds

o
Located more than 35 miles from another hospital

o
Annual average length of stay is 96 hours or less for acute care patients

o
Must provide 24/7 emergency care services

o
Designation by CMS to reduce financial vulnerability of rural hospitals and improve access to healthcare

·
Religious Non-Medical Health Care Institutions

o
Provide nonmedical health care items and services to people who need hospital or skilled nursing facility care, but for whom that care would be inconsistent with their religious beliefs

·
Long Term Acute Care Hospitals

o
Average length of stay is more than 25 days

o
Patients are receiving acute care - services often include respiratory therapy, head trauma treatment, and pain management

·
Rehabilitation Hospitals

o
Specializes in improving or restoring patients' functional abilities through therapies

·
Children’s Hospitals

o
Majority of inpatients under 18 years old

·
Psychiatric Hospitals

o
Provides inpatient services for diagnosis and treatment of mental illness 24/7

o
Under the supervision of a physician

·
Veteran's Affairs (VA) Hospital

o
Responsible for the care of war veterans and other retired military personnel

o
Administered by the U.S. VA, and funded by the federal government

·
Department of Defense (DoD) Hospital

o
Provides care for military service people (Army, Navy, Air Force, Marines, and Coast Guard), their dependents, and retirees (not all military service retirees are eligible for VA services)

The Healthcare Cost and Utilization Project (HCUP) State Emergency Department Databases (SEDD) contain the universe of emergency department visits in participating States. The data are translated into a uniform format to facilitate multi-State comparisons and analyses. The SEDD consist of data from hospital-based emergency department visits that do not result in an admission. The SEDD include all patients, regardless of the expected payer including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality (AHRQ), HCUP data inform decision making at the national, State, and community levels. The SEDD contain clinical and resource use information included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and facilities (as required by data sources). Data elements include but are not limited to: diagnoses, procedures, admission and discharge status, patient demographics (e.g., sex, age, race), total charges, length of stay, and expected payment source, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. In addition to the core set of uniform data elements common to all SEDD, some include State-specific data elements. The SEDD exclude data elements that could directly or indirectly identify individuals. For some States, hospital and county identifiers are included that permit linkage to the American Hospital Association Annual Survey File and the Bureau of Health Professions' Area Resource File except in States that do not allow the release of hospital identifiers. Restricted access data files are available with a data use agreement and brief online security training.

Healthcare fraud is considered a challenge for many societies. Health care funding that could be spent on medicine, care for the elderly, or emergency room visits is instead lost to fraudulent activities by materialistic practitioners or patients. With rising healthcare costs, healthcare fraud is a major contributor to these increasing healthcare costs.

Try out various unsupervised techniques to find the anomalies in the data.

Detailed Data File:

The following variables are included in the detailed Physician and Other Supplier data file (see Appendix A for a condensed version of variables included)).

npi – National Provider Identifier (NPI) for the performing provider on the claim. The provider NPI is the numeric identifier registered in NPPES.

nppes_provider_last_org_name – When the provider is registered in NPPES as an individual (entity type code=’I’), this is the provider’s last name. When the provider is registered as an organization (entity type code = ‘O’), this is the organization's name.

nppes_provider_first_name – When the provider is registered in NPPES as an individual (entity type code=’I’), this is the provider’s first name. When the provider is registered as an organization (entity type code = ‘O’), this will be blank.

nppes_provider_mi – When the provider is registered in NPPES as an individual (entity type code=’I’), this is the provider’s middle initial. When the provider is registered as an organization (entity type code= ‘O’), this will be blank.

nppes_credentials – When the provider is registered in NPPES as an individual (entity type code=’I’), these are the provider’s credentials. When the provider is registered as an organization (entity type code = ‘O’), this will be blank.

nppes_provider_gender – When the provider is registered in NPPES as an individual (entity type code=’I’), this is the provider’s gender. When the provider is registered as an organization (entity type code = ‘O’), this will be blank.

nppes_entity_code – Type of entity reported in NPPES. An entity code of ‘I’ identifies providers registered as individuals and an entity type code of ‘O’ identifies providers registered as organizations.

nppes_provider_street1 – The first line of the provider’s street address, as reported in NPPES.

nppes_provider_street – The second line of the provider’s street address, as reported in NPPES.

nppes_provider_city – The city where the provider is located, as reported in NPPES.

nppes_provider_zip – The provider’s zip code, as reported in NPPES.

nppes_provider_state – The state where the provider is located, as reported in NPPES. The fifty U.S. states and the District of Columbia are reported by the state postal abbreviation. The following values are used for all other areas:

'XX' = 'Unknown' 'AA' = 'Armed Forces Central/South America' 'AE' = 'Armed Forces Europe' 'AP' = 'Armed Forces Pacific' 'AS' = 'American Samoa' 'GU' = 'Guam' 'MP' = 'North Mariana Islands' 'PR' = 'Puerto Rico' 'VI' = 'Virgin Islands' 'ZZ' = 'Foreign Country'

nppes_provider_country – The country where the provider is located, as reported in NPPES. The country code will be ‘US’ for any state or U.S. possession. For foreign countries (i.e., state values of ‘ZZ’), the provider country values include the following: AE=United Arab Emirates IT=Italy AG=Antigua JO= Jordan AR=Argentina JP=Japan AU=Australia KR=Korea BO=Bolivia KW=Kuwait BR=Brazil KY=Cayman Islands CA=Canada LB=Lebanon CH=Switzerland MX=Mexico CN=China NL=Netherlands CO=Colombia NO=Norway DE= Germany NZ=New Zealand ES= Spain PA=Panama FR=France PK=Pakistan GB=Great Britain RW=Rwanda GR=Greece SA=Saudi Arabia HU= Hungary SY=Syria IL= Israel TH=Thailand IN=India TR=Turkey IS= Iceland VE=Venezuela

provider_type – Derived from the provider specialty code reported on the claim.

medicare_participation_indicator – Identifies whether the provider participates in Medicare and/or accepts the assigned assignment of Medicare allowed amounts.

place_of_service – Identifies whether the place of service submitted on the claims is a facility (value of ‘F’) or non-facility (value of ‘O’). Non-facility is generally an office setting; however other entities are included in non-facility.

hcpcs_code – HCPCS code used to identify the specific medical service furnished by the provider.

hcpcs_description – Description of the HCPCS code for the specific medical service furnished by the provider.

hcpcs_drug_indicator –Identifies whether the HCPCS code for the specific service furnished by the provider is an HCPCS listed on the Medicare Part B Drug Average Sales Price (ASP) File.

line_srvc_cnt – Number of services provided; note that the metrics used to count the number provided can vary from service to service.

bene_unique_cnt – Number of distinct Medicare beneficiaries rec...

Abstract (en): This data collection contains two data files derived from information gathered in the initial screening interview and Rounds 1-4 of the Household Survey component of the 1987 NATIONAL MEDICAL EXPENDITURE SURVEY (NMES). The Person File supplies data on each sampled person who reported coverage by Medicare at any time in 1987 and who responded to all rounds of the Household Survey for which he or she was eligible to respond. Data in this file include age, sex, race, marital status, education, employment status, personal and family income, coverage under private health insurance and public programs such as Medicaid and CAMPUS/CAMPVA, and the total number and cost of all prescriptions purchased in 1987 while under Medicare coverage. In addition, there are indicators of general health and specific medical conditions: stroke, cancer, heart disease, gallbladder disease, high blood pressure, hardening of the arteries, rheumatism, emphysema, arthritis and diabetes. The Prescribed Medicines Event File presents data pertaining to every instance a prescribed medicine was purchased or otherwise obtained by these Medicare beneficiaries during 1987. For respondents who were covered by Medicare for part of the year, only prescribed medicines acquired during the Medicare coverage period are included. This file gives the trade and generic name of each prescribed medication and reports the cost of the prescription and the medical condition for which it was prescribed. Civilian noninstitutionalized population of the United States living in housing units, group quarters, and other noninstitutional (nongroup) quarters. Stratified multistage area probability sample of dwelling units. Dwelling units including blacks, Hispanics, the elderly, the functionally impaired, and the poor were oversampled. 2006-03-30 File CB9340.SUPP.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2006-03-30 All files were removed from dataset 3 and flagged as study-level files, so that they will accompany all downloads. (1) The principal investigator was formerly known as the National Center for Health Services Research and Health Care Technology Assessment. (2) The age distribution for Part 1: 17 and under (N=8), 18-63 (N=444), 64 (N=246), 65-74 (N=3,246), 75-84 (N=1,685), 85+ (N=409). (3) Parts 1 and 2 are linked by common identification variables. (4) Hard copy supplementary materials to the machine-readable documentation in Part 3 are supplied for this collection. (5) Part 2 contains alphabetic variables. (6) NMES consists of several surveys including two household panel surveys: the Household Survey and the Survey of American Indians and Alaska Natives (SAIAN). The Household Survey, from which this data collection is derived, surveyed the United States noninstitutionalized population and was fielded over four rounds of personal and telephone interviews at four-month intervals, with a short telephone interview constituting the fifth final round. SAIAN, which was conducted over three rounds of personal interviews, surveyed all persons who were eligible for care through the Indian Health Service and were living on or near reservations. These household surveys were supplemented by additional surveys, most important of which are the Health Insurance Plans Survey of employers and insurers of consenting household survey respondents, and the Medical Provider Survey of physicians, osteopaths, and inpatient and outpatient facilities, including home health care agencies reported as providing services to any member of the noninstitutionalized population sample. NMES also surveyed persons resident in or admitted to long-term care facilities (nursing homes and facilities for the mentally retarded) at any time in 1987. Information on these individuals was obtained from the Survey of Institutions, which collected data from facility administrators and designated staff, and the Survey of Next-of-Kin, which collected data from the respondent's next-of-kin or other knowledgeable persons. Together, the major components of NMES provide measures of health status and estimates of insurance coverage and the use of services, expenditures, and sources of payment for the period from January 1 to December 31, 1987 for the civilian population of the United States. NMES continues a series of national health care expenditure surveys carried out in the past, particularly the 1980 National Medical Care Utiliza...

This map shows where people have Medicaid or means-tested healthcare coverage in the US (ages under 65). This is shown by State, County, and Census Tract, and uses the most current ACS 5-year estimates.The map shows the percentage of the population with Medicaid or means-tested coverage, and also shows the total count of population with Medicaid or means-tested coverage. Because of Medicare starting at age 65, this map represents the population under 65. This map shows a pattern using both centroids and boundaries. This helps clarify where specific areas reach. The data shown is current-year American Community Survey (ACS) data from the US Census. The data is updated each year when the ACS releases its new 5-year estimates. To see the original layers used in this map, visit this group. To learn more about the vintage and data source, click here to visit the Living Atlas layer used in the map.To learn more about when the ACS releases data updates, click here.

Snapshot img

US Dental Clearing Houses Market Size 2025-2029

The US dental clearing houses market size is forecast to increase by USD 351.3 million, at a CAGR of 10.2% between 2024 and 2029.

The market is experiencing significant growth due to expanding dental insurance coverage, which is increasing the number of dental procedures being performed. Strategic partnerships and collaborations among market players are also driving market growth. However, data security and privacy concerns continue to pose challenges for dental clearing houses, as they handle sensitive patient information. Advanced technologies, such as predictive analytics, anomaly detection, and automation, are transforming the dental clearing houses market by streamlining processes and reducing administrative burdens. Mobile payments, patient reminders, and electronic health records are becoming increasingly popular, enabling dental practices to enhance patient engagement and improve operational efficiency. To address these concerns, market participants are investing in advanced security technologies and implementing stringent data protection policies. Overall, these trends and challenges are shaping the future of the dental clearing houses market.

What will be the Size of the market During the Forecast Period?

Request Free Sample

The dental clearing houses market encompasses the provision of services and technologies that facilitate the administrative process between healthcare providers and insurance payers In the dental industry. This market is characterized by a significant volume of electronic claim submissions, driven by the widespread adoption of medical billing software and electronic data interchange. The market's size is substantial, with millions of patient encounters resulting in claims each year. Efficiency is a key factor In the market, with administration time and claim denial rates being major areas of focus. HIPAA compliance and data security concerns are also significant considerations. Automation, predictive analytics, and anomaly detection are increasingly utilized to streamline the claims processing and reimbursement cycle.
In addition, the market is witnessing a digitalization trend, with electronic submission volumes continuing to grow. Patient responsibility, including patient encounters and claim denials, is another important aspect of the market. Dental clearing houses offer solutions that help providers manage these aspects, ensuring accurate and timely reimbursement. The market is dynamic, with ongoing advancements in technology and evolving industry requirements shaping its direction.

How is this market segmented and which is the largest segment?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Application

  Claim submission
  Eligibility and benefit verification
  Claim status inquiry
  Others


End-user

  Dental hospitals and clinics
  Dental service organizations (DSOs)
  Insurance companies


Geography

  US

By Application Insights

The claim submission segment is estimated to witness significant growth during the forecast period. The claim submission segment in the US dental clearing houses market plays a crucial role by facilitating the electronic transmission of dental claims to insurance payers. This application streamlines the reimbursement process for dental practices, minimizing claim denials and expediting payments. Claim submission is the most frequently used application In the market, with solutions like EDI Health Group's ClaimConnect leading the way. ClaimConnect, which boasts a 99% clean claim rate, is designed to eliminate delays and accelerate payments, thereby reducing claim costs, processing time, and manual paperwork for dental providers. Advanced technologies, such as Electronic Data Interchange (EDI), predictive analytics, and anomaly detection, are integral to these claim submission solutions, ensuring operational efficiency, HIPAA compliance, and data security.

Get a glance at the market report of share of various segments Request Free Sample

Market Dynamics

Our US Dental Clearing Houses Market researchers analyzed the data with 2024 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.

What are the key market drivers leading to the rise in the adoption of US Dental Clearing Houses Market?

Expansion of dental insurance coverage is the key driver of the market. The market is experiencing significant growth due to the increasing number of insured individuals under dental insurance policies. According to the Centers for Medicare and Medicaid Services (CMS), approximately 21 million people have enrolled i