Variability in mean payment per physician, number of physicians, and aggregated payments for transactions in the Open Payments database, 2014–2018, for each top-category specialty available for allopathic and osteopathic physicians.

Every year, CMS will update the Open Payments data at least once after its initial publication. The refreshed data will include updates to data disputes and other data corrections made since the initial publication of this data documenting payments or transfers of value to physicians and teaching hospitals, and physician ownership and investment interests. This financial data is submitted by applicable manufacturers and applicable group purchasing organizations (GPOs). #### What data is collected? Applicable manufacturers and GPOs submit data to Open Payments about payments or other transfers of value between applicable manufacturers and GPOs and physicians or teaching hospitals: 1. Paid directly to physicians and teaching hospitals (known as direct payments) 2. Paid indirectly to physicians and teaching hospitals (known as indirect payments) through an intermediary such as a medical specialty society 3. Designated by physicians or teaching hospitals to be paid to another party (known

We conducted a cross-sectional study of the publicly available 2022 Open Payments data to characterize and quantify sponsored events (available for download at: https://www.cms.gov/priorities/key-initiatives/open-payments/data/dataset-downloads). Data sources We downloaded the 2022 dataset ZIP files from the Open Payments website on June 30th, 2023. We included all records for nurse practitioners, clinical nurse specialists, certified registered nurse anesthetists, and certified nurse-midwives (hereafter advanced practiced registered nurses (APRNs)); and allopathic and osteopathic physicians (hereafter, ‘physicians’). To ensure consistency in provider classification, we linked Payments data to the National Plan and Provider Enumeration System data (June 2023) by National Provider Identifier (NPI) and the National Uniform Claim Committee (NUCC) and excluded individuals with an ambiguous provider type. Event-centric analysis of Open Payments records: Creating an event typology We included only payments classified as “food and beverage” to reliably identify distinct sponsored events. We reasoned that food and beverage would be consumed on the same day in the same place, thus assumed that records for food and beverage associated with the same event would share the date of payment and location. We also assumed that the reported value of a food and beverage payment is the total cost of the hospitality divided by the number of attendees, thus grouped payment records with the same amount, rounded to the nearest dollar. Inferring which Open Payment records relate to the same sponsored event requires analytic decisions regarding the selection and representation of variables that define an event. To understand the impact of these choices, we undertook a sensitivity analysis to explore alternative ways to group Open Payments records for food and beverage, to determine how combination of variables, including date (specific date or within the same calendar week), amount (rounded to nearest dollar), and recipient’s state, affected the identification of sponsored events in the Open Payments data set. We chose to define a sponsored event as a cluster of three or more individual payment records for food and beverage (nature of payment) with the following matching Open Payments record variables: • Submitting applicable manufacturer (name) • Product category or therapeutic area • Name of drug or biological or device or medical supply • Recipient state • Total amount of payment (USD, rounded to nearest dollar) • Date of payment (exact) After examining the distribution of the data, we classified events in terms of size (≥20 attendees as “large” and 3-<20 as “small”) and amount per person. We categorized events <$10 as “coffee”, $10-<$30 as “lunch”, $30-<$150 as “dinner”, and ≥$150 as “banquet”.

Information on Open Payments managed by the Centers for Medicare & Medicaid Services (CMS), which is a national disclosure program created by the Affordable Care Act (ACA) that promotes transparency and accountability by helping consumers understand the financial relationships between pharmaceutical and medical device industries and physicians and teaching hospitals.

Open Payments (otherwise known as the Sunshine Act) - Open Payments is a Congressionally-mandated transparency program that increases awareness of financial relationships between the health care industry and physicians by collecting and reporting any payments or transfers of value medical manufacturers make to physicians or teaching hospitals.

This table provides a statistics on Distribution of Physician Payments by Program and Specialty under the Alberta Health Care Insurance Plan (AHCIP). This table is an Excel version of a table in the “Alberta Health Care Insurance Plan Statistical Supplement” report published annually by Alberta Health.

This dataset is pre-filtered based on the most frequent searches of Open Payments data.

Sometimes, doctors and hospitals have financial relationships with health care manufacturing companies. These relationships can include money for research activities, gifts, speaking fees, meals, or travel. The Social Security Act requires CMS to collect information from applicable manufacturers and group purchasing organizations (GPOs) in order to report information about their financial relationships with physicians and hospitals. Open Payments is the federally run program that collects the information about these financial relationships and makes it available to you from the Opendata.utah.gov portal.

The number of editors in each specialty, and percentage of editors receiving general payments.

Association between various amounts of opioid-related payments and Medicare Part D opioid prescribing for physicians receiving payments in 2014 and 2015, but not in 2013.

Median and mean payments received by Chief editors and Associate editors for each specialty.

The CMS Program Statistics - Medicare Physician, Non-Physician Practitioner and Supplier tables provide use and payment data for physicians, other practitioners, limited-licensed practitioners, and durable medical equipment, prosthetic, and orthotic (DMEPOS) suppliers. For additional information on enrollment, providers, and Medicare use and payment, visit the CMS Program Statistics page. These data do not exist in a machine-readable format, so the view data and API options are not available. Please use the download function to access the data. Below is the list of tables: MDCR PHYSSUPP 1. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization, Program Payments, Cost Sharing, and Balance Billing for Original Medicare Beneficiaries, by Type of Entitlement, Yearly Trend MDCR PHYSSUPP 2. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization, Program Payments, Cost Sharing, and Balance Billing for Original Medicare Beneficiaries, by Demographic Characteristics and Medicare-Medicaid Enrollment Status MDCR PHYSSUPP 3. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization, Program Payments, Cost Sharing, and Balance Billing for Original Medicare Beneficiaries, by Area of Residence MDCR PHYSSUPP 4. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization, Program Payments, and Balance Billing for Original Medicare Beneficiaries, by Type of Service MDCR PHYSSUPP 5. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization, Program Payments, and Balance Billing for Original Medicare Beneficiaries, by Place of Service MDCR PHYSSUPP 6. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization, Program Payments, and Balance Billing for Original Medicare Beneficiaries, by Physician Specialty MDCR PHYSSUPP 7. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization and Program Payments for Original Medicare Beneficiaries, by Berenson-Eggers Type of Service (BETOS) Classification

Characteristics of physicians among the top quintile for receipt of payments in Q3/4 2013*.

This dataset is pre-filtered based on the most frequent searches of Open Payments data.

The HPSAs Eligible for the Medicare Physician Bonus Payment advisor tools allows the user (physician) to determine if an address is eligible for bonus payments. Medicare makes bonus payments to physicians who provide medical care services in geographic areas that are HRSA-designated as primary medical care Health Professional Shortage Areas (HPSAs) and to psychiatrists who provide services in HRSA-designated mental health HPSAs. The search results indicate if the address is in a Primary Care HPSA or Mental Health HPSA, along with state, county name, Census Tract, zip code, and a map identifying the address.

This study explores interest in, and the challenges faced by transit agencies and operators in the adoption of open-loop payment systems. The research team focuses in particular on the ways that agencies view passenger needs in the context of adopting open payments. Challenges with cash payments, an increasingly cashless society, and the expanding offerings of digital payment options have spurred increased interest in open-loop payments among transit operators. Paying for transit with cash can require additional time at boarding, add extra steps for passengers who must pay with exact fare, and result in service inefficiencies. It presents security concerns for drivers, and administrative burdens for agencies. While the full costs of cash handling vary per agency the cost of handling and moving cash may be considerable. Pioneering transit agencies are adopting open payment systems that accept credit cards, debit cards, and smartphone/watch-based transactions. However, there is a huge diversity among transit agencies and as such, agencies face different challenges and to different degrees, when considering the adoption of open payment systems. Challenges can include financial barriers, capacity limitations, technological challenges, the duration of existing contracts, competing needs, and a number of passenger challenges such as lack of credit cards or smartphones. This study uses data collected from California transit agencies in the fall of 2022 that gathered information about agency perceptions of open-loop payments and the challenges with adopting open fare collection systems, and whether assistance programs would benefit transit agencies interested in adopting open-loop payments. Even before the pandemic prompted agencies to consider open and contactless payments, many agencies were exploring this option. Results of the present study indicate that the majority of agencies are considering or have considered implementing open payment systems, but agencies are not fully aware of the assistance available from the California Integrated Travel Program to help in the transition to digital and open payment systems. Key challenges include the cost, as well as the technical needs to implement open payments. Agencies also cited passenger familiarity with technology and ability to have a bank account as potential hurdles. This study sheds light on the challenges facing small to medium transit agencies in the transition of California’s transit systems to open-loop payment systems. Methods This data was collected through an online survye of transit agencies; the survey was administered using Qualtrics and the data was downloaded from the Qualtrics platform as a .csv file. The full question text as it appeared in the survey is included in the Codebook. Additional questions containing identifying information or information that has not yet been analyzed was removed from the data prior to publishing.

This dataset provides information about payments made by the City of Detroit to vendors, suppliers, and individuals providing goods and services to the City. Payment data is currently available for City of Detroit Fiscal Year 2017-2018, Fiscal Year 2018-2019, Fiscal Year 2019-2020, and Fiscal Year 2020-2021. This data does not include City payroll and benefits expenses.

This dataset contains data for the Healthcare Payments Data (HPD) Services report. The term "Services" refers to individual procedures reported on the service lines of healthcare claims in California, categorized using the Restructured Berenson-Eggers Type of Services (BETOS) Classification System (RBCS) from the Centers for Medicare & Medicaid Services (CMS). The data in the report includes three main metrics: Total services, the total member count, and the service rate per 1,000 members. Total services represents the total number of services received by members during the reporting year. The member count reports the total number of unique individuals who received at least one service during the reporting year. The service rate per 1,000 members is calculated by dividing the total number of services during the reporting year by the total sum of monthly member enrollments (provided in the data) and multiplying the result by 12,000. The metrics can be grouped by year, age, sex (assigned at birth), county of residence (including an option for Los Angeles Service Planning Areas, or SPAs), Covered California Region, and payer.

Users can choose to view the data at two different levels. The most aggregate level groups the data by the eight main RBCS categories: Anesthesia, Durable Medical Equipment (DME), Evaluation and Management (E&M), Imaging, Procedure, Test, Treatment and Other. The second level breaks the eight aggregate RBCS categories into more specific subcategories. Data files are provided for each choice.

This dataset contains data for the Healthcare Payments Data (HPD) Snapshot visualization. The Enrollment data file contains counts of claims and encounter data collected for California's statewide HPD Program. It includes counts of enrollment records, service records from medical and pharmacy claims, and the number of individuals represented across these records. Aggregate counts are grouped by payer type (Commercial, Medi-Cal, or Medicare), product type, and year. The Medical data file contains counts of medical procedures from medical claims and encounter data in HPD. Procedures are categorized using claim line procedure codes and grouped by year, type of setting (e.g., outpatient, laboratory, ambulance), and payer type. The Pharmacy data file contains counts of drug prescriptions from pharmacy claims and encounter data in HPD. Prescriptions are categorized by name and drug class using the reported National Drug Code (NDC) and grouped by year, payer type, and whether the drug dispensed is branded or a generic.

Medical Payments to Physicians in Nova Scotia. Includes the following data fields: Year, Payment Type, Payment Type Subcategory, Amount