The Medicare Clinical Laboratory Fee Schedule (CLFS) dataset provides raw data reported by any applicable laboratories that reported a volume greater than 10 tests for the data collection period. As described by the Protecting Access to Medicare Act, Applicable Laboratories must report to CMS private payor rates and associated volumes for laboratory tests on the Clinical Laboratory Fee Schedule.

This dataset tracks the updates made on the dataset "Medicare Clinical Laboratory Fee Schedule Private Payer Rates and Volumes" as a repository for previous versions of the data and metadata.

This dataset contains data for the Healthcare Payments Data (HPD) Healthcare Measures report. The data cover three measurement categories: Health conditions, Utilization, and Demographics. The health condition measurements quantify the prevalence of long-term illnesses and major medical events prominent in California’s communities like diabetes and heart failure. Utilization measures convey rates of healthcare system use through visits to the emergency department and different categories of inpatient stays, such as maternity or surgical stays. The demographic measures describe the health coverage and other characteristics (e.g., age) of the Californians included in the data and represented in the other measures. The data include both a count or sum of each measure and a count of the base population so that data users can calculate the percentages, rates, and averages in the visualization. Measures are grouped by year, age band, sex (assigned sex at birth), payer type, Covered California Region, and county.

This data includes the top 25 list for costliest prescribed drugs, most frequently prescribed drugs and the prescribed drugs with the highest monthly median out-of-pocket cost for members. Each of these top 25 lists are broken out by payer type (i.e., All Payers, All Payers W/O Medi-Cal, Commercial, Medicare or Medi-Cal) and drug category (i.e., All, Brand, Generic, Biosimilar or Biologic). The includes National Drug Code (NDC), Year, Top 25 Ranking, National Drug Code, Drug Name, number of prescriptions, number of individuals, total costs, average cost per unit, average dispensed units per fill, drug unit of measure, monthly median out-of-pocket cost, 25th percentile for monthly out-of-pocket cost, 75th percentile for monthly out-of-pocket cost, and percent of monthly out-of-pocket cost with zero dollar amounts for each NDC in each top 25 list.

This dataset contains data for the Healthcare Payments Data (HPD): Medical Out-of-Pocket Costs and Chronic Conditions report. The data covers three measurement categories: annual member count, annual median out-of-pocket count, annual median claim count. The annual member count quantify the number of unique individuals who received at least one medical service in the reporting year. Annual median out-of-pocket measurements quantifies the sum of copay, coinsurance, and deductible incurred by members. Annual median claim count measurements quantifies the number of distinct claims or encounters associated with members. Both 25th and 75th percentiles for out-of-pocket cost and claim count are also included. Measures are grouped by payer types, chronic conditions flag, chronic condition types, and chronic condition numbers.

WA-APCD - Washington All-Payer Claims Database

The WA-APCD is the state’s most complete source of health care eligibility, medical claims, pharmacy claims, and dental claims insurance data. It contains claims from more than 50 data suppliers, spanning commercial, Medicaid, and Medicare managed care. The WA-APCD has historical claims data for five years (2013-2017), with ongoing refreshes scheduled quarterly. Workers' compensation data from the Washington Department of Labor & Industries will be added in fall 2018.

Download the attachment for the data dictionary and more information about WA-APCD and the data.

The Healthcare Cost and Utilization Project (HCUP) Nationwide Readmissions Database (NRD) is a unique and powerful database designed to support various types of analyses of national readmission rates for all payers and the uninsured. The NRD includes discharges for patients with and without repeat hospital visits in a year and those who have died in the hospital. Repeat stays may or may not be related. The criteria to determine the relationship between hospital admissions is left to the analyst using the NRD. This database addresses a large gap in health care data - the lack of nationally representative information on hospital readmissions for all ages. Outcomes of interest include national readmission rates, reasons for returning to the hospital for care, and the hospital costs for discharges with and without readmissions. Unweighted, the NRD contains data from approximately 18 million discharges each year. Weighted, it estimates roughly 35 million discharges. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels. The NRD is drawn from HCUP State Inpatient Databases (SID) containing verified patient linkage numbers that can be used to track a person across hospitals within a State, while adhering to strict privacy guidelines. The NRD is not designed to support regional, State-, or hospital-specific readmission analyses. The NRD contains more than 100 clinical and non-clinical data elements provided in a hospital discharge abstract. Data elements include but are not limited to: diagnoses, procedures, patient demographics (e.g., sex, age), expected source of payer, regardless of expected payer, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge, discharge month, quarter, and year, total charges, length of stay, and data elements essential to readmission analyses. The NIS excludes data elements that could directly or indirectly identify individuals. Restricted access data files are available with a data use agreement and brief online security training.

This dataset contains information submitted by New York State Article** 282 Hospitals** as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions.

The file contains information on the** volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge.**

WA-APCD - Washington All-Payer Claims Database

The WA-APCD is the state’s most complete source of health care eligibility, medical claims, pharmacy claims, and dental claims insurance data. It contains claims from more than 50 data suppliers, spanning commercial, Medicaid, and Medicare managed care. The WA-APCD has historical claims data for five years (2013-2017), with ongoing refreshes scheduled quarterly. Workers' compensation data from the Washington Department of Labor & Industries will be added in fall 2018.

Download the attachment for the data dictionary and more information about WA-APCD and the data.

The column chart shows performance measurement rates for the managed care provider network by payer. The chart uses the statewide average rates of all insurance plans. For more information, check out http://www.health.ny.gov/health_care/managed_care/reports/quality_performance_improvement.htm. The "About" tab contains additional details concerning this dataset.

The first Social Drivers of Health (SDoH) dataset contains percentages of preventable hospitalizations (i.e., discharges) by Race/Ethnicity, preferred language spoken, expected payer, percent of employment, percent of home ownership, percent of park access and percent of access to basic kitchen facilities by the stated year. Preventable hospitalizations rates were created by dividing the number of patients who are 18 years and older and were admitted to a hospital for at least one of the preventable hospitalization diagnoses (see list below) by the total number of hospitalizations. List of preventable hospitalization diagnoses: diabetes with short-term complications, diabetes with long-term complications, uncontrolled diabetes without complications, diabetes with lower-extremity amputation, chronic obstructive pulmonary disease, asthma, hypertension, heart failure, angina without a cardiac procedure, dehydration, bacterial pneumonia, or urinary tract infection were counted as a preventable hospitalization. These conditions correspond with the conditions used in the Agency for Healthcare Research and Quality’s (AHRQ), Prevention Quality Indicator - Overall Composite Measure (PQI #90). The SDoH "overtime" dataset contains percentages of preventable hospitalizations (i.e., discharges) by Race/Ethnicity, preferred language spoken and expected payer overtime in the stated year range.

Content

The Federal Reserve Board has discontinued this series as of October 31, 2016. More information, including possible alternative series, can be found at http://www.federalreserve.gov/feeds/h15.html. Rate paid by fixed-rate payer on an interest rate swap with maturity of thirty years. International Swaps and Derivatives Association (ISDA®) mid-market par swap rates. Rates are for a Fixed Rate Payer in return for receiving three month LIBOR, and are based on rates collected at 11:00 a.m. Eastern time by Garban Intercapital plc and published on Reuters Page ISDAFIX®1. ISDAFIX is a registered service mark of ISDA. Source: Reuters Limited.

Context

This is a dataset from the Federal Reserve hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according to the frequency that the data updates. Explore the Federal Reserve using Kaggle and all of the data sources available through the Federal Reserve organization page!

• Update Frequency: This dataset is updated daily.

• Observation Start: 2000-07-03

• Observation End : 2016-10-28

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

Cover photo by Roman Trofimiuk on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

Payer–Provider Data Exchange Platforms Market Outlook

According to our latest research, the Payer–Provider Data Exchange Platforms market size was valued at $3.7 billion in 2024 and is projected to reach $12.4 billion by 2033, expanding at a robust CAGR of 14.2% during the forecast period of 2025–2033. This remarkable growth trajectory is primarily driven by the increasing emphasis on interoperability and seamless data sharing between healthcare payers and providers, a trend accelerated by regulatory mandates and the rising adoption of digital health technologies worldwide. As healthcare ecosystems become more complex and data-driven, the demand for sophisticated data exchange platforms that ensure secure, real-time, and compliant information flow is surging, fundamentally transforming payer–provider collaboration and enabling improved patient outcomes, cost efficiencies, and operational agility.

This dataset contains information submitted by New York State Article 28 Hospitals as part of the New York Statewide Planning and Research Cooperative (SPARCS) and Institutional Cost Report (ICR) data submissions. The dataset contains information on the volume of discharges, All Payer Refined Diagnosis Related Group (APR-DRG), the severity of illness level (SOI), medical or surgical classification the median charge, median cost, average charge and average cost per discharge. When interpreting New York’s data, it is important to keep in mind that variations in cost may be attributed to many factors. Some of these include overall volume, teaching hospital status, facility specific attributes, geographic region and quality of care provided. For more information, check out: http://www.health.ny.gov/statistics/sparcs/ or go to the "About" tab.

The Nationwide Readmissions Database (NRD) is a unique and powerful database designed to support various types of analyses of national readmission rates for all patients regardless of the expected payer for the hospital stay. The NRD includes discharges for patients with and without repeat hospital visits in a year and those who have died in the hospital. Repeat stays may or may not be related. The criteria to determine the relationship between hospital admissions is left to the analyst using the NRD. This database addresses a large gap in healthcare data - the lack of nationally representative information on hospital readmissions for all ages.

This statistic displays the rate of all-cause 7 and 30-day readmission rates for U.S. hospitals in 2014, by expected payer. According to the data, among those using Medicare to pay for hospital expenses, those that were readmitted within 7 days had a readmission rate of 6.1 and those that were readmitted after 7 days had a readmission rate of 17.3.

The column chart shows rates of satisfaction for managed care plans by year. The chart can be filtered by measurement year or measure by changing these options under the Filter tab. The chart uses statewide average rates of all insurance plans. Removing the statewide average filter is not recommended. For more information, check out http://www.health.ny.gov/health_care/managed_care/reports/quality_performance_improvement.htm. The "About" tab contains additional details concerning this dataset.

The Healthcare Cost and Utilization Project (HCUP) Nationwide Emergency Department Sample (NEDS) is the largest all-payer emergency department (ED) database in the United States. yielding national estimates of hospital-owned ED visits. Unweighted, it contains data from over 30 million ED visits each year. Weighted, it estimates roughly 145 million ED visits nationally. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels.

Sampled from the HCUP State Inpatient Databases (SID) and State Emergency Department Databases (SEDD), the HCUP NEDS can be used to create national and regional estimates of ED care. The SID contain information on patients initially seen in the ED and subsequently admitted to the same hospital. The SEDD capture information on ED visits that do not result in an admission (i.e., treat-and-release visits and transfers to another hospital). Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels.

The NEDS contain information about geographic characteristics, hospital characteristics, patient characteristics, and the nature of visits (e.g., common reasons for ED visits, including injuries). The NEDS contains clinical and resource use information included in a typical discharge abstract, with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data sources). It includes ED charge information for over 85% of patients, regardless of expected payer, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge’. The NEDS excludes data elements that could directly or indirectly identify individuals, hospitals, or states.Restricted access data files are available with a data use agreement and brief online security training.

Discover the explosive growth of the healthcare payer analytics market! This in-depth analysis reveals key trends, drivers, and restraints impacting this $15B+ industry, including regional market shares, leading companies (Oracle, Cerner, McKesson), and future projections to 2033. Learn how payers are using analytics for cost control, risk adjustment, and better patient outcomes.

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.