The All CMS Data Feeds dataset is an expansive resource offering access to 118 unique report feeds, providing in-depth insights into various aspects of the U.S. healthcare system. With over 25.8 billion rows of data meticulously collected since 2007, this dataset is invaluable for healthcare professionals, analysts, researchers, and businesses seeking to understand and analyze healthcare trends, performance metrics, and demographic shifts over time. The dataset is updated monthly, ensuring that users always have access to the most current and relevant data available.

Dataset Overview:

118 Report Feeds: - The dataset includes a wide array of report feeds, each providing unique insights into different dimensions of healthcare. These topics range from Medicare and Medicaid service metrics, patient demographics, provider information, financial data, and much more. The breadth of information ensures that users can find relevant data for nearly any healthcare-related analysis. - As CMS releases new report feeds, they are automatically added to this dataset, keeping it current and expanding its utility for users.

25.8 Billion Rows of Data:

• With over 25.8 billion rows of data, this dataset provides a comprehensive view of the U.S. healthcare system. This extensive volume of data allows for granular analysis, enabling users to uncover insights that might be missed in smaller datasets. The data is also meticulously cleaned and aligned, ensuring accuracy and ease of use.

Historical Data Since 2007: - The dataset spans from 2007 to the present, offering a rich historical perspective that is essential for tracking long-term trends and changes in healthcare delivery, policy impacts, and patient outcomes. This historical data is particularly valuable for conducting longitudinal studies and evaluating the effects of various healthcare interventions over time.

Monthly Updates:

• To ensure that users have access to the most current information, the dataset is updated monthly. These updates include new reports as well as revisions to existing data, making the dataset a continuously evolving resource that stays relevant and accurate.

Data Sourced from CMS:

• The data in this dataset is sourced directly from the Centers for Medicare & Medicaid Services (CMS). After collection, the data is meticulously cleaned and its attributes are aligned, ensuring consistency, accuracy, and ease of use for any application. Furthermore, any new updates or releases from CMS are automatically integrated into the dataset, keeping it comprehensive and current.

Use Cases:

Market Analysis:

• The dataset is ideal for market analysts who need to understand the dynamics of the healthcare industry. The extensive historical data allows for detailed segmentation and analysis, helping users identify trends, market shifts, and growth opportunities. The comprehensive nature of the data enables users to perform in-depth analyses of specific market segments, making it a valuable tool for strategic decision-making.

Healthcare Research:

• Researchers will find the All CMS Data Feeds dataset to be a robust foundation for academic and commercial research. The historical data, combined with the breadth of coverage across various healthcare metrics, supports rigorous, in-depth analysis. Researchers can explore the effects of healthcare policies, study patient outcomes, analyze provider performance, and more, all within a single, comprehensive dataset.

Performance Tracking:

• Healthcare providers and organizations can use the dataset to track performance metrics over time. By comparing data across different periods, organizations can identify areas for improvement, monitor the effectiveness of initiatives, and ensure compliance with regulatory standards. The dataset provides the detailed, reliable data needed to track and analyze key performance indicators.

Compliance and Regulatory Reporting:

• The dataset is also an essential tool for compliance officers and those involved in regulatory reporting. With detailed data on provider performance, patient outcomes, and healthcare utilization, the dataset helps organizations meet regulatory requirements, prepare for audits, and ensure adherence to best practices. The accuracy and comprehensiveness of the data make it a trusted resource for regulatory compliance.

Data Quality and Reliability:

The All CMS Data Feeds dataset is designed with a strong emphasis on data quality and reliability. Each row of data is meticulously cleaned and aligned, ensuring that it is both accurate and consistent. This attention to detail makes the dataset a trusted resource for high-stakes applications, where data quality is critical.

Integration and Usability:

Ease of Integration:

• The dataset is provided in a CSV format, which is widely compatible with most data analysis tools and platforms. This ensures that users can easily integrate the data into their existing wo...

We are releasing data that compares the HHS Provider Relief Fund and the CMS Accelerated and Advance Payments by State and provider as of May 15, 2020. This data is already available on other websites, but this chart brings the information together into one view for comparison. You can find additional information on the Accelerated and Advance Payments at the following links:

Fact Sheet: https://www.cms.gov/files/document/Accelerated-and-Advanced-Payments-Fact-Sheet.pdf;

Zip file on providers in each state: https://www.cms.gov/files/zip/accelerated-payment-provider-details-state.zip

Medicare Accelerated and Advance Payments State-by-State information and by Provider Type: https://www.cms.gov/files/document/covid-accelerated-and-advance-payments-state.pdf.

This file was assembled by HHS via CMS, HRSA and reviewed by leadership and compares the HHS Provider Relief Fund and the CMS Accelerated and Advance Payments by State and provider as of December 4, 2020.

HHS Provider Relief Fund President Trump is providing support to healthcare providers fighting the coronavirus disease 2019 (COVID-19) pandemic through the bipartisan Coronavirus Aid, Relief, & Economic Security Act and the Paycheck Protection Program and Health Care Enhancement Act, which provide a total of $175 billion for relief funds to hospitals and other healthcare providers on the front lines of the COVID-19 response. This funding supports healthcare-related expenses or lost revenue attributable to COVID-19 and ensures uninsured Americans can get treatment for COVID-19. HHS is distributing this Provider Relief Fund money and these payments do not need to be repaid. The Department allocated $50 billion of the Provider Relief Fund for general distribution to Medicare facilities and providers impacted by COVID-19, based on eligible providers' net reimbursement. It allocated another $22 billion to providers in areas particularly impacted by the COVID-19 outbreak, rural providers, and providers who serve low-income populations and uninsured Americans. HHS will be allocating the remaining funds in the near future.

As part of the Provider Relief Fund distribution, all providers have 45 days to attest that they meet certain criteria to keep the funding they received, including public disclosure. As of May 15, 2020, there has been a total of $34 billion in attested payments. The chart only includes those providers that have attested to the payments by that date. We will continue to update this information and add the additional providers and payments once their attestation is complete.

CMS Accelerated and Advance Payments Program On March 28, 2020, to increase cash flow to providers of services and suppliers impacted by the coronavirus disease 2019 (COVID-19) pandemic, the Centers for Medicare & Medicaid Services (CMS) expanded the Accelerated and Advance Payment Program to a broader group of Medicare Part A providers and Part B suppliers. Beginning on April 26, 2020, CMS stopped accepting new applications for the Advance Payment Program, and CMS began reevaluating all pending and new applications for Accelerated Payments in light of the availability of direct payments made through HHS’s Provider Relief Fund.

Since expanding the AAP program on March 28, 2020, CMS approved over 21,000 applications totaling $59.6 billion in payments to Part A providers, which includes hospitals, through May 18, 2020. For Part B suppliers—including doctors, non-physician practitioners and durable medical equipment suppliers— during the same time period, CMS approved almost 24,000 applications advancing $40.4 billion in payments. The AAP program is not a grant, and providers and suppliers are required to repay the loan.

CMS has published AAP data, as required by the Continuing Appropriations and Other Extensions Act of 2021, on this website: https://www.cms.gov/files/document/covid-medicare-accelerated-and-advance-payments-program-covid-19-public-health-emergency-payment.pdf. Requests for additional data related to the program must be submitted through the CMS FOIA office. For more information on how to submit a FOIA request please visit our website at https://www.cms.gov/Regulations-and-Guidance/Legislation/FOIA. The PRF is administered by the Health Resources & Services Administration (HRSA). For more information on how to submit a request for unpublished program data from HRSA, please visit https://www.hrsa.gov/foia/index.html.

Provider Relief Fund Data - https://data.cdc.gov/Administrative/Provider-Relief-Fund-COVID-19-High-Impact-Payments/b58h-s9zx

Data consist of CMS Medicare data files which are restricted access and cannot be released publicly. 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. EPA cannot release CBI, or data protected by copyright, patent, or otherwise subject to trade secret restrictions. Request for access to CBI data may be directed to the dataset owner by an authorized person by contacting the party listed. It can be accessed through the following means: CMS Medicare data are available from: https://www.cms.gov/data-research/files-for-order/data-disclosures-and-data-use-agreements-duas/limited-data-set-lds with the requirement of a signed Data Use Agreement. . Weather data are available at https://prism.oregonstate.edu/. Format: The data that support the findings of this study are available from the Centers for Medicare and Medicaid Services (CMS). Restrictions apply to the availability of these data, which were provided under a Data Use Agreement specific to this study. Data are available from: https://www.cms.gov/data-research/files-for-order/data-disclosures-and-data-use-agreements-duas/limited-data-set-lds with the requirement of a signed Data Use Agreement. Data do not contain personally identifiable information but contain are classified as Limited Data Set files and their distribution require an agreement and between CMS and the requester and approval by CMS. Weather data are available at https://prism.oregonstate.edu/. Because the data do not contain identifiable private information and were not obtained through interaction or intervention with individuals, the Institutional Review Board for the University of North Carolina and the US Environmental Protection Agency Human Research Protocol Officer determined that use of this data does not constitute human subjects research. This dataset is associated with the following publication: Wade, T., and C. Herbert. Weather conditions and legionellosis: a nationwide case-crossover study among Medicare recipients. EPIDEMIOLOGY AND INFECTION. Cambridge University Press, Cambridge, UK, 152: E125, (2024).

The data used in this project cannot be shared publicly. The data were purchased from the Centers for Medicaid and Medicare Services (CMS) with specific Data Use Agreement (DUA) requirements in terms of safeguarding the confidentiality of CMS data. Researchers may download the data directly from the CMS website after completing individual requests. Information regarding data requests and download are available at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Computer-Data-and-Systems/MedicaidDataSourcesGenInfo/MAXGeneralInformation

Purpose: Develop an easy-to-use data product to facilitate comparative effectiveness research involving complex patients. Scope: Claims data can be difficult to use, requiring experience to most appropriately aggregate to the patient level and to create meaningful variables such as treatments, covariates, and endpoints. Easy to use data products will accelerate meaningful comparative effectiveness research (CER). Methods: This project used data from the Medicare Chronic Condition Data Warehouse for patients hospitalized with acute myocardial infarction (AMI) or stroke in 2007 with two-year follow-up and one-year pre-admission baseline. The project joined over 100 raw data files per condition to create research-ready person- and service-level analytic files, code templates, and macros while at the same time adding uniformity in measures of comorbid conditions and other covariates. The data product was tested in a project on statin effectiveness in older patients with multiple comorbidities. Results: A programmer/analyst with no administrative claims data experience was able to use the data product to create an analytic dataset with minimal support aside from the documentation provided. Analytic dataset creation used the conditions, procedures, and timeline macros provided. The data structure created for AMI adapted successfully for stroke. Complexity increased and statin treatment decreased with age. The two-year survival benefit of statins post-AMI increased with age. Conclusion: Claims data can be made more user-friendly for CER research on complex conditions. The data product should be expanded by refreshing the cohort and increasing follow-up. Action is warranted to increase the rate of statin use among the oldest patients. Data Access: These data are not available from ICPSR. The data cannot be made publicly available. Data are stored on University of Iowa College of Public Health secure servers, and may be used only for projects covered within the aims of the original research protocol and Centers for Medicare and Medicaid Services (CMS)-approved data use agreement. Data sharing is allowed only for research protocols approved under data re-use requests by the CMS privacy board. The CMS process for data re-use requests is described at Research Data Assistance Center (ResDac). Please note that as of May 2013, the DUA covering this work is set to expire February 1, 2014. Thereafter, per the terms of the DUA, datasets created for this project may not be available. User guides are available from ICPSR for detailed descriptions of the data products, including a user guide for Acute Myocardial Infarction (AMI) Analytic Files and a user guide for Stroke and Transient Ischemic Attack (TIA) Analytic Files. Data dictionaries are available upon request. Please contact Nick Rudzianski (nicholas-rudzianski@uiowa.edu or 319-335-9783) for more information.

State-reported data on Medicaid and CHIP eligibility renewals that reflect the outcomes of previously pending renewals three months after the renewal was due and also any corrections to the original renewal data submitted to CMS. See here for original renewal data.
CMS renewal data specifications require states to update and submit to CMS their monthly renewal outcome metrics - metric 5 data and its submetrics (monthly metrics 5a, 5a(1), 5a(2), 5b, 5c, and 5d) - after the original monthly report submission. The “updated” renewal data reflect the outcomes of renewals previously reported as pending (monthly metric 5d of the original monthly report) as of three months after the renewal was due. For more information about this data set and considerations for users when reviewing, please see the Medicaid and CHIP Unwinding: Data Sources and Metrics Definitions Overview found here.
Sources:
(1) March 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on March 05, 2024, representing the updated disposition of renewals due in March 2023 as of June 2023. April 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on March 05, 2024, representing the updated disposition of renewals due in April 2023 as of July 2023. May 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on March 05, 2024, representing the updated disposition of renewals due in May 2023 as of August 2023. June 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on March 05, 2024, representing the updated disposition of renewals due in June 2023 as of September 2023. July 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on March 05, 2024, representing the updated disposition of renewals due in July 2023 as of October 2023. August 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on March 05, 2024, representing the updated disposition of renewals due in August 2023 as of November 2023. September 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on April 02, 2024, representing the updated disposition of renewals due in September 2023 as of December 2023. October 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on April 02, 2024, representing the updated disposition of renewals due in October 2023 as of January 2024. November 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on May 07, 2024, representing the updated disposition of renewals due in November 2023 as of February 2024. December 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on June 11, 2024, representing the updated disposition of renewals due in December 2023 as of March 2024. New Hampshire’s December 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on April 09, 2024, representing the updated disposition of renewals due in December 2023 as of March 2024. New York’s December 2023 state Medicaid and CHIP Renewal and Termination Data for the Unwinding Data Report pulled on April 22, 2024, representing the updated disposition of renewals due in December 2023 as of March 2024. January 2024 state Medicaid and CHIP Renewal and Termination Data for t

The global Content Management Systems (CMS) market size was valued at USD 5,413 million in 2025 and is projected to reach USD 10,861 million by 2033, exhibiting a CAGR of 7.7% during the forecast period (2025-2033). The growing demand for efficient and user-friendly content management solutions, coupled with the increasing adoption of cloud-based platforms, is driving market growth. Additionally, the surge in digital content creation, particularly in industries such as media and entertainment, academia, and e-commerce, further fuels market expansion. The market landscape is fragmented, with established players such as Adobe Acrobat Reader, VideoLan, and Foxit Reader holding significant market shares. However, the rise of cloud-based CMS providers, such as WP Engine, PDFfiller, and PowerDMS, is challenging the dominance of traditional desktop-based solutions. Regional analysis indicates that North America holds the largest market share due to the presence of numerous content-driven businesses. Asia Pacific is expected to be the fastest-growing region, driven by the increasing internet penetration and digital content consumption in emerging economies.

The Consent Management System (CMS) market is experiencing robust growth, driven by the increasing global adoption of stringent data privacy regulations like GDPR, CCPA, and others. The market, estimated at $2 billion in 2025, is projected to maintain a healthy Compound Annual Growth Rate (CAGR) of 15% throughout the forecast period (2025-2033). This expansion is fueled by the rising need for organizations across various sectors—including BFSI, IT & Telecom, Government, Healthcare, Higher Education, and Retail & E-commerce—to ensure compliance and manage user consent effectively. The software segment currently holds the largest market share, reflecting the preference for automated solutions for efficient consent management. However, the services segment is poised for significant growth, driven by the increasing demand for professional services to navigate the complexities of data privacy regulations and implement effective CMS strategies. Key players like OneTrust, TrustArc, and IBM are actively shaping the market landscape through continuous innovation and strategic partnerships, but the market also accommodates smaller, specialized players catering to niche requirements. Geographic expansion is another key driver, with North America and Europe currently dominating the market share, but regions like Asia-Pacific are witnessing accelerated growth owing to rising digitalization and growing awareness of data privacy. The restraints to market growth primarily stem from the complexities of implementing and maintaining CMS solutions, coupled with the ongoing evolution of data privacy regulations. The high initial investment costs associated with implementing these systems and the need for continuous updates to adapt to evolving regulatory landscapes can pose challenges for some organizations, particularly smaller businesses. However, the increasing awareness of potential legal ramifications and financial penalties for non-compliance is expected to drive increased adoption and mitigate the effect of these restraints. The long-term outlook remains highly positive, fueled by increasing data volumes, sophisticated user preferences regarding data control, and the continuous evolution of data privacy regulations worldwide. The emergence of innovative technologies such as AI and machine learning further promises to enhance the capabilities of CMS solutions and further expand the market potential.

The dataset consists of simulated events of electron-positron pairs (e⁺e⁻) with flat transverse momentum p_T distribution p_T ∈ [1,200] GeV, with Phase 2 conditions, 200 pileup, V11 geometry, HLT TDR Summer20 campaign The original dataset (CMS-internal).

This derived dataset in ROOT format contains generator-level particle and simulated detector information. More information about how the dataset is derived is available at this TWiki (CMS-internal).

A description of each variable is below.

Variable	Description	Type
run	Run number	int
event	Event number	int
lumi	Luminosity section	int
gen_n	Number of primary generated particles	int
gen_PUNumInt	Number of pileup interactions	int
gen_TrueNumInt	Number of true interactions	float
vtx_x	Simulated primary vertex x position in cm	float
vtx_y	Simulated primary vertex y position in cm	float
vtx_z	Simulated primary vertex z position in cm	float
gen_eta	Primary generated particle pseudorapidity η	vector
gen_phi	Primary generated particle azimuthal angle ϕ	vector
gen_pt	Primary generated particle transverse momentum pT in GeV	vector
gen_energy	Primary generated particle energy in GeV	vector
gen_charge	Initial generated particle charge	vector
gen_pdgid	Primary generated particle PDG ID	vector
gen_status	Primary generated particle generator status	vector
gen_daughters	Primary generated particle daughters (empty)	vector
genpart_eta	Primary and secondary generated particle pseudorapidity η	vector
genpart_phi	Primary and secondary generated particle azimuthal angle ϕ	vector
genpart_pt	Primary and secondary generated particle transverse momentum pT in GeV	vector
genpart_energy	Primary and secondary generated particle energy in GeV	vector
genpart_dvx	Primary and secondary generated particle decay vertex x position in cm	vector
genpart_dvy	Primary and secondary generated particle decay vertex y position in cm	vector
genpart_dvz	Primary and secondary generated particle decay vertex z position in cm	vector
genpart_ovy	Primary and secondary generated particle original vertex y position in cm	vector
genpart_ovz	Primary and secondary generated particle original vertex z position in cm	vector
genpart_mother	Primary and secondary generated particle parent particle index (-1 indicates no parent)	vector
genpart_exphi	Primary and secondary generated particle azimuthal angle ϕ extrapolated to the corresponding HGCAL coordinate	vector
genpart_exeta	Primary and secondary generated particle pseudorapidity η extrapolated to the corresponding HGCAL coordinate	vector
genpart_exx	Primary and secondary generated particle decay vertex x extrapolated to the corresponding HGCAL coordinate	vector
genpart_exy	Primary and secondary generated particle decay vertex y extrapolated to the corresponding HGCAL coordinate	vector
genpart_fbrem	Primary and secondary generated particle decay vertex z extrapolated to the corresponding HGCAL coordinate	vector
genpart_pid	Primary and secondary generated particle PDG ID	vector
genpart_gen	Index of associated primary generated particle	vector
genpart_reachedEE	Primary and secondary generated particle flag: 2 indicates that the particle reached the HGCAL, 1 indicates the particle reached the barrel calorimeter, and 0 indicates other cases	vector
genpart_fromBeamPipe	Deprecated variable, always true	vector
genpart_posx	Primary and secondary generated particle position x coordinate in cm	vector
genpart_posy	Primary and secondary generated particle position y coordinate in cm	vector
genpart_posz	Primary and secondary generated particle position z coordinate in cm	vector
ts_n	Number of trigger sums	int
ts_id	Trigger sum ID	vector
ts_subdet	Trigger sum subdetector	vector
ts_zside	Trigger sum endcap (plus or minus endcap)	vector
ts_layer	Trigger sum layer ID	vector
ts_wafer	Trigger sum wafer ID	vector
ts_wafertype	Trigger sum wafer type: 0 indicates fine divisions of wafer with 120 μm thick silicon, 1 indicates coarse divisions of wafer with 200 μm thick silicon, and 2 indicates coarse divisions of wafer with 300 μm thick silicon	vector
ts_data	Trigger sum ADC value	vector
ts_pt	Trigger sum transverse momentum in GeV	vector
ts_mipPt	Trigger sum energy in units of transverse MIP	vector
ts_energy	Trigger sum energy in GeV	vector
ts_eta	Trigger sum pseudorapidity η	vector
ts_phi	Trigger sum azimuthal angle ϕ	vector
ts_x	Trigger sum x position in cm	vector
ts_y	Trigger sum y position in cm	vector
ts_z	Trigger sum z position in cm	vector
tc_n	Number of trigger

Content Management System (CMS) Software Market Outlook

The global Content Management System (CMS) Software market size was valued at approximately $47 billion in 2023 and is projected to reach $97 billion by 2032, growing at a compound annual growth rate (CAGR) of 8.5% during the forecast period. The growth of this market is primarily driven by the increasing digitalization efforts across various industries and the rising need for managing vast amounts of data efficiently.

The proliferation of digital content across multiple platforms is a significant growth factor for the CMS software market. As businesses expand their digital presence to reach a broader audience, the necessity for robust CMS solutions becomes more apparent. Organizations are increasingly adopting CMS software to manage, store, and disseminate content seamlessly across various channels. This trend is evident in sectors like retail, healthcare, and media and entertainment, where the volume and complexity of content are continually growing.

Moreover, the growing demand for personalized content is driving the need for advanced CMS software. Modern consumers expect personalized experiences, and businesses are leveraging CMS solutions to curate and deliver customized content based on user preferences, behavior, and demographics. This capability not only enhances user engagement but also boosts customer retention and brand loyalty, thereby contributing to the market's expansion. Additionally, advancements in artificial intelligence (AI) and machine learning (ML) are enhancing the functionality of CMS software, making it more intelligent and capable of automating complex tasks, further propelling market growth.

Another crucial growth factor is the increasing emphasis on regulatory compliance and data security. With stringent data protection regulations such as GDPR and CCPA, businesses are under pressure to manage content securely and ensure compliance. CMS software with robust security features helps organizations in safeguarding sensitive information and maintaining regulatory compliance. This necessity is particularly pronounced in industries like BFSI and healthcare, where data security is paramount. Consequently, the demand for secure and compliant CMS solutions is witnessing a substantial rise.

In the realm of content management, WYSIWYG Editors Software plays a pivotal role in simplifying the creation and editing of web content. These editors allow users to design web pages without needing to write code manually, offering a 'What You See Is What You Get' interface. This feature is particularly beneficial for businesses aiming to maintain a dynamic and engaging online presence without extensive technical expertise. By enabling non-technical users to create and manage content with ease, WYSIWYG editors enhance the efficiency of content management processes. As a result, organizations can focus on strategic content initiatives, ensuring that their digital platforms are both visually appealing and functionally robust.

From a regional perspective, North America holds a significant share of the CMS software market, primarily due to the high adoption rate of advanced technologies and the presence of leading market players. The region's mature IT infrastructure and the increasing demand for digital content management solutions across various industries, including retail, healthcare, and media, are key driving factors. Additionally, the Asia Pacific region is expected to witness substantial growth during the forecast period, driven by rapid digital transformation, increasing internet penetration, and the growing adoption of CMS solutions by small and medium enterprises (SMEs) in emerging economies like India and China.

Component Analysis

The CMS software market is segmented by component into software and services. The software segment dominates the market, driven by the increasing demand for robust and scalable content management solutions. Companies across various sectors are investing heavily in CMS software to streamline their content management processes, enhance operational efficiency, and provide seamless digital experiences to their customers. The software solutions segment includes web content management, document management, digital asset management, and social media management software, each catering to different aspects of content management, thereby broadening the scope of the market.

On the other hand,

The global next-generation CMS market is projected to experience significant growth over the forecast period, driven by the increasing adoption of headless and hybrid headless CMS platforms. The growing demand for personalized, omnichannel experiences, the need for improved content management capabilities, and the advancements in artificial intelligence (AI) and machine learning (ML) are the major factors driving the market growth. The market is expected to witness a CAGR of XX% during the forecast period, reaching a market size of USD XXX million by 2033. Key trends in the next-generation CMS market include the rise of headless and hybrid headless CMS platforms, the increasing use of AI and ML to automate content management tasks, the integration of CMS with marketing automation and e-commerce platforms, and the adoption of cloud-based CMS solutions. Major companies operating in the market include Crownpeak, Optimizely, Acquia, Magnolia, Sitecore, Progress Software, and Umbraco. The market is highly competitive with a fragmented vendor landscape, and key players are focusing on product innovation and strategic partnerships to gain a competitive edge.

A database based on a random sample of the noninstitutionalized population of the United States, developed for the purpose of studying the effects of demographic and socio-economic characteristics on differentials in mortality rates. It consists of data from 26 U.S. Current Population Surveys (CPS) cohorts, annual Social and Economic Supplements, and the 1980 Census cohort, combined with death certificate information to identify mortality status and cause of death covering the time interval, 1979 to 1998. The Current Population Surveys are March Supplements selected from the time period from March 1973 to March 1998. The NLMS routinely links geographical and demographic information from Census Bureau surveys and censuses to the NLMS database, and other available sources upon request. The Census Bureau and CMS have approved the linkage protocol and data acquisition is currently underway. The plan for the NLMS is to link information on mortality to the NLMS every two years from 1998 through 2006 with research on the resulting database to continue, at least, through 2009. The NLMS will continue to incorporate data from the yearly Annual Social and Economic Supplement into the study as the data become available. Based on the expected size of the Annual Social and Economic Supplements to be conducted, the expected number of deaths to be added to the NLMS through the updating process will increase the mortality content of the study to nearly 500,000 cases out of a total number of approximately 3.3 million records. This effort would also include expanding the NLMS population base by incorporating new March Supplement Current Population Survey data into the study as they become available. Linkages to the SEER and CMS datasets are also available. Data Availability: Due to the confidential nature of the data used in the NLMS, the public use dataset consists of a reduced number of CPS cohorts with a fixed follow-up period of five years. NIA does not make the data available directly. Research access to the entire NLMS database can be obtained through the NIA program contact listed. Interested investigators should email the NIA contact and send in a one page prospectus of the proposed project. NIA will approve projects based on their relevance to NIA/BSR''s areas of emphasis. Approved projects are then assigned to NLMS statisticians at the Census Bureau who work directly with the researcher to interface with the database. A modified version of the public use data files is available also through the Census restricted Data Centers. However, since the database is quite complex, many investigators have found that the most efficient way to access it is through the Census programmers. * Dates of Study: 1973-2009 * Study Features: Longitudinal * Sample Size: ~3.3 Million Link: *ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00134

Note: After November 1, 2024, this dataset will no longer be updated due to a transition in NHSN Hospital Respiratory Data reporting that occurred on Friday, November 1, 2024. For more information on NHSN Hospital Respiratory Data reporting, please visit https://www.cdc.gov/nhsn/psc/hospital-respiratory-reporting.html.

Due to a recent update in voluntary NHSN Hospital Respiratory Data reporting that occurred on Wednesday, October 9, 2024, reporting levels and other data displayed on this page may fluctuate week-over-week beginning Friday, October 18, 2024. For more information on NHSN Hospital Respiratory Data reporting, please visit https://www.cdc.gov/nhsn/psc/hospital-respiratory-reporting.html. Find more information about the updated CMS requirements: https://www.federalregister.gov/documents/2024/08/28/2024-17021/medicare-and-medicaid-programs-and-the-childrens-health-insurance-program-hospital-inpatient. 

This dataset represents weekly respiratory virus-related hospitalization data and metrics aggregated to national and state/territory levels reported during two periods: 1) data for collection dates from August 1, 2020 to April 30, 2024, represent data reported by hospitals during a mandated reporting period as specified by the HHS Secretary; and 2) data for collection dates beginning May 1, 2024, represent data reported voluntarily by hospitals to CDC’s National Healthcare Safety Network (NHSN). NHSN monitors national and local trends in healthcare system stress and capacity for up to approximately 6,000 hospitals in the United States. Data reported represent aggregated counts and include metrics capturing information specific to COVID-19- and influenza-related hospitalizations, hospital occupancy, and hospital capacity. Find more information about reporting to NHSN at: https://www.cdc.gov/nhsn/psc/hospital-respiratory-reporting.html.

Source: COVID-19 hospitalization data reported to CDC’s National Healthcare Safety Network (NHSN).

• Data source description (updated October 18, 2024): As of October 9, 2024, Hospital Respiratory Data (HRD; formerly Respiratory Pathogen, Hospital Capacity, and Supply data or ‘COVID-19 hospital data’) are reported to HHS through CDC’s National Healthcare Safety Network based on updated requirements from the Centers for Medicare and Medicaid Services (CMS). These data are voluntarily reported to NHSN as of May 1, 2024 until November 1, 2024, at which time CMS will require acute care and critical access hospitals to electronically report information via NHSN about COVID-19, Influenza, and RSV, hospital bed census and capacity, and limited patient demographic information, including age. Data for collection dates prior to May 1, 2024, represent data reported during a previously mandated reporting period as specified by the HHS Secretary. Data for collection dates May 1, 2024, and onwards represent data reported voluntarily to NHSN; as such, data included represents reporting hospitals only for a given week and might not be complete or representative of all hospitals. NHSN monitors national and local trends in healthcare system stress and capacity for approximately 6,000 hospitals in the United States. Data reported by hospitals to NHSN represent aggregated counts and include metrics capturing information specific to hospital capacity, occupancy, hospitalizations, and admissions. Find more information about reporting to NHSN: https://www.cdc.gov/nhsn/psc/hospital-respiratory-reporting.html. Find more information about the updated CMS requirements: https://www.federalregister.gov/documents/2024/08/28/2024-17021/medicare-and-medicaid-programs-and-the-childrens-health-insurance-program-hospital-inpatient. 
• Data quality: While CDC reviews reported data for completeness and errors and corrects those found, some reporting errors might still exist within the data. CDC and partners work with reporters to correct these errors and update the data in subse

Video CMS Software Market Outlook

The global Video CMS Software market size is projected to rise from USD 3.5 billion in 2023 to USD 9.2 billion by 2032, reflecting a compound annual growth rate (CAGR) of 11.2%. This impressive growth can be attributed to a variety of factors including the increasing demand for video content across various sectors, the rise of digital marketing strategies, and advancements in video streaming technologies. As organizations continue to prioritize video as a key component of their communication and marketing strategies, the need for sophisticated content management systems tailored to video is expected to surge.

One of the primary growth drivers of the Video CMS Software market is the exponential rise in video consumption both on personal devices and through corporate channels. With the proliferation of high-speed internet and the ubiquity of smartphones, video has emerged as a dominant medium for both entertainment and information dissemination. This trend is not only limited to consumer behavior but extends to corporate environments where video is increasingly used for training, corporate communication, and marketing. This surge in video content necessitates robust management systems capable of handling large volumes of video data, which in turn drives demand for Video CMS Software.

Another significant growth factor is the increasing utilization of video content in educational settings. The COVID-19 pandemic has accelerated the adoption of remote learning, further highlighting the need for effective video content management solutions in the education sector. Schools, colleges, and universities are increasingly leveraging video CMS software to manage, store, and distribute educational content, thereby enhancing the learning experience. This shift towards digital education is expected to have a long-term impact, sustaining the demand for Video CMS Software in the foreseeable future.

Moreover, the corporate sector's growing reliance on video for internal communication, training, and marketing purposes is also a key driver for the market. Companies are increasingly recognizing the power of video to engage employees, enhance brand visibility, and communicate complex information effectively. Video CMS software helps enterprises streamline their video content management, ensure security, and optimize delivery, thereby improving operational efficiency and effectiveness. This has led to substantial investments in advanced video CMS solutions by large corporations as well as small and medium enterprises.

The evolution of Fee-based SaaS Online Video Platform solutions has been pivotal in transforming how businesses manage and monetize their video content. These platforms offer a subscription-based model that provides organizations with access to a suite of video management tools without the need for significant upfront investments in infrastructure. This model is particularly beneficial for businesses looking to scale their video operations rapidly and efficiently. By leveraging a fee-based SaaS approach, companies can focus on content creation and distribution while relying on the platform provider for maintenance, updates, and security. This not only reduces operational costs but also ensures that businesses have access to the latest features and technologies, keeping them competitive in a fast-paced digital landscape.

From a regional perspective, North America is expected to dominate the Video CMS Software market, driven by the presence of key market players, high internet penetration, and the rapid adoption of advanced technologies. Asia Pacific is anticipated to witness significant growth due to the increasing internet user base, growth in the e-learning sector, and rising digitalization efforts by enterprises. Europe is also expected to see considerable growth attributed to technological advancements and high investments in digital infrastructure across the region. Other regions like Latin America and the Middle East & Africa are expected to grow at a steady pace, driven by increasing digital adoption and expanding internet access.

Deployment Type Analysis

The Video CMS Software market is segmented into On-Premises and Cloud-Based deployments. On-Premises deployment refers to the installation and hosting of the software on the userÂ’s own servers. This type of deployment is preferred by organizations that require greater control over their data and have stringent security requirements

The Fiscal Intermediary Shared System (FISS) Attending and Rendering dataset provides a list of those attending and rendering physicians for the FISS. FISS edits require that the Line Item Rendering Physician information be transmitted when providers submit a combined claim. Claims that include both facility and professional components, need to report the rendering physician or other practitioner at the line level if it differs from the rendering physician/practitioner reported at the claim level.

Note: This full dataset contains more records than most spreadsheet programs can handle, which will result in an incomplete load of data. Use of a database or statistical software is required.

Title	CMS: LiDAR Biomass Improved for High Biomass Forests, Sonoma County, CA, USA, 2013
Description	This data set provides estimates of above-ground woody biomass and uncertainty at 30-m spatial resolution for Sonoma County, California, USA, for the nominal year 2013. Biomass estimates, megagrams of biomass per hectare (Mg/ha), were generated using a combination of airborne LiDAR data and field plot measurements with a parametric modeling approach. The relationship between field estimated and airborne LiDAR estimated aboveground biomass density is represented as a parametric model that predicts biomass as a function of canopy cover and 50th percentile and 90th percentile LiDAR heights at a 30-m resolution. To estimate uncertainty, the biomass model was re-fit 1,000 times through a sampling of the variance-covariance matrix of the fitted parametric model. This produced 1,000 estimates of biomass per pixel. The 5th and 95th percentiles, and the standard deviation of these pixel biomass estimates, were calculated.
Date
Media Type	ATOM | SRU
Metadata	ISO 19139 | ISO 19139-2

The NADAC Weekly Comparison identifies the drug products with current NADAC rates that are replaced with new NADAC rates. Other changes (e.g. NDC additions and terminations) to the NADAC file are not reflected in this comparison. Note: Effective Date was not recorded in the dataset until 6/7/2017

The Next Generation Content Management System (CMS) market has evolved significantly, responding to the shifting demands of businesses seeking more flexible, efficient, and powerful tools to manage their digital content. In today's fast-paced digital landscape, organizations require CMS solutions that not only facil

Casino Management System (CMS) Market Outlook

The global casino management system (CMS) market size was valued at approximately $6.5 billion in 2023 and is projected to reach around $12.3 billion by 2032, growing at a compound annual growth rate (CAGR) of 7.1% during the forecast period. The growth of the CMS market is primarily driven by the increasing demand for advanced management solutions to enhance operational efficiency and customer experience in casinos across the globe. Innovations in digital technologies, coupled with the rising number of casinos, especially in emerging economies, are fostering the expansion of the CMS market.

One of the key growth factors in the CMS market is the rapid technological advancements in the gaming and entertainment industry. With the proliferation of digital platforms and the increasing penetration of internet connectivity, casinos are integrating advanced management systems to streamline their operations. The adoption of sophisticated analytics, IoT devices, and AI-driven technologies in CMS solutions allows casinos to enhance player tracking, optimize gaming floor layouts, and improve overall customer service, thereby boosting market growth. Additionally, the integration of these technologies helps in ensuring compliance with regulatory requirements, further encouraging the adoption of CMS solutions.

The growing emphasis on security and surveillance within casinos is another significant factor contributing to the market's expansion. Casinos require robust security solutions to protect their assets and ensure the safety of their patrons. CMS solutions offer comprehensive security and surveillance modules that help in monitoring gaming floors, preventing fraud, and ensuring regulatory compliance. The rising incidents of fraudulent activities and security breaches in casinos have heightened the need for advanced CMS solutions, thus driving the market growth. Furthermore, the ability of CMS solutions to integrate with existing security infrastructure makes them an attractive option for casino operators looking to enhance their security measures.

Another driving force for the CMS market is the increasing focus on enhancing customer experience and engagement. Casinos are leveraging CMS solutions to gather valuable insights into player preferences and behaviors, which in turn helps in creating personalized gaming experiences. The use of data analytics and AI-powered tools enables casino operators to design targeted marketing campaigns, reward loyal customers, and optimize gaming strategies. This emphasis on customer-centric approaches is expected to fuel the demand for CMS solutions, as casinos strive to retain existing customers and attract new ones in a competitive landscape.

From a regional perspective, North America remains a dominant player in the CMS market, with a significant share attributed to the presence of numerous large-scale casinos and the high adoption rate of advanced technologies. However, the Asia Pacific region is witnessing the fastest growth, driven by the increasing number of casinos and the rapid expansion of the gaming industry in countries like China, Japan, and Singapore. The rising disposable incomes and changing entertainment preferences in these regions are further propelling market growth. Meanwhile, Europe and Latin America are also seeing notable developments in the casino sector, contributing to the overall growth of the CMS market.

Component Analysis

When analyzing the casino management system market by component, it is evident that the software segment holds a significant share and is expected to continue its dominance over the forecast period. The software component of CMS solutions plays a crucial role in automating various casino operations, including player tracking, accounting, and analytics. The continuous advancements in software technologies, such as AI and machine learning, have enhanced the capabilities of CMS solutions, enabling casinos to make data-driven decisions and improve operational efficiency. The growing demand for customized and scalable software solutions that can be easily integrated with existing casino infrastructure is further driving the growth of this segment.

Hardware components are also essential to the effective functioning of casino management systems, although their growth is relatively moderate compared to software. Hardware includes a range of devices such as servers, kiosks, and surveillance cameras that support the implementation of CMS solutions. The increasing focus on security and surveillance in casinos is driving the demand for advanced hardware sy

Content Management Systems Market Outlook

The global Content Management Systems (CMS) market has been demonstrating a robust growth trajectory, with a market size estimated to reach USD 27.3 billion in 2023, and anticipated to burgeon to USD 51.2 billion by 2032, reflecting a significant compound annual growth rate (CAGR) of 7.2% during the forecast period. One of the primary growth factors for this market is the increasing digitalization across various industries, as businesses and organizations seek to enhance their online presence and streamline content operations. The demand for efficient and user-friendly CMS solutions is surging as enterprises need to manage vast amounts of content across multiple digital platforms.

One of the major growth drivers in the CMS market is the rising adoption of digital marketing strategies by businesses worldwide. As companies strive to create engaging and personalized customer experiences, the need for advanced CMS platforms that can handle dynamic content and support multichannel marketing efforts becomes crucial. Additionally, the integration of Artificial Intelligence (AI) in CMS solutions is transforming content management by offering automation capabilities, improved content personalization, and insightful analytics. AI-powered CMS platforms are enabling businesses to deliver tailored content to their target audiences, thus enhancing user engagement and conversion rates.

Another factor propelling the growth of the CMS market is the increasing emphasis on digital transformation strategies across various industries. Organizations are investing in CMS solutions to streamline their content workflows, improve collaboration, and optimize content delivery. The shift towards remote working and online collaboration, accelerated by the COVID-19 pandemic, has further heightened the demand for cloud-based CMS platforms that facilitate seamless access to content from any location. This trend is particularly pronounced in sectors like education, healthcare, and media, where digital content delivery is critical.

The regulatory landscape and compliance requirements are also shaping the CMS market dynamics. With stringent data protection regulations such as the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the United States, organizations are compelled to adopt CMS solutions that offer robust data security and privacy features. This has led to the development of CMS platforms that prioritize data governance and offer comprehensive compliance management tools, thereby gaining traction among enterprises looking to safeguard sensitive information.

Regionally, the CMS market exhibits varied growth patterns, with North America leading in terms of market share due to the presence of major technology companies and a high rate of technology adoption. The Asia Pacific region is expected to witness the fastest growth, driven by the increasing digitalization of businesses and the rapid expansion of the internet and smartphone penetration. Europe too is a significant market for CMS, bolstered by the region's focus on data protection and digital transformation initiatives. Latin America and the Middle East & Africa, though smaller in terms of market size, are gradually adopting CMS technologies as businesses in these regions recognize the benefits of digital content management.

Component Analysis

The CMS market is segmented into software and services components, each playing a distinct role in the overall content management ecosystem. The software segment forms the core of the CMS market, encompassing the wide range of platforms and applications that enable users to create, manage, and publish digital content. This segment is characterized by a plethora of offerings, from enterprise-grade solutions like WordPress, Joomla, and Drupal to niche platforms tailored for specific use cases. The continuous evolution of CMS software is driven by the need for advanced features such as mobile responsiveness, SEO optimization, and multilingual support. Moreover, the integration of AI and machine learning capabilities is adding a new dimension to CMS software, enabling predictive content delivery and enhanced user engagement.

On the other hand, the services segment in the CMS market covers consulting, implementation, training, and support services that complement the software offerings. These services are critical in ensuring the successful deployment and operation of CMS platforms, especially for organizations lacking in-house technical expertise. As businesses increasingly seek to optimize their con