Graph and download economic data for Real Health Expenditures, Blended Account Basis (HLTHSCREXBLEND) from 2000 to 2021 about healthcare, health, expenditures, real, and USA.

Graph and download economic data for Real Health Services Expenditures, MEPS Account Basis (HLTHSEREXMEPS) from 2000 to 2021 about healthcare, health, expenditures, services, real, and USA.

Graph and download economic data for Real Medical Services Expenditures by Provider: Nursing Homes (NURHOMREXHCSA) from 2000 to 2021 about nursing homes, nursing, healthcare, medical, health, expenditures, services, real, and USA.

This statistic displays the year-on-year growth of health expenditure per capita, in real terms, in Romania from 2006 to 2015. Health expenditure per capita, in real terms, fell from 2.9 percent in 2014 to -1.4 percent in 2015. The largest annual growth was experienced in 2004 when total health expenditure grew by 11.8 percent on 2003. In 2013, the share of public expenditure on healthcare amounted to 79.7 percent.

The dataset contains fake and real news. There are 16898 unique rows that points out the numbers of news as well. The dataset is merged from two datasets one is from different source of CBC news (link: https://zenodo.org/record/4722470) and other is from different web portals (link: https://zenodo.org/record/4282522). Data Description: Text: Text contains the news that is either fake or real. Outcome: Contains either fake or real which is the status of the news. Data source link 1: https://www.kaggle.com/ryanxjhan/cbc-news-coronavirusarticles-march-26 Data source link 2: https://zenodo.org/record/4722470

IntroductionObtaining real-world data from routine clinical care is of growing interest for scientific research and personalized medicine. Despite the abundance of medical data across various facilities — including hospitals, outpatient clinics, and physician practices — the intersectoral exchange of information remains largely hindered due to differences in data structure, content, and adherence to data protection regulations. In response to this challenge, the Medical Informatics Initiative (MII) was launched in Germany, focusing initially on university hospitals to foster the exchange and utilization of real-world data through the development of standardized methods and tools, including the creation of a common core dataset. Our aim, as part of the Medical Informatics Research Hub in Saxony (MiHUBx), is to extend the MII concepts to non-university healthcare providers in a more seamless manner to enable the exchange of real-world data among intersectoral medical sites.MethodsWe investigated what services are needed to facilitate the provision of harmonized real-world data for cross-site research. On this basis, we designed a Service Platform Prototype that hosts services for data harmonization, adhering to the globally recognized Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) international standard communication format and the Observational Medical Outcomes Partnership (OMOP) common data model (CDM). Leveraging these standards, we implemented additional services facilitating data utilization, exchange and analysis. Throughout the development phase, we collaborated with an interdisciplinary team of experts from the fields of system administration, software engineering and technology acceptance to ensure that the solution is sustainable and reusable in the long term.ResultsWe have developed the pre-built packages “ResearchData-to-FHIR,” “FHIR-to-OMOP,” and “Addons,” which provide the services for data harmonization and provision of project-related real-world data in both the FHIR MII Core dataset format (CDS) and the OMOP CDM format as well as utilization and a Service Platform Prototype to streamline data management and use.ConclusionOur development shows a possible approach to extend the MII concepts to non-university healthcare providers to enable cross-site research on real-world data. Our Service Platform Prototype can thus pave the way for intersectoral data sharing, federated analysis, and provision of SMART-on-FHIR applications to support clinical decision making.

IntroductionObtaining real-world data from routine clinical care is of growing interest for scientific research and personalized medicine. Despite the abundance of medical data across various facilities — including hospitals, outpatient clinics, and physician practices — the intersectoral exchange of information remains largely hindered due to differences in data structure, content, and adherence to data protection regulations. In response to this challenge, the Medical Informatics Initiative (MII) was launched in Germany, focusing initially on university hospitals to foster the exchange and utilization of real-world data through the development of standardized methods and tools, including the creation of a common core dataset. Our aim, as part of the Medical Informatics Research Hub in Saxony (MiHUBx), is to extend the MII concepts to non-university healthcare providers in a more seamless manner to enable the exchange of real-world data among intersectoral medical sites.MethodsWe investigated what services are needed to facilitate the provision of harmonized real-world data for cross-site research. On this basis, we designed a Service Platform Prototype that hosts services for data harmonization, adhering to the globally recognized Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) international standard communication format and the Observational Medical Outcomes Partnership (OMOP) common data model (CDM). Leveraging these standards, we implemented additional services facilitating data utilization, exchange and analysis. Throughout the development phase, we collaborated with an interdisciplinary team of experts from the fields of system administration, software engineering and technology acceptance to ensure that the solution is sustainable and reusable in the long term.ResultsWe have developed the pre-built packages “ResearchData-to-FHIR,” “FHIR-to-OMOP,” and “Addons,” which provide the services for data harmonization and provision of project-related real-world data in both the FHIR MII Core dataset format (CDS) and the OMOP CDM format as well as utilization and a Service Platform Prototype to streamline data management and use.ConclusionOur development shows a possible approach to extend the MII concepts to non-university healthcare providers to enable cross-site research on real-world data. Our Service Platform Prototype can thus pave the way for intersectoral data sharing, federated analysis, and provision of SMART-on-FHIR applications to support clinical decision making.

Real World Evidence Solutions Market size was valued at USD 1.30 Billion in 2024 and is projected to reach USD 3.71 Billion by 2031, growing at a CAGR of 13.92% during the forecast period 2024-2031.

Global Real World Evidence Solutions Market Drivers

The market drivers for the Real World Evidence Solutions Market can be influenced by various factors. These may include:

Growing Need for Evidence-Based Healthcare: Real-world evidence (RWE) is becoming more and more important in healthcare decision-making, according to stakeholders such as payers, providers, and regulators. In addition to traditional clinical trial data, RWE solutions offer important insights into the efficacy, safety, and value of healthcare interventions in real-world situations. Growing Use of RWE by Pharmaceutical Companies: RWE solutions are being used by pharmaceutical companies to assist with market entry, post-marketing surveillance, and drug development initiatives. Pharmaceutical businesses can find new indications for their current medications, improve clinical trial designs, and convince payers and providers of the worth of their products with the use of RWE. Increasing Priority for Value-Based Healthcare: The emphasis on proving the cost- and benefit-effectiveness of healthcare interventions in real-world settings is growing as value-based healthcare models gain traction. To assist value-based decision-making, RWE solutions are essential in evaluating the economic effect and real-world consequences of healthcare interventions. Technological and Data Analytics Advancements: RWE solutions are becoming more capable due to advances in machine learning, artificial intelligence, and big data analytics. With the use of these technologies, healthcare stakeholders can obtain actionable insights from the analysis of vast and varied datasets, including patient-generated data, claims data, and electronic health records. Regulatory Support for RWE Integration: RWE is being progressively integrated into regulatory decision-making processes by regulatory organisations including the European Medicines Agency (EMA) and the U.S. Food and Drug Administration (FDA). The FDA's Real-World Evidence Programme and the EMA's Adaptive Pathways and PRIority MEdicines (PRIME) programme are two examples of initiatives that are making it easier to incorporate RWE into regulatory submissions and drug development. Increasing Emphasis on Patient-Centric Healthcare: The value of patient-reported outcomes and real-world experiences in healthcare decision-making is becoming more widely acknowledged. RWE technologies facilitate the collection and examination of patient-centered data, offering valuable insights into treatment efficacy, patient inclinations, and quality of life consequences. Extension of RWE Use Cases: RWE solutions are being used in medication development, post-market surveillance, health economics and outcomes research (HEOR), comparative effectiveness research, and market access, among other healthcare fields. The necessity for a variety of RWE solutions catered to the needs of different stakeholders is being driven by the expansion of RWE use cases.

BIGAN is the Big Data project of the Department of Health of the Government of Aragon, created to improve healthcare using data that are routinely collected within the public health system of Aragon. Development of the project has been entrusted to the Aragon Institute of Health Sciences (IACS).

The purpose of the project is to integrate all data collected within the health system on a technological platform, where it can be analysed by healthcare professionals, managers, educators, and researchers. The ultimate goal is to improve the healthcare system and the health of residents in Aragon through data observation. To achieve this, collection, analysis, and sharing of information between all involved stakeholders is vital.

Real Gross Domestic Product: Ambulatory Health Care Services (NAICS 621) in Vermont was 1828.60000 Mil. of Chn. 2009 $ in January of 2023, according to the United States Federal Reserve. Historically, Real Gross Domestic Product: Ambulatory Health Care Services (NAICS 621) in Vermont reached a record high of 1828.60000 in January of 2023 and a record low of 724.00000 in January of 1997. Trading Economics provides the current actual value, an historical data chart and related indicators for Real Gross Domestic Product: Ambulatory Health Care Services (NAICS 621) in Vermont - last updated from the United States Federal Reserve on July of 2025.

Graph and download economic data for Real Medical Services Expenditures by Disease: Endocrine; Nutritional; and Metabolic Diseases and Immunity Disorders, MEPS Account Basis (EDCNMIREXMEPS) from 2000 to 2021 about disease, healthcare, medical, health, nutrition, expenditures, services, real, and USA.

The Real World Data (RWD) solution market is experiencing robust growth, driven by the increasing adoption of digital health technologies, the rising prevalence of chronic diseases, and the urgent need for more efficient and cost-effective clinical trials. The market's expansion is fueled by several key factors, including the growing availability of large datasets from electronic health records (EHRs), wearable sensors, and mobile health applications. Pharmaceutical and biotechnology companies are increasingly leveraging RWD to accelerate drug development, gain deeper insights into patient populations, and improve post-market surveillance. Furthermore, regulatory agencies are showing greater acceptance of RWD in clinical decision-making, further stimulating market growth. We estimate the market size to be approximately $15 billion in 2025, with a Compound Annual Growth Rate (CAGR) of 18% projected through 2033. This growth is anticipated to be driven primarily by the increased integration of AI and machine learning into RWD platforms, enhancing data analysis and generating actionable insights. The market is segmented by application (e.g., clinical trials, drug safety surveillance, regulatory submissions, payer decision support) and by type of data (e.g., EHRs, claims data, patient-generated health data, registry data). North America currently holds a significant share of the global RWD market, due to advanced healthcare infrastructure and early adoption of digital health technologies. However, Asia-Pacific is projected to witness the highest growth rate in the forecast period, driven by rapid technological advancements and increasing healthcare expenditure in emerging economies like India and China. Significant restraints include data privacy concerns, data interoperability challenges, and the need for robust data governance frameworks to ensure data quality and security. However, ongoing technological advancements and supportive regulatory policies are expected to mitigate these challenges in the coming years. Key players in the market are actively investing in RWD solutions, strengthening their competitive landscape through strategic partnerships, mergers, and acquisitions.

Real Gross Domestic Product by Industry: Private Industries: Educational Services, Health Care, and Social Assistance: Health Care and Social Assistance: Hospitals and Nursing and Residential Care Facilities for Ohio (DISCONTINUED) was 22032.00000 Mil. of Chn. 2009 $ in January of 2016, according to the United States Federal Reserve. Historically, Real Gross Domestic Product by Industry: Private Industries: Educational Services, Health Care, and Social Assistance: Health Care and Social Assistance: Hospitals and Nursing and Residential Care Facilities for Ohio (DISCONTINUED) reached a record high of 22204.00000 in January of 2014 and a record low of 18124.00000 in January of 1998. Trading Economics provides the current actual value, an historical data chart and related indicators for Real Gross Domestic Product by Industry: Private Industries: Educational Services, Health Care, and Social Assistance: Health Care and Social Assistance: Hospitals and Nursing and Residential Care Facilities for Ohio (DISCONTINUED) - last updated from the United States Federal Reserve on July of 2025.

Real Gross Domestic Product: Health Care and Social Assistance (NAICS 62) in Montana was 6203.20000 Mil. of Chn. 2009 $ in January of 2025, according to the United States Federal Reserve. Historically, Real Gross Domestic Product: Health Care and Social Assistance (NAICS 62) in Montana reached a record high of 6203.20000 in January of 2025 and a record low of 3171.50000 in January of 2005. Trading Economics provides the current actual value, an historical data chart and related indicators for Real Gross Domestic Product: Health Care and Social Assistance (NAICS 62) in Montana - last updated from the United States Federal Reserve on July of 2025.

These are peer-reviewed supplementary materials for the article 'Real-world evidence: state-of-the-art and future perspectives' published in the Journal of Comparative Effectiveness Research.BackgroundAimMethodsStep 1: Selection of TAsStep 2a: Cross-validation of definition of ‘use of routine data in non-experimental settings’ Figure 3: Refinement of the criteria used to define 'use of routine data in non-experimental settings’ for the full assessment of published NICE TAsStep 2b: Full review of 12 Cancer and 67 Non-Cancer TAs published 2022-24ResultsFigure 4: Selection of TAs for reviewFigure 5: Distribution of Cancer (blue) and Non-Cancer (green) TAs submitted to NICE since 2000 (A). Non-Cancer TAs are broken down by specialty (B)Table 1: Results of the cross-validation of the criteria applied to randomly selected Cancer TAsTable 2: Results of the cross-validation of the criteria applied to randomly selected Non-Cancer TAsRecent developments in digital infrastructure, advanced analytical approaches, and regulatory settings have facilitated the broadened use of real-world evidence (RWE) in population health management and evaluation of novel health technologies. RWE has uniquely contributed to improving human health by addressing unmet clinical needs, from assessing the external validity of clinical trial data to discovery of new disease phenotypes. In this perspective, we present exemplars across various health areas that have been impacted by real-world data and RWE, and we provide insights into further opportunities afforded by RWE. By deploying robust methodologies and transparently reporting caveats and limitations, realworld data accessed via secure data environments can support proactive healthcare management and accelerate access to novel interventions in England.

Real Gross Domestic Product: Health Care and Social Assistance (NAICS 62) in New Mexico was 8430.50000 Mil. of Chn. 2009 $ in January of 2024, according to the United States Federal Reserve. Historically, Real Gross Domestic Product: Health Care and Social Assistance (NAICS 62) in New Mexico reached a record high of 8430.50000 in January of 2024 and a record low of 3693.00000 in January of 1997. Trading Economics provides the current actual value, an historical data chart and related indicators for Real Gross Domestic Product: Health Care and Social Assistance (NAICS 62) in New Mexico - last updated from the United States Federal Reserve on July of 2025.

Real Gross Domestic Product: Health Care and Social Assistance (NAICS 62) in South Dakota was 5887.00000 Mil. of Chn. 2009 $ in January of 2024, according to the United States Federal Reserve. Historically, Real Gross Domestic Product: Health Care and Social Assistance (NAICS 62) in South Dakota reached a record high of 5887.00000 in January of 2024 and a record low of 2420.90000 in January of 1997. Trading Economics provides the current actual value, an historical data chart and related indicators for Real Gross Domestic Product: Health Care and Social Assistance (NAICS 62) in South Dakota - last updated from the United States Federal Reserve on July of 2025.

Comprehensive dataset of 2 Mental health clinics in Ciudad Real, Spain as of August, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Real Gross Domestic Product: Health Care and Social Assistance (NAICS 62) in Wisconsin was 32915.70000 Mil. of Chn. 2009 $ in January of 2024, according to the United States Federal Reserve. Historically, Real Gross Domestic Product: Health Care and Social Assistance (NAICS 62) in Wisconsin reached a record high of 32915.70000 in January of 2024 and a record low of 16912.50000 in January of 1997. Trading Economics provides the current actual value, an historical data chart and related indicators for Real Gross Domestic Product: Health Care and Social Assistance (NAICS 62) in Wisconsin - last updated from the United States Federal Reserve on July of 2025.

The Real-World Evidence (RWE) Solutions market is experiencing robust growth, projected to reach $828.46 million in 2025 and expand at a compound annual growth rate (CAGR) of 13% from 2025 to 2033. This significant expansion is driven by several key factors. The increasing adoption of RWE in regulatory decision-making, fueled by the need for more efficient and cost-effective drug development, is a primary driver. Furthermore, the rising availability of large, diverse datasets from electronic health records (EHRs), claims databases, and wearable devices provides rich sources of real-world data for analysis. Pharmaceutical companies and healthcare providers are actively investing in RWE solutions to improve clinical trial design, enhance post-market surveillance, and optimize treatment strategies, further bolstering market growth. The market is segmented by type (e.g., software, services) and application (e.g., drug development, post-market surveillance), each exhibiting unique growth trajectories influenced by specific technological advancements and regulatory landscapes. Competitive strategies among leading companies, such as Clinigen Group Plc, ICON Plc, and IQVIA Inc., focus on strategic partnerships, technological innovation, and expansion into new geographical markets. These companies are engaged in developing advanced analytical tools and data integration platforms to cater to growing demands for comprehensive RWE solutions. The North American market currently holds a substantial share, driven by robust regulatory frameworks and advanced healthcare infrastructure. However, other regions, particularly Asia Pacific, are expected to witness significant growth in the coming years due to increasing healthcare expenditure and technological advancements. The restraints on market growth are primarily related to data privacy concerns, regulatory hurdles in accessing and utilizing real-world data, and the need for robust data standardization across different sources. However, proactive measures like developing better data security protocols, clarifying regulatory guidelines, and investing in data harmonization initiatives are mitigating these challenges. The future of the RWE Solutions market hinges on continuous technological innovation, particularly in areas like artificial intelligence (AI) and machine learning (ML), which can enhance data analysis and generate valuable insights from complex datasets. Further growth will depend on fostering collaboration among stakeholders, including regulatory bodies, healthcare providers, and technology companies, to create a more conducive environment for RWE adoption.