Read reports on priority public health topics including opioid, stimulant, & other substance use, maternal & child health, and racial & health inequities

DATA.HRSA.GOV is the go-to source for data, dashboards, maps, reports, locators, APIs and downloadable data files on HRSA's public health programs, including: HRSA-funded Health Center grants, grantees, sites, and related primary care programs Health Professional Shortage Areas (HPSA) and Medically Underserved Areas/Populations (MUA/P) Ryan White HIV/AIDS services, grantees, and providers Maternal and Child Health grants (Title V, Home Visiting, Healthy Start) National Health Service Corps (NHSC), Nurse Corps, and other workforce loan repayment/scholarship programs Grants for workforce training programs in medicine, nursing, dentistry, and public health Grants for rural health programs Organ donation DATA.HRSA.GOV allows you to search by topic area, by geography, and by tool.

Objective The aim of this study was to develop an accurate regional forecast algorithm to predict the number of hospitalized patients and to assess the benefit of the Electronic Health Records (EHR) information to perform those predictions. Materials and Methods Aggregated data from SARS-CoV-2 and weather public database and data warehouse of the Bordeaux hospital were extracted from May 16, 2020, to January 17, 2022. The outcomes were the number of hospitalized patients in the Bordeaux Hospital at 7 and 14 days. We compared the performance of different data sources, feature engineering, and machine learning models. Results During the period of 88 weeks, 2561 hospitalizations due to COVID-19 were recorded at the Bordeaux Hospital. The model achieving the best performance was an elastic-net penalized linear regression using all available data with a median relative error at 7 and 14 days of 0.136 [0.063; 0.223] and 0.198 [0.105; 0.302] hospitalizations, respectively. Electronic health r..., Aggregated data from 2020-05-16 to 2022-01-17 regarding Bordeaux Hospital EHR. Bordeaux hospital data warehouse was used, during the pandemic, to describe the current state of the epidemic at the hospital level on a daily basis. Those data were then used in the forecast model including: hospitalizations, hospital and ICU admission and discharge, ambulance service notes and emergency unit notes. Concepts related to COVID-19 were extracted from notes by dictionary-based approaches (e.g. cough, dyspnoea, covid-19). Dictionaries were manually created based on manual chart review to identify terms used by practitioners. Then, the number and proportion of ambulance service calls or hospitalization in emergency units mentioning concepts related to covid-19 were extracted. Due to different data acquisition mechanisms, there was a delay between the occurrence of events and the data acquisition. It was of 1 day for EHR data, 5 days for department hospitalizations and RT-PCR, 4 days for weather, 2..., Data are stored in a .rdata file. Please use R (https://www.r-project.org/) software to open the data.

The HRSA Data Warehouse is the go-to source for data, maps, reports, locators, and dashboards on HRSA's public health programs. This website provides a wide variety of data on HRSA's programs, including:

• HRSA-funded Health Center grants, grantees, sites, and related primary care programs
• Health Professional Shortage Areas (HPSA) and Medically Underserves Areas/Populations (MUA/P)
• Ryan White HIV/AIDS services, grantees, and providers
• Maternal and Child Health grants (Title V, Home Visiting, Health Start)
• National Health Service Corps (NHSC), Nurse Corps, and other workforce loan repayment/scholarship programs
• Grants for workforce training programs in medicine, nursing, dentistry, and public health
• Grants for rural health programs
• Organ donation
• 340(b) drug discount program

The HRSA Data Warehouse allows you to search by topic area, by geography, and by tool.

AbstractIntroductionThis paper's aim is to develop a data warehouse from the integration of the files of three Brazilian health information systems concerned with the production of ambulatory and hospital procedures for cancer care, and cancer mortality. These systems do not have a unique patient identification, which makes their integration difficult even within a single system.MethodsData from the Brazilian Public Hospital Information System (SIH-SUS), the Oncology Module for the Outpatient Information System (APAC-ONCO) and the Mortality Information System (SIM) for the State of Rio de Janeiro, in the period from January 2000 to December 2004 were used. Each of the systems has the monthly data production compiled in dbase files (dbf). All the files pertaining to the same system were then read into a corresponding table in a MySQL Server 5.1. The SIH-SUS and APAC-ONCO tables were linked internally and with one another through record linkage methods. The APAC-ONCO table was linked to the SIM table. Afterwards a data warehouse was built using Pentaho and the MySQL database management system.ResultsThe sensitivities and specificities of the linkage processes were above 95% and close to 100% respectively. The data warehouse provided several analytical views that are accessed through the Pentaho Schema Workbench.ConclusionThis study presented a proposal for the integration of Brazilian Health Systems to support the building of data warehouses and provide information beyond those currently available with the individual systems.

The Veterans Health Administration (VHA) is increasingly dependent upon data. Most of its employees generate and use vast amounts of data on a daily basis. To improve our capacity for data analysis while providing the most efficient and the highest quality health care to our Veteran patients, VHA, working with the VA Office of Information and Technology, implemented a health data warehouse. Central to this plan is consolidating data from disparate sources into a coherent single logical data model. The Corporate Data Warehouse (CDW) is the physical implementation of this logical data model at the enterprise level for VHA. Although the CDW initially began to store data as early as 2006, a renewed effort began in 2010 to accelerate CDW's content by including more subject areas from Veterans Health Information Systems and Technology Architecture (VistA) and content from other existing national data systems. CDW supports fully developed subject areas in its production environment as well as supporting rapid prototyping by extracting data directly from source systems with very minor data transformations. The Regional Data Warehouses and the Veterans Integrated Service Network (VISN) Data Warehouses share content from CDW and allow for greater reporting flexibility at the local level throughout the VHA organization.

Clinical Data Warehouse Market Outlook

According to our latest research, the global clinical data warehouse market size reached USD 2.84 billion in 2024, demonstrating robust demand across healthcare and life sciences sectors. The market is expected to expand at a CAGR of 11.2% from 2025 to 2033, reaching a forecasted value of USD 7.36 billion by 2033. This impressive growth trajectory is primarily fueled by the increasing adoption of data-driven healthcare, regulatory mandates for data integration, and the rising emphasis on evidence-based clinical decision-making worldwide.

One of the most significant growth factors for the clinical data warehouse market is the exponential rise in healthcare data volumes generated by electronic health records (EHRs), medical imaging, genomics, and connected medical devices. Healthcare providers and research institutions are facing mounting pressure to harness this data for actionable insights, improved patient outcomes, and operational efficiency. Clinical data warehouses serve as the backbone for integrating disparate data sources, standardizing information, and enabling advanced analytics and artificial intelligence (AI) applications. As healthcare organizations increasingly prioritize digital transformation, the demand for robust, scalable, and secure clinical data warehousing solutions continues to surge, driving market expansion.

Another key driver is the growing regulatory emphasis on data interoperability, patient privacy, and quality reporting. Governments and regulatory bodies across the globe are mandating the adoption of interoperable health IT systems and standardized data formats to ensure seamless data exchange and compliance with regulations such as HIPAA, GDPR, and the 21st Century Cures Act. Clinical data warehouses play a critical role in facilitating regulatory compliance, supporting quality reporting initiatives, and enabling value-based care models. Their ability to aggregate, cleanse, and harmonize clinical, operational, and financial data empowers healthcare organizations to demonstrate care quality, optimize reimbursements, and participate in population health management programs.

The rapid advancement of artificial intelligence, machine learning, and predictive analytics is also transforming the clinical data warehouse landscape. These technologies require high-quality, well-structured data repositories for training algorithms, developing predictive models, and conducting real-world evidence studies. Clinical data warehouses are increasingly being integrated with advanced analytics platforms, enabling real-time insights for clinical research, patient stratification, risk prediction, and personalized medicine. As the healthcare industry moves toward precision health and data-driven innovation, the strategic value of clinical data warehouses is expected to grow, further accelerating market growth.

From a regional perspective, North America currently dominates the global clinical data warehouse market, accounting for the largest revenue share in 2024. This leadership is attributed to the presence of advanced healthcare infrastructure, widespread adoption of EHRs, and strong regulatory frameworks supporting health data integration. Europe follows closely, driven by stringent data protection regulations and growing investments in digital health. Meanwhile, the Asia Pacific region is emerging as the fastest-growing market, propelled by healthcare modernization initiatives, increasing adoption of cloud-based solutions, and government efforts to digitize healthcare systems. Latin America and the Middle East & Africa are also witnessing steady growth, albeit from a smaller base, as healthcare providers in these regions increasingly recognize the value of data-driven decision-making.

Component Analysis

The clinical data warehouse market is segmented by component into software, hardware, and services, each playing a pivotal role in the ecosystem. Software represents the largest segment

The CMS Chronic Condition Data Warehouse (CCW) provides researchers with Medicare and Medicaid beneficiary, claims, and assessment data linked by beneficiary across the continuum of care. In the past, researchers analyzing data files were required to perform extensive analysis related to beneficiary matching, deduplication, and merging of the files in preparation for their study analysis. With the CCW data, this preliminary linkage work is already accomplished and delivered as part of the data files sent to researchers.

The Health Claims Data Warehouse (HCDW) will receive and analyze health claims data to support management and administrative purposes. The Federal Employee Health Benefits Program (FEHBP) is a $40 billion program covering approximately 8 million eligible participants using more than 100 health insurance carriers. The HCDW will incorporate extensive analytical capabilities to support cost analysis, administration, design, and quality improvement of healthcare services provided to eligible participants.

The amount of global healthcare data is expected to increase dramatically by the year 2020. Despite the growing amount of data, there is not enough storage space to accommodate the data being generated. It is projected that by 2020 there will be 985 exabytes of storage available for healthcare data but there will be 2,314 exabytes of healthcare data generated.

Clinical Data Warehouse Market Outlook

According to our latest research, the global clinical data warehouse market size was valued at USD 5.82 billion in 2024. The market is expected to grow at a robust CAGR of 12.3% during the forecast period, reaching USD 16.25 billion by 2033. This significant growth is primarily driven by the increasing adoption of advanced analytics in healthcare, the rising need for integrated data management solutions, and the accelerating digital transformation across medical institutions. As per our latest research, the demand for clinical data warehouse solutions is surging due to the growing emphasis on evidence-based medicine, regulatory compliance, and the need to optimize clinical and operational outcomes.

One of the primary growth factors for the clinical data warehouse market is the escalating volume and complexity of healthcare data generated from diverse sources such as electronic health records (EHRs), medical imaging, genomic data, and wearable devices. Healthcare providers and organizations are increasingly recognizing the value of consolidating disparate data sets into a centralized repository to enhance clinical decision-making, streamline operations, and facilitate research initiatives. The integration of artificial intelligence and machine learning algorithms into clinical data warehouses is further amplifying their capabilities, enabling predictive analytics, real-time insights, and personalized patient care. This technological evolution is catalyzing the adoption of clinical data warehouses across hospitals, research institutions, and pharmaceutical companies, fueling market expansion.

Another substantial driver is the growing regulatory pressure to maintain comprehensive and accurate healthcare records. Governments and regulatory bodies worldwide are mandating stringent data management practices to ensure patient safety, privacy, and compliance with standards such as HIPAA, GDPR, and other regional frameworks. Clinical data warehouses play a pivotal role in meeting these requirements by offering secure, scalable, and interoperable platforms for data storage and retrieval. The ability to support quality reporting, audit trails, and data governance is making these solutions indispensable in the modern healthcare landscape. As a result, organizations are increasingly investing in advanced data warehousing solutions to mitigate risks, enhance transparency, and achieve regulatory alignment.

Moreover, the shift towards value-based healthcare and population health management is propelling the need for robust data analytics infrastructure. Clinical data warehouses are instrumental in aggregating and analyzing patient data to identify trends, measure outcomes, and support preventive care strategies. The growing focus on cost containment, resource optimization, and improved patient outcomes is prompting healthcare organizations to leverage data-driven insights for strategic decision-making. Additionally, the proliferation of cloud-based solutions is democratizing access to advanced analytics tools, enabling even smaller healthcare providers to harness the power of clinical data warehousing. This democratization is fostering innovation and competition, further stimulating market growth.

From a regional perspective, North America currently dominates the clinical data warehouse market, accounting for the largest revenue share in 2024, followed by Europe and the Asia Pacific. The presence of a well-established healthcare infrastructure, high adoption of digital health technologies, and substantial investments in research and development are key factors underpinning North America's leadership. Meanwhile, the Asia Pacific region is emerging as a lucrative market, driven by rapid healthcare digitization, expanding patient populations, and increasing government initiatives to modernize healthcare systems. Europe continues to witness steady growth, supported by favorable regulatory frameworks and strong focus on healthcare innovation. Latin America and the Middle East & Africa are also showing promising potential, albeit at a comparatively nascent stage.

Component Analysis

The clinical data warehouse market is segmented by component into software, hardware, and services, each playing a critical role in the overall ecosystem. The software segment constitutes the largest share of the market, reflecting the increasing demand for advanced analytics platforms, data integration tools, and user-fr

VA CDW is a repository comprising data from multiple Veterans Health Administration (VHA) clinical and administrative systems. VHA is one of the largest integrated healthcare systems in the United States with data from over 20 years of sustained electronic health record (EHR) use. VA CDW was developed in 2006 to accommodate the massive amounts of data being generated and to streamline the process of knowledge discovery to application. The registry consists of approximately 7,500 databases hosted across 86 servers. Information that appears in the VA CDW includes demographic information, information on medication dispensing from VA pharmacies, laboratory test result information, free text from progress notes and radiology reports, as well as billing and claims-related data.

Collection of health indicator data categorized by topic, geography, and initiative. For developers, the HIW provides access to the underlying data through the use of an Application Programming Interface (API) which is designed to present information to systems with disparate architectures and underlying technologies.

This dataset provides summarized data for all expenditures from July 2003 through the current fiscal year, year to date, from the State's central accounting system. The state fiscal year runs from July 1 to the following June 30 and is numbered for the calendar year in which it ends. The State of Iowa operates on a modified accrual basis which provides that encumbrances on June 30 must be paid within 60 days after year end. The expenditures are summarized by Fiscal Year, Month, Fund, Appropriation, Department, Unit, and Object Class.

Web based Data Warehouse disemminating typing data to the regions and Health Protection Unit

This dataset contains measures that evaluate the quality of care delivered by Health Homes for the Centers for Medicare & Medicaid Services (CMS) Core Set and Health Home State Plan Amendment (SPA). To support ongoing assessment of the effectiveness of the Health Home model, the CMS has established a recommended Core Set of health care quality measures that it intends to promulgate in the rulemaking process. The data used in the Health Home Quality Measures are taken from the following sources: • Medicaid Data Mart: Claims and encounters data generated from the Medicaid Data Warehouse (MDW). • QARR Member Level Files: Sample of the health plan eligible member’s quality. • New York State Delivery System Inform Incentive Program (DSRIP) Data Warehouse: Claims and encounters data generated from the Medicaid Data Warehouse (MDW).

Please refer to the Overview document for additional information.

Healthcare Data Storage Market size was valued at USD 3.97 Billion in 2024 and is projected to reach USD 10.27 Billion by 2032, growing at a CAGR of 13.90% during the forecast period 2026-2032.Global Healthcare Data Storage Market DriversThe market drivers for the Healthcare Data Storage Market can be influenced by various factors. These may include:Growing volume of healthcare data: The amount of data produced by healthcare providers has increased dramatically as a result of the digitalization of medical records. This covers genomic information, medical imaging, electronic health records (EHRs), and more. To handle this data, healthcare institutions need effective and safe storage options.Severe laws and compliance requirements: HIPAA (Health Insurance Portability and Accountability Act) in the US and GDPR (General Data Protection Regulation) in Europe are two examples of the severe laws that apply to healthcare data. In order to protect patient information, these requirements mandate that healthcare organisations employ secure data storage solutions.Cloud storage is becoming more and more popular since it is affordable, flexible, and scalable, which appeals to healthcare institutions. Adoption is accelerated by cloud storage companies' provision of specialised healthcare cloud solutions that meet legal and regulatory standards.Technological developments: Artificial intelligence (AI), machine learning (ML), and big data analytics are some of the technologies that are revolutionising healthcare. To handle the massive volumes of data collected and analysed, these technologies need reliable data storage systems.Growing need for data interoperability: In order to enhance patient care coordination and results, healthcare providers are placing a greater emphasis on interoperability. This calls for the smooth transfer of medical data between various systems, which calls for trustworthy data storage options.Escalating healthcare expenses: There is pressure on healthcare institutions to save expenses without sacrificing care quality. Healthcare data management and storage operations can be made more cost-effective with the use of efficient data storage solutions.Growing comprehension of data security's significance Healthcare data breaches may result in severe repercussions, such as monetary losses and reputational harm. To safeguard patient data from online dangers, healthcare institutions are investing in secure data storage solutions.

According to Cognitive Market Research, the global healthcare data storage market size is USD 5.4 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 14.3% from 2024 to 2031. Market Dynamics of Healthcare Data Storage Market

Key Drivers for Healthcare Data Storage Market

Increasing amount of healthcare records- Healthcare data storage market is in high demand due to the increasing amount of healthcare data. Electronic health records (EHRs), medical imaging, wearable electronics, and health applications all contribute to the daily deluge of data generated and amassed by healthcare institutions. This data includes a wide range of information, including patients’ medical records, diagnostic pictures, treatment programs, health indicators in real-time, and more. Moreover, healthcare data storage systems are necessary for efficient management of such vast data sets because they can manage high volumes, provide fast retrieval, and keep data secure. Further, state-of-the-art storage systems are required for compliance with data retention and security regulations. Thus, in order to facilitate better patient care and operational efficiency, the ever-increasing volume of healthcare data is driving the use of advanced data storage technologies.
The market is being propelled by the demand for efficient and rapid access to patient data in order to enhance clinical decision-making and patient care.

Key Restraints for Healthcare Data Storage Market

Healthcare data storage market growth is hindered due to the high costs of implementation and upkeep.
The market expansion is being impeded by concerns about data breaches and data accessibility.

Introduction of the Healthcare Data Storage Market

Healthcare data storage describes the infrastructure and procedures put in place to keep and handle massive volumes of patient records safely. Complying with regulatory requirements while ensuring data integrity, confidentiality, and accessibility is essential for healthcare data storage solutions. The rising amount of digital data produced by healthcare companies, the convenience and speed with which cloud storage solutions can be implemented, and the increasing popularity of hybrid data storage solutions are the primary elements propelling the expansion of this market. Security concerns over cloud-based image processing and analytics, however, are limiting the company’s growth. Concerns about the security of cloud-based image processing and analytics are expected to dampen the worldwide healthcare data storage industry. Additionally, advancements in artificial intelligence, big data analytics, and cloud computing have greatly improved the efficiency and capacity of the healthcare data storage market.

BackgroundHealthcare data is a rich yet underutilized resource due to its disconnected, heterogeneous nature. A means of connecting healthcare data and integrating it with additional open and social data in a secure way can support the monumental challenge policy-makers face in safely accessing all relevant data to assist in managing the health and wellbeing of all. The goal of this study was to develop a novel health data platform within the MIDAS (Meaningful Integration of Data Analytics and Services) project, that harnesses the potential of latent healthcare data in combination with open and social data to support evidence-based health policy decision-making in a privacy-preserving manner.MethodsThe MIDAS platform was developed in an iterative and collaborative way with close involvement of academia, industry, healthcare staff and policy-makers, to solve tasks including data storage, data harmonization, data analytics and visualizations, and open and social data analytics. The platform has been piloted and tested by health departments in four European countries, each focusing on different region-specific health challenges and related data sources.ResultsA novel health data platform solving the needs of Public Health decision-makers was successfully implemented within the four pilot regions connecting heterogeneous healthcare datasets and open datasets and turning large amounts of previously isolated data into actionable information allowing for evidence-based health policy-making and risk stratification through the application and visualization of advanced analytics.ConclusionsThe MIDAS platform delivers a secure, effective and integrated solution to deal with health data, providing support for health policy decision-making, planning of public health activities and the implementation of the Health in All Policies approach. The platform has proven transferable, sustainable and scalable across policies, data and regions.

Healthcare Data Storage Market is projected to reach USD 13.4 billion by 2032, growing at a CAGR of 14.5% from 2024-2032.