According to the data from 2025, some 16 percent of respondents said that rising health care costs were the most important health issue facing the United States. Cancer ranked second on the list with 15 percent. Issues with healthcare costsCurrently, the most urgent problem facing American healthcare is the high costs of care. The high expense of healthcare may deter people from getting the appropriate treatment when they need medical care or cause them to completely forego preventative care visits. Many Americans reported that they may skip prescription doses or refrain from taking medication as prescribed due to financial concerns. Such health-related behavior can result in major health problems, which may raise the long-term cost of care. Inflation, medical debt, and unforeseen medical expenses have all added to the burden that health costs are placing on household income. Gun violence issueThe gun violence epidemic has plagued the United States over the past few years, yet very little has been done to address the issue. In recent years, gun violence has become the leading cause of death among American children and teens. Even though more than half of Americans are in favor of tougher gun control regulations, there is little political will to strongly reform the current gun law. Gun violence has a deep traumatic impact on survivors and society, it is developing into a major public health crisis in the United States.

A 2024 survey found that over half of U.S. individuals indicated the cost of accessing treatment was the biggest problem facing the national healthcare system. This is much higher than the global average of 32 percent and is in line with the high cost of health care in the U.S. compared to other high-income countries. Bureaucracy along with a lack of staff were also considered to be pressing issues. This statistic reveals the share of individuals who said select problems were the biggest facing the health care system in the United States in 2024.

This data package contains dataset on prevalence rates of health conditions and diseases like obesity, diabetes and hearing loss and health risk factors for diseases like tobacco, alcohol and drug use.

In the United States, the most common diagnostic category treated by acute care hospital at home programs was diseases and disorders of the respiratory system. In the period 2022 to 2024, respiratory diseases accounted for ** percent of episodes treated by hospital at home.

The National Health Interview Survey (NHIS) is the principal source of information on the health of the civilian noninstitutionalized population of the United States and is one of the major data collection programs of the National Center for Health Statistics (NCHS) which is part of the Centers for Disease Control and Prevention (CDC). The National Health Survey Act of 1956 provided for a continuing survey and special studies to secure accurate and current statistical information on the amount, distribution, and effects of illness and disability in the United States and the services rendered for or because of such conditions. The survey referred to in the Act, now called the National Health Interview Survey, was initiated in July 1957. Since 1960, the survey has been conducted by NCHS, which was formed when the National Health Survey and the National Vital Statistics Division were combined. NHIS data are used widely throughout the Department of Health and Human Services (DHHS) to monitor trends in illness and disability and to track progress toward achieving national health objectives. The data are also used by the public health research community for epidemiologic and policy analysis of such timely issues as characterizing those with various health problems, determining barriers to accessing and using appropriate health care, and evaluating Federal health programs. The NHIS also has a central role in the ongoing integration of household surveys in DHHS. The designs of two major DHHS national household surveys have been or are linked to the NHIS. The National Survey of Family Growth used the NHIS sampling frame in its first five cycles and the Medical Expenditure Panel Survey currently uses half of the NHIS sampling frame. Other linkage includes linking NHIS data to death certificates in the National Death Index (NDI). While the NHIS has been conducted continuously since 1957, the content of the survey has been updated about every 10-15 years. In 1996, a substantially revised NHIS questionnaire began field testing. This revised questionnaire, described in detail below, was implemented in 1997 and has improved the ability of the NHIS to provide important health information.

Introduction

Global Big Data in Healthcare Market size is expected to be worth around USD 145.8 Billion by 2033 from USD 42.2 Billion in 2023, growing at a CAGR of 13.2% during the forecast period from 2024 to 2033.

Big data in healthcare encompasses vast amounts of diverse, unstructured data sourced from medical journals, biometric sensors, electronic medical records (EMRs), Internet of Medical Things (IoMT), social media platforms, payer records, omics research, and data repositories. Integrating this unstructured data into traditional systems presents considerable challenges, primarily in data structuring and standardization. Effective data structuring is essential for ensuring compatibility across systems and enabling robust analytical processes.

However, advancements in big data analytics, artificial intelligence, and machine learning have significantly enhanced the ability to convert complex healthcare data into actionable insights. These advancements have transformed healthcare, driving informed decision-making, enabling early and accurate diagnostics, facilitating precision medicine, and enhancing patient engagement through digital self-service platforms, including online portals, mobile applications, and wearable health devices.

The role of big data in pharmaceutical R&D has become increasingly central, as analytics tools streamline drug discovery, accelerate clinical trial processes, and identify potential therapeutic targets more efficiently. The demand for business intelligence solutions within healthcare is rising, fueled by the surge of unstructured data and the focus on developing tailored treatment protocols. As a result, the global market for big data in healthcare is projected to grow steadily during the forecast period.

NOTE: On October 19, 2021, estimates for 2016–2018 by health insurance status were revised to correct errors. Changes are highlighted and tagged at https://www.cdc.gov/nchs/data/hus/2019/012-508.pdf Data on health conditions among children under age 18, by selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions, and changes over time. SOURCE: NCHS, National Health Interview Survey, Family Core and Sample Child questionnaires. For more information on the National Health Interview Survey, see the corresponding Appendix entry at https://www.cdc.gov/nchs/data/hus/hus19-appendix-508.pdf.

Changelog:

Update September 20, 2021: Data and overview updated to reflect data used in the September 15 story Over Half of States Have Rolled Back Public Health Powers in Pandemic. It includes 303 state or local public health leaders who resigned, retired or were fired between April 1, 2020 and Sept. 12, 2021. Previous versions of this dataset reflected data used in the Dec. 2020 and April 2021 stories.

Overview

Across the U.S., state and local public health officials have found themselves at the center of a political storm as they combat the worst pandemic in a century. Amid a fractured federal response, the usually invisible army of workers charged with preventing the spread of infectious disease has become a public punching bag.

In the midst of the coronavirus pandemic, at least 303 state or local public health leaders in 41 states have resigned, retired or been fired since April 1, 2020, according to an ongoing investigation by The Associated Press and KHN.

According to experts, that is the largest exodus of public health leaders in American history.

Many left due to political blowback or pandemic pressure, as they became the target of groups that have coalesced around a common goal — fighting and even threatening officials over mask orders and well-established public health activities like quarantines and contact tracing. Some left to take higher profile positions, or due to health concerns. Others were fired for poor performance. Dozens retired. An untold number of lower level staffers have also left.

The result is a further erosion of the nation’s already fragile public health infrastructure, which KHN and the AP documented beginning in 2020 in the Underfunded and Under Threat project.

Findings

The AP and KHN found that:

• One in five Americans live in a community that has lost its local public health department leader during the pandemic
• Top public health officials in 28 states have left state-level departments ## Using this data To filter for data specific to your state, use this query

To get total numbers of exits by state, broken down by state and local departments, use this query

Methodology

KHN and AP counted how many state and local public health leaders have left their jobs between April 1, 2020 and Sept. 12, 2021.

The government tasks public health workers with improving the health of the general population, through their work to encourage healthy living and prevent infectious disease. To that end, public health officials do everything from inspecting water and food safety to testing the nation’s babies for metabolic diseases and contact tracing cases of syphilis.

Many parts of the country have a health officer and a health director/administrator by statute. The analysis counted both of those positions if they existed. For state-level departments, the count tracks people in the top and second-highest-ranking job.

The analysis includes exits of top department officials regardless of reason, because no matter the reason, each left a vacancy at the top of a health agency during the pandemic. Reasons for departures include political pressure, health concerns and poor performance. Others left to take higher profile positions or to retire. Some departments had multiple top officials exit over the course of the pandemic; each is included in the analysis.

Reporters compiled the exit list by reaching out to public health associations and experts in every state and interviewing hundreds of public health employees. They also received information from the National Association of City and County Health Officials, and combed news reports and records.

Public health departments can be found at multiple levels of government. Each state has a department that handles these tasks, but most states also have local departments that either operate under local or state control. The population served by each local health department is calculated using the U.S. Census Bureau 2019 Population Estimates based on each department’s jurisdiction.

KHN and the AP have worked since the spring on a series of stories documenting the funding, staffing and problems around public health. A previous data distribution detailed a decade's worth of cuts to state and local spending and staffing on public health. That data can be found here.

Attribution

Findings and the data should be cited as: "According to a KHN and Associated Press report."

Is Data Missing?

If you know of a public health official in your state or area who has left that position between April 1, 2020 and Sept. 12, 2021 and isn't currently in our dataset, please contact authors Anna Maria Barry-Jester annab@kff.org, Hannah Recht hrecht@kff.org, Michelle Smith mrsmith@ap.org and Lauren Weber laurenw@kff.org.

This is the Google Search interest data that powers the Visualisation Searching For Health. Google Trends data allows us to see what people are searching for at a very local level. This visualization tracks the top searches for common health issues in the United States, from Cancer to Diabetes, and compares them with the actual location of occurrences for those same health conditions to understand how search data reflects life for millions of Americans.

How does search interest for top health issues change over time? From 2004–2017, the data shows that search interest gradually increased over the past few years. Certain regions show a more significant increase in search interest than others. The increase in search activity is greatest in the Midwest and Northeast, while the changes are noticeably less dramatic in California, Texas, and Idaho. Are people generally becoming more aware of health conditions and health risks?

The search interest data was collected using the Google Trends API. The visualisation also brings in incidences of each condition so they can be compared. The health conditions were hand-selected from the Community Health Status Indicators (CHSI) which provides key indicators for local communities in the United States. The CHSI dataset includes more than 200 measures for each of the 3,141 United States counties. More information about the CHSI can be found on healthdata.gov.

Many striking similarities exist between searches and actual conditions—but the relationship between the Obesity and Diabetes maps stands out the most. “There are many risk factors for type 2 diabetes such as age, race, pregnancy, stress, certain medications, genetics or family history, high cholesterol and obesity. However, the single best predictor of type 2 diabetes is overweight or obesity. Almost 90% of people living with type 2 diabetes are overweight or have obesity. People who are overweight or have obesity have added pressure on their body's ability to use insulin to properly control blood sugar levels, and are therefore more likely to develop diabetes.” —Obesity Society via obesity.org

Users can utilize a number of interactive tools or access and download reports, fact sheets, slides, briefs and survey on various health topics. Background The Henry J. Kaiser Family Foundation is a non-partisan non-profit research and communications organization focused on major health care issues in the U.S. and around the world. Topics are organized by the following categories: health reform; Medicaid/ CHIP; Medicare; costs/ insurance; uninsured/ coverage; state policy; prescription drugs; HIV/ AIDS; U.S. Global Health Policy; minority health; women's health policy; and media and health. User Functionality Users can search for information by health topic category. After selecting the health topic category of interest, users can narrow their search by report type and date range. Reports types are: charts and data; fact sheets; interactive tools; issue briefs; news releases; presentations; reports and studies; surveys; testimony; and video/ audio. Users can also begin their search by initially focusing on a specific report type and then searching by health topic and data range. Additionally, users can select "Fast Facts" from the Kaiser Family Foundation homepage to access a database of slides. Users can search for and download slides as PDF files or Powerpoint slides, or they can pick and choose specific slides and create a slideshow directly on the website. Information is available on an international/ global, U.S. national or U.S. state level. From the main website, users can move to other Kaiser Family Foundation sites that may be more tailored to their specific needs. On the StateHealthFacts.org website, individual state profiles and comparisons between or across all 50 states are available. The GlobalHealthFacts.org website allows users to compare different countries on an unlimited number of health indicators. Data Notes All data comes from the Kaiser Family Foundation's own research efforts, and new studie s and reports are frequently published.

Overview

New York, NY – Aug 11 , 2025: The U.S. digital health market is projected to grow from USD 94.8 billion in 2024 to USD 567.7 billion by 2034, at a CAGR of 19.6%. This rapid growth is largely driven by the rise in chronic diseases and an aging population. Many Americans now face long term conditions like diabetes and heart disease. Digital health tools such as mobile apps and remote monitoring allow patients to manage their care from home. This reduces the need for hospital visits and supports better long term health outcomes.

Government initiatives are playing a major role in this shift. Agencies like the Department of Health and Human Services (HHS) have introduced policies to expand telehealth and improve data protection. These efforts have made it easier for clinics and hospitals to adopt digital systems. Supportive regulations and financial incentives have boosted confidence among healthcare providers. This has accelerated the use of electronic health records and virtual care, making healthcare more accessible and efficient across the U.S.

The COVID-19 pandemic changed how people access healthcare. During lockdowns, many patients and doctors used telehealth for the first time. The experience was mostly positive, leading to continued use of remote care. Telemedicine now helps reduce wait times and improves access for people in rural areas. It also supports those with mobility issues or busy schedules. This shift to virtual care has become a permanent feature in the U.S. healthcare system, offering both convenience and broader reach.

Technology and internet access are also improving the quality of digital health services. Tools powered by artificial intelligence, secure cloud systems, and high speed networks have made care delivery faster and smarter. People are now using mobile apps to track fitness, medication, and mental health. This shift in consumer behavior reflects a broader demand for easy-to-use, tech driven health services. Digital tools now offer a more personalized and connected healthcare experience for both patients and providers.

Cost control is another reason digital health is expanding. The U.S. healthcare system is expensive, and there’s pressure to lower costs while maintaining care quality. Digital solutions help by reducing unnecessary hospital visits and streamlining services. Global bodies like the World Health Organization (WHO) have also encouraged digital health adoption to close care gaps. Strong data privacy systems and improved digital infrastructure continue to support nationwide growth and trust in digital healthcare services.

Demographic Trends and Health Outcomes in the U.S

Inequalities,Risk Factors and Access to Care

By Data Society [source]

About this dataset

This dataset contains key demographic, health status indicators and leading cause of death data to help us understand the current trends and health outcomes in communities across the United States. By looking at this data, it can be seen how different states, counties and populations have changed over time. With this data we can analyze levels of national health services use such as vaccination rates or mammography rates; review leading causes of death to create public policy initiatives; as well as identify risk factors for specific conditions that may be associated with certain populations or regions. The information from these files includes State FIPS Code, County FIPS Code, CHSI County Name, CHSI State Name, CHSI State Abbreviation, Influenza B (FluB) report count & expected cases rate per 100K population , Hepatitis A (HepA) Report Count & expected cases rate per 100K population , Hepatitis B (HepB) Report Count & expected cases rate per 100K population , Measles (Meas) Report Count & expected cases rate per 100K population , Pertussis(Pert) Report Count & expected case rate per 100K population , CRS report count & expected case rate per 100K population , Syphilis report count and expected case rate per 100k popuation. We also look at measures related to preventive care services such as Pap smear screen among women aged 18-64 years old check lower/upper confidence intervals seperately ; Mammogram checks among women aged 40-64 years old specified lower/upper conifence intervals separetly ; Colonosopy/ Proctoscpushy among men aged 50+ measured in lower/upper limits ; Pneumonia Vaccination amongst 65+ with loewr/upper confidence level detail Additionally we have some interesting trend indicating variables like measures of birth adn death which includes general fertility ratye ; Teen Birth Rate by Mother's age group etc Summary Measures covers mortality trend following life expectancy by sex&age categories Vressionable populations access info gives us insight into disablilty ratio + access to envtiromental issues due to poor quality housing facilities Finally Risk Factors cover speicfic hoslitic condtiions suchs asthma diagnosis prevelance cancer diabetes alcholic abuse smoking trends All these information give a good understanding on Healthy People 2020 target setings demograpihcally speaking hence will aid is generating more evience backed policies

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

What the Dataset Contains

This dataset contains valuable information about public health relevant to each county in the United States, broken down into 9 indicator domains: Demographics, Leading Causes of Death, Summary Measures of Health, Measures of Birth and Death Rates, Relative Health Importance, Vulnerable Populations and Environmental Health Conditions, Preventive Services Use Data from BRFSS Survey System Data , Risk Factors and Access to Care/Health Insurance Coverage & State Developed Types of Measurements such as CRS with Multiple Categories Identified for Each Type . The data includes indicators such as percentages or rates for influenza (FLU), hepatitis (HepA/B), measles(MEAS) pertussis(PERT), syphilis(Syphilis) , cervical cancer (CI_Min_Pap_Smear - CI_MaxPap Smear), breast cancer (CIMin Mammogram - CI Max Mammogram ) proctoscopy (CI Min Proctoscopy - CI Max Proctoscopy ), pneumococcal vaccinations (Ci min Pneumo Vax - Ci max Pneumo Vax )and flu vaccinations (Ci min Flu Vac - Ci Max Flu Vac). Additionally , it provides information on leading causes of death at both county levels & national level including age-adjusted mortality rates due to suicide among teens aged between 15-19 yrs per 100000 population etc.. Furthermore , summary measures such as age adjusted percentage who consider their physical health fair or poor are provided; vulnerable populations related indicators like relative importance score for disabled adults ; preventive service use related ones ranging from self reported vaccination coverage among men40-64 yrs old against hepatitis B virus etc...

Getting Started With The Dataset

To get started with exploring this dataset first your need to understand what each column in the table represents: State FIPS Code identifies a unique identifier used by various US government agencies which denote states . County FIPS code denotes counties wi...

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

These data are being released in BETA version to facilitate early access to the study for research purposes. This collection has not been fully processed by NACDA or ICPSR at this time; the original materials provided by the principal investigator were minimally processed and converted to other file types for ease of use. As the study is further processed and given enhanced features by ICPSR, users will be able to access the updated versions of the study. Please report any data errors or problems to user support and we will work with you to resolve any data related issues. The National Health Interview Survey (NHIS) is conducted annually and sponsored by the National Center for Health Statistics (NCHS), which is part of the U.S. Public Health Service. The purpose of the NHIS is to obtain information about the amount and distribution of illness, its effects in terms of disability and chronic impairments, and the kinds of health services people receive across the United States population through the collection and analysis of data on a broad range of health topics. The redesigned NHIS questionnaire introduced in 1997 (see National Health Interview Survey, 1997 [ICPSR 2954]) consists of a core that remains largely unchanged from year to year, plus an assortment of supplements varying from year to year. The 2010 NHIS Core consists of three modules: Family, Sample Adult, and Sample Child. The datasets derived from these modules include Household Level, Family Level, Person Level, Injury/Poison Episode Level, Injury/Poison Verbatim Level, Sample Adult Level, and Sample Child level. The 2010 NHIS supplements consist of stand alone datasets for Cancer Level and Quality of Life data derived from the Sample Adult core and Disability Questions Tests 2010 Level derived from the Family core questionnaire. Additional supplementary questions can be found in the Sample Child dataset on the topics of cancer, immunization, mental health, and mental health services and in the Sample Adult dataset on the topics of epilepsy, immunization, and occupational health. Part 1, Household Level, contains data on type of living quarters, number of families in the household responding and not responding, and the month and year of the interview for each sampling unit. Parts 2-5 are based on the Family Core questionnaire. Part 2, Family Level, provides information on all family members with respect to family size, family structure, health status, limitation of daily activities, cognitive impairment, health conditions, doctor visits, hospital stays, health care access and utilization, employment, income, participation in government assistance programs, and basic demographic information. Part 3, Person Level, includes information on sex, age, race, marital status, education, family income, major activities, health status, health care costs, activity limits, and employment status. Parts 4 and 5, Injury/Poisoning Episode Level and Injury/Poisoning Verbatim Level, consist of questions about injuries and poisonings that resulted in medical consultations for any family members and contains information about the external cause and nature of the injury or poisoning episode and what the person was doing at the time of the injury or poisoning episode, in addition to the date and place of occurrence. A randomly-selected adult in each family was interviewed for Part 6, Sample Adult Level, regarding specific health issues, the relation between employment and health, health status, health care and doctor visits, limitation of daily activities, immunizations, and behaviors such as smoking, alcohol consumption, and physical activity. Demographic information, including occupation and industry, also was collected. The respondents to Part 6 also completed Part 7, Cancer Level, which consists of a set of supplemental questions about diet and nutrition, physical activity, tobacco, cancer screening, genetic testing, family history, and survivorship. Part 8, Sample Child Level, provides information from an adult in the household on medical conditions of one child in the household, such as developmental or intellectual disabilities, respiratory problems, seizures, allergies, and use of special equipment like hearing aids, braces, or wheelchairs. Parts 9 through 13 comprise the additional Supplements and Paradata for the 2010 NHIS. Part 9, Disability Questions Tests 2010 Level

A survey of adults in the United States found that around ** percent of respondents identified mobility issues, cancer, and cognitive decline as their top aging-related health concerns. This statistic depicts the percentage of adults in the United States who had select health concerns related to the aging process as of 2024.

The graph displays the most common waterborne diseases in the United States for the year 2014. The x-axis lists the diseases, including Otitis externa, Norovirus infection, Giardiasis, Cryptosporidiosis, and Campylobacteriosis, while the y-axis represents the estimated number of illnesses for each disease. In 2014, Otitis externa was the most prevalent waterborne disease, with an estimated 4,670,000 cases, significantly higher than the other diseases. Norovirus infections followed with approximately 1,330,000 illnesses. Giardiasis accounted for around 415,000 cases, Cryptosporidiosis had an estimated 322,000 cases, and Campylobacteriosis was the least common, with about 171,000 reported illnesses. The data highlights that Otitis externa overwhelmingly outnumbers the other waterborne diseases, indicating it as the predominant concern among water-related health issues in the U.S. during that year. The information is best represented in a bar graph format, effectively illustrating the comparative prevalence of each disease based on the estimated number of illnesses.

Digital Health And Wellness Market Outlook

The global digital health and wellness market size was valued at approximately USD 150 billion in 2023 and is projected to reach nearly USD 600 billion by 2032, growing at a compound annual growth rate (CAGR) of 16.5% during the forecast period. This substantial growth is primarily driven by the increasing adoption of digital health technologies, the rising prevalence of chronic diseases, and the continuous advancements in healthcare IT infrastructure.

One of the major growth factors contributing to the expansion of the digital health and wellness market is the rising prevalence of chronic diseases such as diabetes, cardiovascular diseases, and respiratory disorders. With an aging global population and changing lifestyles, the burden of chronic diseases is escalating, necessitating efficient and innovative healthcare solutions. Digital health technologies, such as telehealth and remote monitoring, offer significant advantages in managing these conditions by facilitating timely interventions and continuous monitoring, thereby improving patient outcomes and reducing healthcare costs.

Another significant factor driving the market growth is the increasing penetration of smartphones and the internet, coupled with the growing awareness and acceptance of digital health solutions among consumers and healthcare providers. Mobile health (mHealth) applications are becoming essential tools for health management, providing users with easy access to health information, remote consultations, and personalized health tracking. The convenience and accessibility offered by these digital health tools are encouraging more individuals to adopt them, leading to a surge in demand and market expansion.

The continuous advancements in healthcare IT infrastructure and the integration of advanced technologies such as artificial intelligence (AI), big data analytics, and the Internet of Things (IoT) are further propelling the digital health and wellness market. These technologies enable more precise diagnostics, personalized treatment plans, and efficient healthcare delivery. For instance, AI-powered algorithms can analyze vast amounts of health data to identify patterns and predict potential health issues, while IoT devices facilitate seamless data exchange between patients and healthcare providers, enhancing the overall efficiency of healthcare services.

Regionally, North America is leading the digital health and wellness market, driven by the high adoption rate of advanced healthcare technologies, supportive government policies, and significant investments in healthcare IT infrastructure. The United States, in particular, is at the forefront, with numerous digital health startups and established firms actively innovating in this space. However, other regions such as Europe and Asia Pacific are also witnessing substantial growth, fueled by increasing healthcare expenditures, rising awareness about digital health solutions, and the expansion of telehealth services.

Connected Health Solutions are becoming increasingly pivotal in the digital health and wellness market, as they offer a seamless integration of various healthcare services through digital platforms. These solutions enable real-time communication and data sharing between patients and healthcare providers, enhancing the quality and efficiency of care. By leveraging technologies such as IoT and AI, Connected Health Solutions facilitate continuous monitoring and personalized healthcare, which is particularly beneficial for managing chronic conditions. The ability to connect different healthcare systems and devices ensures that patients receive comprehensive and coordinated care, reducing the risk of errors and improving overall health outcomes. As the demand for integrated healthcare solutions grows, Connected Health Solutions are set to play a crucial role in transforming the healthcare landscape.

Component Analysis

The digital health and wellness market is segmented by component into software, hardware, and services. Each component plays a crucial role in the functionality and efficiency of digital health solutions, and their interplay determines the overall effectiveness of digital health systems. Software, as a component, encompasses a wide array of applications, including electronic health records (EHRs), telehealth platforms, a

IntroductionCommunity-acquired pneumonia (CAP) is a major health concern in the United States (US), with its incidence, severity, and outcomes influenced by social determinants of health, including socioeconomic status. The impact of neighborhood socioeconomic status, as measured by the Distressed Communities Index (DCI), on CAP-related admissions remains understudied in the literature.ObjectiveTo determine the independent association between DCI and CAP-related admissions in Maryland.MethodsWe conducted a retrospective study using the Maryland State Inpatient Database (SID) to collate data on CAP-related admissions from January 2018 to December 2020. The study included adults aged 18–85 years. We explored the independent association between community-level economic deprivation based on DCI quintiles and CAP-related admissions, adjusting for significant covariates.ResultsIn the study period, 61,467 cases of CAP-related admissions were identified. The patients were predominantly White (49.7%) and female (52.4%), with 48.6% being over 65 years old. A substantive association was found between the DCI and CAP-related admissions. Compared to prosperous neighborhoods, patients living in economically deprived communities had 43% increased odds of CAP-related admissions.ConclusionResidents of the poorest neighborhoods in Maryland have the highest risk of CAP-related admissions, emphasizing the need to develop effective public health strategies beneficial to the at-risk patient population.

Snapshot img

Big Data Spending In Healthcare Sector Market Size 2025-2029

The big data spending in healthcare sector market size is valued to increase by USD 7.78 billion, at a CAGR of 10.2% from 2024 to 2029. Need to improve business efficiency will drive the big data spending in healthcare sector market.

Market Insights

APAC dominated the market and accounted for a 31% growth during the 2025-2029.
By Service - Services segment was valued at USD 5.9 billion in 2023
By Type - Descriptive analytics segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 108.28 million 
Market Future Opportunities 2024: USD 7783.80 million
CAGR from 2024 to 2029 : 10.2%

Market Summary

The healthcare sector's adoption of big data analytics is a global trend that continues to gain momentum, driven by the need to improve business efficiency, enhance patient care, and ensure regulatory compliance. Big data in healthcare refers to the large and complex data sets generated from various sources, including Electronic Health Records, medical devices, and patient-generated data. This data holds immense potential for identifying patterns, predicting outcomes, and driving evidence-based decision-making. One real-world scenario illustrating this is supply chain optimization. Hospitals and healthcare providers can leverage big data analytics to optimize their inventory management, reduce wastage, and ensure timely availability of essential medical supplies.
For instance, predictive analytics can help anticipate demand for specific medical equipment or supplies, enabling healthcare providers to maintain optimal stock levels and minimize the risk of stockouts or overstocking. However, the adoption of big data analytics in healthcare is not without challenges. Data privacy and security concerns related to patients' medical data are a significant concern, with potential risks ranging from data breaches to unauthorized access. Ensuring robust Data security measures and adhering to regulatory guidelines, such as the Health Insurance Portability and Accountability Act (HIPAA) in the US, is essential for maintaining trust and protecting sensitive patient information.
In conclusion, the use of big data analytics in healthcare is a transformative trend that offers numerous benefits, from improved operational efficiency to enhanced patient care and regulatory compliance. However, it also presents challenges related to data privacy and security, which must be addressed to fully realize the potential of this technology.

What will be the size of the Big Data Spending In Healthcare Sector Market during the forecast period?

Get Key Insights on Market Forecast (PDF) Request Free Sample

The market continues to evolve, with recent research indicating a significant increase in investments. This growth is driven by the need for improved patient care, regulatory compliance, and cost savings. One trend shaping the market is the adoption of advanced analytics techniques to gain insights from large datasets. For instance, predictive analytics is being used to identify potential health risks and improve patient outcomes.
Additionally, data visualization software and data analytics platforms are essential tools for healthcare organizations to make data-driven decisions. Compliance is another critical area where big data is making a significant impact. With the increasing amount of patient data being generated, there is a growing need for data security and privacy. Data encryption methods and data anonymization techniques are being used to protect sensitive patient information. Budgeting is also a significant consideration for healthcare organizations investing in big data. Cost benefit analysis and statistical modeling are essential tools for evaluating the return on investment of big data initiatives.
As healthcare organizations continue to invest in big data, they must balance the benefits against the costs to ensure they are making informed decisions. In conclusion, the market is experiencing significant growth, driven by the need for improved patient care, regulatory compliance, and cost savings. The adoption of advanced analytics techniques, data visualization software, and data analytics platforms is essential for healthcare organizations to gain insights from large datasets and make data-driven decisions. Additionally, data security and privacy are critical considerations, with data encryption methods and data anonymization techniques being used to protect sensitive patient information.
Budgeting is also a significant consideration, with cost benefit analysis and statistical modeling essential tools for evaluating the return on investment of big data initiatives.

Unpacking the Big Data Spending In Healthcare Sector Market Landscape

In the dynamic healthcare sector, the adoption of big data technologies has become a st

Latin America Specialized Formula Medical Nutrition Market Size was valued at USD 1.6 Billion in 2024 and is projected to reach USD 2.71 Billion by 2031, growing at a CAGR of 7.47% from 2024 to 2031.

Latin America Specialized Formula Medical Nutrition Market Drivers

Growing Chronic Illness Prevalence: Specialized medical nutrition is in high demand due to the rise in chronic diseases like diabetes, obesity, and cardiovascular problems. Tailored nutritional formulae created to support particular health issues have become increasingly important as healthcare systems concentrate on preventative measures and therapy for these diseases.

Population Aging: With an aging population, Latin America is undergoing a demographic change. Nutritional demands specific to age-related health conditions, like sarcopenia or malnutrition, are common in older persons. There has been a sharp increase in the development of products targeted at older consumers as a result of this demographic change, which is pushing the need for specialty formulae that meet the nutritional gaps common in this age range.