Mental Health in the Tech Industry

Exploring Mental Health Conditions in the Tech Industry

By Olga Tsubiks [source]

About this dataset

This dataset contains survey responses from the tech industry about mental health, offering an insightful snapshot into the diagnoses, treatments, and attitudes of those in the field towards mental health. These data points allow people to understand more about how their peers in tech view mental health and can provide greater insight into how to better support those who work in this industry. This dataset includes questions on whether or not respondents have had a mental health disorder or sought treatment for a mental health issue in the past, if they currently have been diagnosed with a condition and what it is, their age group, location of work and residence as well as information on whether they are self-employed or working at a tech company with other questions. Additionally, this dataset also provides insight into respondents' attitudes towards speaking openly about their mental wellbeing versus physical wellbeing. To gain even more understanding of individual's experiences within their place of business overall employee count is included as well what role they fill within that organisation is related to technology/IT. This valuable data set may be used for medical research furthering our knowledge about workplace stressors effecting people seen within this particular field but also across multiple industries to help create support systems that reflect upon individual need rather than one-size fits all models previously employed by employers through out many parts globally

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Research Ideas

• Analyze the correlation between employment industry and mental health status, including self-identified diagnosis, use of mental health services and any history of mental illness in the family.
• Determine if there are differences in how people experience and speak out about their own mental health based on geographic location.
• Compare attitudes towards open conversations on physical vs mental health within different age groups both in the U.S. and abroad

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: OSMI_Survey_Data.csv | Column name | Description | |:-----------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------| | Are you selfemployed | Indicates whether the respondent is self-employed or not. (Boolean) | | How many employees does your company or organization have | Indicates the number of employees in the respondent's company or organization. (Numeric) | | Is your employer primarily a tech companyorganization | Indicates whether the respondent's employer is primarily a tech company or organization. (Boolean) | | Is your primary role within your company related to techIT | Indicates whether the respondent's primary role within their company is related to tech or IT. (Boolean) | | Do you have previous employers | Indicates whether the respondent has had previous employers. (Boolean) ...

Between January and September 2024, healthcare organizations in the United States saw 491 large-scale data breaches, resulting in the loss of over 500 records. This figure has increased significantly in the last decade. To date, the highest number of large-scale data breaches in the U.S. healthcare sector was recorded in 2023, with a reported 745 cases.

Context

Health care in the United States is provided by many distinct organizations. Health care facilities are largely owned and operated by private sector businesses. 58% of US community hospitals are non-profit, 21% are government owned, and 21% are for-profit. According to the World Health Organization (WHO), the United States spent more on healthcare per capita ($9,403), and more on health care as percentage of its GDP (17.1%), than any other nation in 2014. Many different datasets are needed to portray different aspects of healthcare in US like disease prevalences, pharmaceuticals and drugs, Nutritional data of different food products available in US. Such data is collected by surveys (or otherwise) conducted by Centre of Disease Control and Prevention (CDC), Foods and Drugs Administration, Center of Medicare and Medicaid Services and Agency for Healthcare Research and Quality (AHRQ). These datasets can be used to properly review demographics and diseases, determining start ratings of healthcare providers, different drugs and their compositions as well as package informations for different diseases and for food quality. We often want such information and finding and scraping such data can be a huge hurdle. So, Here an attempt is made to make available all US healthcare data at one place to download from in csv files.

Content

• Nhanes Survey (National Health and Nutrition Examination Survey) - The National Health and Nutrition Examination Survey (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. The survey is unique in that it combines interviews and physical examinations. NHANES is a major program of the National Center for Health Statistics (NCHS). NCHS is part of the Centers for Disease Control and Prevention (CDC) and has the responsibility for producing vital and health statistics for the Nation. The NHANES interview includes demographic, socioeconomic, dietary, and health-related questions. The examination component consists of medical, dental, and physiological measurements, as well as laboratory tests administered by highly trained medical personnel. The diseases, medical conditions, and health indicators to be studied include: Anemia, Cardiovascular disease, Diabetes, Environmental exposures, Eye diseases, Hearing loss, Infectious diseases, Kidney disease, Nutrition, Obesity, Oral health, Osteoporosis, Physical fitness and physical functioning, Reproductive history and sexual behavior, Respiratory disease (asthma, chronic bronchitis, emphysema), Sexually transmitted diseases, Vision. 10000 individuals are surveyed to represent US statistics. Five files in this datasets represent current recent Nhanes data -
  Nhanes_2005_2006.csv
  Nhanes_2007_2008.csv
  Nhanes_2009_2010.csv
  Nhanes_2011_2012.csv
  Nhanes_2013_2014.csv
  
  • Data fields' description -
    • Nhanes_2005_2006.csv - Demographic, Dietary, Examinations, Laboratory
    • Nhanes_2007_2008.csv - Demographic, Dietary, Examinations, Laboratory
    • Nhanes_2009_2010.csv - Demographic, Dietary, Examinations, Laboratory
    • Nhanes_2011_2012.csv - Demographic, Dietary, [Examinations](http://https://wwwn.cdc.gov/nchs/nhanes/search/variab...

In 2023, there were more than *** incidents of data compromises in the healthcare sector in the United States. Reaching its all-time highest. This indicates a significant growth since 2005 when the industry saw only ** cases of data compromises in the country.

This dataset is about companies. It has 26 rows and is filtered where the industry is Health Care REITs. It features 30 columns including city, country, employees, and employee type.

This dataset is about companies. It has 12,992 rows and is filtered where the industry is Health Care Equipment & Supplies. It features 30 columns including city, country, employees, and employee type.

The big data in healthcare market size is estimated to grow from USD 78 billion in 2024 to USD 540 billion by 2035, representing a CAGR of 19.20% till 2035

The researcher tests the QA capability of ChatGPT in the medical field from the following aspects:1. Test their reserve capacity for medical knowledge2. Check their ability to read literature and understand medical literature3. Test their ability of auxiliary diagnosis after reading case data4. Test its error correction ability for case data5. Test its ability to standardize medical terms6. Test their evaluation ability to experts7. Check their ability to evaluate medical institutionsThe conclusion is:ChatGPT has great potential in the application of medical and health care, and may directly replace human beings or even professionals at a certain level in some fields;The researcher preliminarily believe that ChatGPT has basic medical knowledge and the ability of multiple rounds of dialogue, and its ability to understand Chinese is not weak;ChatGPT has the ability to read, understand and correct cases;ChatGPT has the ability of information extraction and terminology standardization, and is quite excellent;ChatGPT has the reasoning ability of medical knowledge;ChatGPT has the ability of continuous learning. After continuous training, its level has improved significantly;ChatGPT does not have the academic evaluation ability of Chinese medical talents, and the results are not ideal;ChatGPT does not have the academic evaluation ability of Chinese medical institutions, and the results are not ideal;ChatGPT is an epoch-making product, which can become a useful assistant for medical diagnosis and treatment, knowledge service, literature reading, review and paper writing.

The global healthcare financial software market is experiencing robust growth, projected to reach $17.64 billion in 2025 and expanding at a compound annual growth rate (CAGR) of 25% from 2025 to 2033. This significant expansion is driven by several key factors. Firstly, the increasing adoption of electronic health records (EHRs) and the growing need for efficient revenue cycle management (RCM) are fueling demand for sophisticated software solutions. Hospitals and healthcare providers are under pressure to improve operational efficiency, reduce administrative costs, and enhance financial performance. Healthcare financial software offers a powerful tool to achieve these goals by automating processes, improving data analytics, and providing real-time insights into financial performance. Furthermore, the rising prevalence of chronic diseases and an aging population are leading to increased healthcare expenditures, emphasizing the need for better financial management within the healthcare sector. The market's segmentation into claim analytics, RCM, risk management analytics, and others reflects the diverse functionalities and applications of these software solutions. The software and services component holds a dominant market share, driven by continuous innovation and the need for comprehensive, integrated solutions. The cloud-based deployment model is gaining traction due to its scalability, cost-effectiveness, and accessibility. Major players like CVS Health, SAS Institute Inc., McKesson Corporation, and others are shaping the market landscape through continuous innovation and strategic partnerships. Geographic expansion is also a key driver, with North America currently holding a substantial market share due to high adoption rates and advanced technological infrastructure. However, emerging economies in Asia-Pacific and other regions are poised for rapid growth, driven by increasing healthcare spending and government initiatives to modernize healthcare systems. The competitive landscape is marked by both established players and emerging technology providers, leading to ongoing innovation and a diverse range of solutions available to healthcare organizations. The market's future growth will be influenced by factors such as regulatory changes, technological advancements (e.g., AI and machine learning), and the ongoing digital transformation within the healthcare industry. Recent developments include: In May 2022, the Clarify Health Institute is a cutting-edge research division established by Clarify Health, a leading cloud analytics, and value-based payments platform company, to provide practical analysis and data-driven insights on issues and trends affecting healthcare organizations, policymakers, and patients., In January 2022, following the signing of a legally binding agreement, Francisco Partners acquired healthcare data and analytics assets from IBM that were previously a part of the Watson Health business. Francisco Partners is a well-known international investment firm that specializes in working with technology companies.. Key drivers for this market are: Emergence of Big Data in Healthcare, Growing Awareness For Digital Technologies; Technological Advancements Making Data Handling Easy. Potential restraints include: Lack of Properly Trained IT Professionals in Healthcare. Notable trends are: Cloud Based Segment is Expected to Show Significant Growth over the Forecast Period.

The European Healthcare Big Data Analytics market is booming, with a 19% CAGR. This in-depth analysis explores market size, key drivers, trends, restraints, and leading companies, offering valuable insights for stakeholders. Discover the future of healthcare analytics in Europe. Recent developments include: May 2022 : The European Health Data Space was introduced by the European Commission (EHDS). The EHDS should assist the EU in significantly improving how healthcare is supplied to people throughout Europe. People should be able to manage and use their health information in their nation or another Member State. It should promote a single market for services and goods related to digital health. Additionally, it should guarantee complete adherence to the stringent data protection requirements set by the EU and provide a consistent, reliable, and effective framework for using health data for research, innovation, policy-making, and regulatory activities., November 2022 : The largest health services provider in Israel, Clalit, and IQVIA, a leading global provider of advanced analytics, technological solutions, and clinical research services to the life sciences sector, have announced a long-term partnership. The partnership assures IQVIA it can meet the pharmaceutical industry's interest in Israel as a top location for research and innovation by combining Clalit's aim to improve policy and healthcare with IQVIA's Connected Intelligence.. Key drivers for this market are: Reduced Cost of Care and Prediction of Possible Emergency Services, Increasing Evidence-based Activities and Shift from Volume- to Value-based Commissioning. Potential restraints include: Reduced Cost of Care and Prediction of Possible Emergency Services, Increasing Evidence-based Activities and Shift from Volume- to Value-based Commissioning. Notable trends are: Clinical Data Analytics to Witness Significant Growth Over the Forecast Period.

Update — December 7, 2014. – Evidence-based medicine (EBM) is not working for many reasons, for example: 1. Incorrect in their foundations (paradox): hierarchical levels of evidence are supported by opinions (i.e., lowest strength of evidence according to EBM) instead of real data collected from different types of study designs (i.e., evidence). http://dx.doi.org/10.6084/m9.figshare.1122534 2. The effect of criminal practices by pharmaceutical companies is only possible because of the complicity of others: healthcare systems, professional associations, governmental and academic institutions. Pharmaceutical companies also corrupt at the personal level, politicians and political parties are on their payroll, medical professionals seduced by different types of gifts in exchange of prescriptions (i.e., bribery) which very likely results in patients not receiving the proper treatment for their disease, many times there is no such thing: healthy persons not needing pharmacological treatments of any kind are constantly misdiagnosed and treated with unnecessary drugs. Some medical professionals are converted in K.O.L. which is only a puppet appearing on stage to spread lies to their peers, a person supposedly trained to improve the well-being of others, now deceits on behalf of pharmaceutical companies. Probably the saddest thing is that many honest doctors are being misled by these lies created by the rules of pharmaceutical marketing instead of scientific, medical, and ethical principles. Interpretation of EBM in this context was not anticipated by their creators. “The main reason we take so many drugs is that drug companies don’t sell drugs, they sell lies about drugs.” ―Peter C. Gøtzsche “doctors and their organisations should recognise that it is unethical to receive money that has been earned in part through crimes that have harmed those people whose interests doctors are expected to take care of. Many crimes would be impossible to carry out if doctors weren’t willing to participate in them.” —Peter C Gøtzsche, The BMJ, 2012, Big pharma often commits corporate crime, and this must be stopped. Pending (Colombia): Health Promoter Entities (In Spanish: EPS ―Empresas Promotoras de Salud).

1. Misinterpretations New technologies or concepts are difficult to understand in the beginning, it doesn’t matter their simplicity, we need to get used to new tools aimed to improve our professional practice. Probably the best explanation is here in these videos (credits to Antonio Villafaina for sharing these videos with me). English https://www.youtube.com/watch?v=pQHX-SjgQvQ&w=420&h=315 Spanish https://www.youtube.com/watch?v=DApozQBrlhU&w=420&h=315 ----------------------- Hypothesis: hierarchical levels of evidence based medicine are wrong Dear Editor, I have data to support the hypothesis described in the title of this letter. Before rejecting the null hypothesis I would like to ask the following open question:Could you support with data that hierarchical levels of evidence based medicine are correct? (1,2) Additional explanation to this question: – Only respond to this question attaching publicly available raw data.– Be aware that more than a question this is a challenge: I have data (i.e., evidence) which is contrary to classic (i.e., McMaster) or current (i.e., Oxford) hierarchical levels of evidence based medicine. An important part of this data (but not all) is publicly available. References
2. Ramirez, Jorge H (2014): The EBM challenge. figshare. http://dx.doi.org/10.6084/m9.figshare.1135873
3. The EBM Challenge Day 1: No Answers. Competing interests: I endorse the principles of open data in human biomedical research Read this letter on The BMJ – August 13, 2014.http://www.bmj.com/content/348/bmj.g3725/rr/762595Re: Greenhalgh T, et al. Evidence based medicine: a movement in crisis? BMJ 2014; 348: g3725. _ Fileset contents Raw data: Excel archive: Raw data, interactive figures, and PubMed search terms. Google Spreadsheet is also available (URL below the article description). Figure 1. Unadjusted (Fig 1A) and adjusted (Fig 1B) PubMed publication trends (01/01/1992 to 30/06/2014). Figure 2. Adjusted PubMed publication trends (07/01/2008 to 29/06/2014) Figure 3. Google search trends: Jan 2004 to Jun 2014 / 1-week periods. Figure 4. PubMed publication trends (1962-2013) systematic reviews and meta-analysis, clinical trials, and observational studies.
   Figure 5. Ramirez, Jorge H (2014): Infographics: Unpublished US phase 3 clinical trials (2002-2014) completed before Jan 2011 = 50.8%. figshare.http://dx.doi.org/10.6084/m9.figshare.1121675 Raw data: "13377 studies found for: Completed | Interventional Studies | Phase 3 | received from 01/01/2002 to 01/01/2014 | Worldwide". This database complies with the terms and conditions of ClinicalTrials.gov: http://clinicaltrials.gov/ct2/about-site/terms-conditions Supplementary Figures (S1-S6). PubMed publication delay in the indexation processes does not explain the descending trends in the scientific output of evidence-based medicine. Acknowledgments I would like to acknowledge the following persons for providing valuable concepts in data visualization and infographics:
4. Maria Fernanda Ramírez. Professor of graphic design. Universidad del Valle. Cali, Colombia.
5. Lorena Franco. Graphic design student. Universidad del Valle. Cali, Colombia. Related articles by this author (Jorge H. Ramírez)
6. Ramirez JH. Lack of transparency in clinical trials: a call for action. Colomb Med (Cali) 2013;44(4):243-6. URL: http://www.ncbi.nlm.nih.gov/pubmed/24892242
7. Ramirez JH. Re: Evidence based medicine is broken (17 June 2014). http://www.bmj.com/node/759181
8. Ramirez JH. Re: Global rules for global health: why we need an independent, impartial WHO (19 June 2014). http://www.bmj.com/node/759151
9. Ramirez JH. PubMed publication trends (1992 to 2014): evidence based medicine and clinical practice guidelines (04 July 2014). http://www.bmj.com/content/348/bmj.g3725/rr/759895 Recommended articles
10. Greenhalgh Trisha, Howick Jeremy,Maskrey Neal. Evidence based medicine: a movement in crisis? BMJ 2014;348:g3725
11. Spence Des. Evidence based medicine is broken BMJ 2014; 348:g22
12. Schünemann Holger J, Oxman Andrew D,Brozek Jan, Glasziou Paul, JaeschkeRoman, Vist Gunn E et al. Grading quality of evidence and strength of recommendations for diagnostic tests and strategies BMJ 2008; 336:1106
13. Lau Joseph, Ioannidis John P A, TerrinNorma, Schmid Christopher H, OlkinIngram. The case of the misleading funnel plot BMJ 2006; 333:597
14. Moynihan R, Henry D, Moons KGM (2014) Using Evidence to Combat Overdiagnosis and Overtreatment: Evaluating Treatments, Tests, and Disease Definitions in the Time of Too Much. PLoS Med 11(7): e1001655. doi:10.1371/journal.pmed.1001655
15. Katz D. A-holistic view of evidence based medicinehttp://thehealthcareblog.com/blog/2014/05/02/a-holistic-view-of-evidence-based-medicine/ ---

China Number of Employee: Urban Non-private: Health Care and Social Work data was reported at 11.269 Person mn in Dec 2023. This records an increase from the previous number of 11.145 Person mn for Dec 2022. China Number of Employee: Urban Non-private: Health Care and Social Work data is updated quarterly, averaging 8.252 Person mn from Mar 2012 (Median) to Dec 2023, with 21 observations. The data reached an all-time high of 11.269 Person mn in Dec 2023 and a record low of 6.924 Person mn in Mar 2012. China Number of Employee: Urban Non-private: Health Care and Social Work data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Labour Market – Table CN.GB: No of Employee: by Industry: Quarterly.

Home care providers support the overall health and well-being of millions in the US annually. This number has been growing fast, expanding the scale and scope of home care providers in recent years. A rising number of adults 65 and older has been the primary driver behind this, as older adults are at a higher risk of developing a condition or experiencing an injury that limits their ability to perform tasks they once did independently. While changing demographic trends are an overarching trend impacting the health sector, the pandemic has permanently altered the industry's trajectory. Widespread outbreaks at residential facilities in the first year of the pandemic led more people to value remaining in their homes as they age; the interest in aging-in-place has only grown even as pandemic concerns have dissipated, as older adults look for options that provide safety and independence. In all, revenue has been expanding at a CAGR of 3.7% to an estimated $155.9 billion over the past five years, including expected growth of 3.2% in 2025. The mounting need for home care services and a shortage of home health aides create a mismatch between supply and demand that limits revenue growth. Shortages, preexisting the pandemic, have worsened as caregivers seek more flexible jobs with higher pay, creating increasingly high turnover that pressures providers to raise wages. Medicare and Medicaid reimbursements to home health agencies have been declining for several years, preventing home health agencies from raising salaries despite shortages. Clients eligible for home care services through insurance face long waits, leading more people to opt for self-directed care, where family members or friends work as caregivers. Too few caregivers prevent the industry from fully benefiting from rising demand and curtail profit growth. Trends driving growth in recent years will continue, providing various opportunities for home care providers. How home care providers capitalize on these trends will depend on insurer reimbursements and workforce development. Technology, ranging from wearables to telehealth, will have a more prominent role in the industry as providers look for ways to improve patient care while lessening the burden on staff. Regulatory and financial pressures will maintain consolidation activity, with private equity investment likely to expand. A significant headwind facing the industry will be the future of Medicare policies, the extent to which they cover home health and how states will react to Medicaid cuts in the Trump Administration's Big Beautiful Bill. Revenue will grow at a CAGR of 2.9% to an estimated $179.8 billion over the next five years.

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 2032, growing at a CAGR of 13.92% during the forecast period 2026-2032.Global Real World Evidence Solutions Market DriversThe 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.

This dataset provides information on the closing price, high price, low price, and volume of stocks for the top 10 companies in the healthcare sector. The dataset consists of time-series data, covering daily stock market data from 2000 to 2023.

The dataset includes the following columns:

Date: Date Company: Company name Close: Closing price of the stock High: High price of the stock Low: Low price of the stock Volume: Volume of trades The data is sourced using the Googlefinance function in Google Sheets, and the selection of the top 10 healthcare companies is based on information from the article "World's Top 10 Health Care Companies" published on Investopedia (https://www.investopedia.com/articles/markets/030916/worlds-top-10-health-care-companies-unh-mdt.asp).

This dataset can be used for various data analysis purposes, such as stock market analysis, predictive modeling, and statistical analysis. However, it is important to note that this dataset is provided for informational purposes only and should not be considered as financial advice or a recommendation for investment decisions. It is always advisable to consult with a professional financial consultant before making any investment decisions.

Electronic health records (EHR) are expected to boost the market value of smart hospitals. In 2021, the global smart hospital market was valued at **** billion U.S. dollars, from which *** billion were linked to EHR and the consequent clinical workflow. According to future estimations, this market was forecast to increase in value and reach nearly ** billion U.S. dollars in 2026. The use of electronic health records in hospitals EHR systems improve the quality and efficiency of healthcare delivery and enable patients more autonomy in their treatment. In 2020, over ** percent of surveyed European clinicians used electronic health records in their practice. According to the same survey, in countries such as the Netherlands or Denmark, nearly *** practicians used EHRs. The implementation of these medical records plays a central role in the emergence of smart hospitals. Data privacy and electronic health records Although the global EHR market is projected to steadily increase in the future, EHR use still raises some issues. Indeed, an electronic health record encompasses private information on a patient that can be shared across a range of healthcare settings. Thus, it presents challenges in terms of access control to ensure data privacy and confidentiality. These risks need to be addressed through legal frameworks, optimal access controls, quality training, and standards shared across all EHR users.

Salutary Data is a boutique, B2B contact and company data provider that's committed to delivering high quality data for sales intelligence, lead generation, marketing, recruiting / HR, identity resolution, and ML / AI. Our database currently consists of 148MM+ highly curated B2B Contacts ( US only), along with over 4M+ companies, and is updated regularly to ensure we have the most up-to-date information.

We can enrich your in-house data ( CRM Enrichment, Lead Enrichment, etc.) and provide you with a custom dataset ( such as a lead list) tailored to your target audience specifications and data use-case. We also support large-scale data licensing to software providers and agencies that intend to redistribute our data to their customers and end-users.

What makes Salutary unique? - We offer our clients a truly unique, one-stop aggregation of the best-of-breed quality data sources. Our supplier network consists of numerous, established high quality suppliers that are rigorously vetted. - We leverage third party verification vendors to ensure phone numbers and emails are accurate and connect to the right person. Additionally, we deploy automated and manual verification techniques to ensure we have the latest job information for contacts. - We're reasonably priced and easy to work with.

Products: API Suite Web UI Full and Custom Data Feeds

Services: Data Enrichment - We assess the fill rate gaps and profile your customer file for the purpose of appending fields, updating information, and/or rendering net new “look alike” prospects for your campaigns. ABM Match & Append - Send us your domain or other company related files, and we’ll match your Account Based Marketing targets and provide you with B2B contacts to campaign. Optionally throw in your suppression file to avoid any redundant records. Verification (“Cleaning/Hygiene”) Services - Address the 2% per month aging issue on contact records! We will identify duplicate records, contacts no longer at the company, rid your email hard bounces, and update/replace titles or phones. This is right up our alley and levers our existing internal and external processes and systems.

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US Population Health Management (PHM) Market Size 2025-2029

The us population health management (phm) market size is forecast to increase by USD 6.04 billion at a CAGR of 7.4% between 2024 and 2029.

The Population Health Management (PHM) market in the US is experiencing significant growth, driven by the increasing adoption of healthcare IT solutions and analytics. These technologies enable healthcare providers to collect, analyze, and act on patient data to improve health outcomes and reduce costs. However, the high perceived costs associated with PHM solutions pose a challenge for some organizations, limiting their ability to fully implement and optimize these technologies. Despite this obstacle, the potential benefits of PHM, including improved patient care and population health, make it a strategic priority for many healthcare organizations. To capitalize on this opportunity, companies must focus on cost-effective solutions and innovative approaches to addressing the challenges of PHM implementation and optimization. By leveraging advanced analytics, cloud technologies, and strategic partnerships, organizations can overcome cost barriers and deliver better care to their patient populations.

What will be the size of the US Population Health Management (PHM) Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The Population Health Management (PHM) market in the US is experiencing significant advancements, integrating various elements to improve patient outcomes and reduce healthcare costs. Public health surveillance and data governance ensure accurate population health data, enabling healthcare leaders to identify health disparities and target interventions. Quality measures and health literacy initiatives promote transparency and patient activation, while data visualization and business intelligence facilitate data-driven decision-making. Behavioral health integration, substance abuse treatment, and mental health services address the growing need for holistic care, and outcome-based contracts incentivize providers to focus on patient outcomes. Health communication, community health workers, and patient portals enhance patient engagement, while wearable devices and mHealth technologies provide real-time data for personalized care plans. Precision medicine and predictive modeling leverage advanced analytics to tailor treatment approaches, and social service integration addresses the social determinants of health. Health data management, data storytelling, and healthcare innovation continue to drive market growth, transforming the industry and improving overall population health.

How is this market segmented?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. ProductSoftwareServicesDeploymentCloudOn-premisesEnd-userHealthcare providersHealthcare payersEmployers and government bodiesGeographyNorth AmericaUS

By Product Insights

The software segment is estimated to witness significant growth during the forecast period.

Population Health Management (PHM) software in the US gathers patient data from healthcare systems and utilizes advanced analytics tools, including data visualization and business intelligence, to predict health conditions and improve patient care. PHM software aims to enhance healthcare efficiency, reduce costs, and ensure quality patient care. By analyzing accurate patient data, PHM software enables the identification of community health risks, leading to proactive interventions and better health outcomes. The adoption of PHM software is on the rise in the US due to the growing emphasis on value-based care and the increasing prevalence of chronic diseases. Machine learning, artificial intelligence, and predictive analytics are integral components of PHM software, enabling healthcare payers to develop personalized care plans and improve care coordination. Data integration and interoperability facilitate seamless data sharing among various healthcare stakeholders, while data visualization tools help in making informed decisions. Public health agencies and healthcare providers leverage PHM software for population health research, disease management programs, and quality improvement initiatives. Cloud computing and data warehousing provide the necessary infrastructure for storing and managing large volumes of population health data. Healthcare regulations mandate the adoption of PHM software to ensure compliance with data privacy and security standards. PHM software also supports care management services, patient engagement platforms, and remote patient monitoring, empowering patients to take charge of their health. Welln

United States Number of Job Postings: Active: Health Care and Social Assistance data was reported at 2,024,906.000 Unit in 05 May 2025. This records a decrease from the previous number of 2,072,576.000 Unit for 28 Apr 2025. United States Number of Job Postings: Active: Health Care and Social Assistance data is updated weekly, averaging 333,079.000 Unit from Jan 2008 (Median) to 05 May 2025, with 905 observations. The data reached an all-time high of 4,309,137.000 Unit in 27 Feb 2023 and a record low of 65,426.000 Unit in 18 Feb 2008. United States Number of Job Postings: Active: Health Care and Social Assistance data remains active status in CEIC and is reported by Revelio Labs, Inc.. The data is categorized under Global Database’s United States – Table US.RL.JP: Number of Job Postings: Active: by Industry.

Graph and download economic data for Employment for Health Care and Social Assistance: General Medical and Surgical Hospitals (NAICS 622110) in the United States (IPURN622110W201000000) from 1988 to 2024 about surgical, general, hospitals, healthcare, medical, social assistance, health, NAICS, IP, employment, and USA.