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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

Healthcare Provider Population Health Management Software Market Outlook

According to our latest research, the global Healthcare Provider Population Health Management Software market size reached USD 15.2 billion in 2024. The market is projected to expand at a robust CAGR of 13.8% from 2025 to 2033, reaching approximately USD 47.2 billion by 2033. This impressive growth is primarily driven by the rising demand for value-based care, increasing healthcare data volumes, and the critical need for efficient patient management across diverse healthcare settings. The ongoing digital transformation in healthcare, coupled with regulatory mandates for data interoperability and quality reporting, continues to accelerate the adoption of advanced population health management solutions among providers worldwide.

One of the most significant growth factors propelling the Healthcare Provider Population Health Management Software market is the global shift from fee-for-service to value-based care models. Healthcare systems and providers are under increasing pressure to improve patient outcomes while controlling costs, necessitating robust tools for data aggregation, risk stratification, and care coordination. Population health management (PHM) software enables providers to analyze large datasets, identify at-risk populations, and proactively manage chronic diseases. The integration of electronic health records (EHRs), claims data, and social determinants of health into PHM platforms allows for a more holistic approach to patient care, driving better clinical and financial outcomes. Additionally, government initiatives and reforms, such as the Affordable Care Act in the United States and similar policies in Europe and Asia Pacific, are further incentivizing the adoption of PHM solutions by linking reimbursement to quality metrics and patient satisfaction.

Another critical driver is the rapid advancement of healthcare IT infrastructure and the proliferation of digital health technologies. The increasing adoption of cloud computing, artificial intelligence, and machine learning in healthcare is transforming the way providers manage patient populations. Modern PHM software platforms leverage these technologies to deliver predictive analytics, automate care management workflows, and facilitate real-time decision support. This technological evolution enables healthcare organizations to efficiently aggregate and analyze disparate data sources, streamline patient engagement, and optimize resource allocation. The growing emphasis on interoperability and data exchange standards, such as HL7 FHIR, is also fostering a more connected and integrated healthcare ecosystem, further enhancing the value proposition of PHM software.

Population Health Management is increasingly becoming a cornerstone in the healthcare industry, as it focuses on improving the health outcomes of entire populations. This approach involves the systematic collection and analysis of health-related data to identify patterns and trends that can inform healthcare strategies. By leveraging Population Health Management, providers can better understand the needs of their patient populations, tailor interventions to specific groups, and ultimately enhance the quality of care delivered. As healthcare systems worldwide continue to shift towards value-based care, the role of Population Health Management in driving efficiency and effectiveness in healthcare delivery is more critical than ever. This paradigm shift is not only improving patient outcomes but also helping to control rising healthcare costs by promoting preventive care and reducing unnecessary hospitalizations.

The COVID-19 pandemic has also played a pivotal role in accelerating the adoption of population health management solutions. The need for remote patient monitoring, telehealth, and coordinated care during the pandemic highlighted the importance of robust PHM platforms. Providers leveraged these tools to track disease outbreaks, manage high-risk patient cohorts, and allocate resources more effectively. As healthcare systems continue to adapt to the post-pandemic landscape, the focus on preventive care, chronic disease management, and population-level analytics is expected to remain strong, sustaining the long-term growth trajectory of the market. Furthermore, the increasing prevalence of chronic diseases, aging populations, and rising healthcare expenditures

The NIHR is one of the main funders of public health research in the UK. Public health research falls within the remit of a range of NIHR Research Programmes, NIHR Centres of Excellence and Facilities, plus the NIHR Academy. NIHR awards from all NIHR Research Programmes and the NIHR Academy that were funded between January 2006 and the present extraction date are eligible for inclusion in this dataset. An agreed inclusion/exclusion criteria is used to categorise awards as public health awards (see below). Following inclusion in the dataset, public health awards are second level coded to one of the four Public Health Outcomes Framework domains. These domains are: (1) wider determinants (2) health improvement (3) health protection (4) healthcare and premature mortality.More information on the Public Health Outcomes Framework domains can be found here.This dataset is updated quarterly to include new NIHR awards categorised as public health awards. Please note that for those Public Health Research Programme projects showing an Award Budget of £0.00, the project is undertaken by an on-call team for example, PHIRST, Public Health Review Team, or Knowledge Mobilisation Team, as part of an ongoing programme of work.Inclusion criteriaThe NIHR Public Health Overview project team worked with colleagues across NIHR public health research to define the inclusion criteria for NIHR public health research awards. NIHR awards are categorised as public health awards if they are determined to be ‘investigations of interventions in, or studies of, populations that are anticipated to have an effect on health or on health inequity at a population level.’ This definition of public health is intentionally broad to capture the wide range of NIHR public health awards across prevention, health improvement, health protection, and healthcare services (both within and outside of NHS settings). This dataset does not reflect the NIHR’s total investment in public health research. The intention is to showcase a subset of the wider NIHR public health portfolio. This dataset includes NIHR awards categorised as public health awards from NIHR Research Programmes and the NIHR Academy. This dataset does not currently include public health awards or projects funded by any of the three NIHR Research Schools or any of the NIHR Centres of Excellence and Facilities. Therefore, awards from the NIHR Schools for Public Health, Primary Care and Social Care, NIHR Public Health Policy Research Unit and the NIHR Health Protection Research Units do not feature in this curated portfolio.DisclaimersUsers of this dataset should acknowledge the broad definition of public health that has been used to develop the inclusion criteria for this dataset. This caveat applies to all data within the dataset irrespective of the funding NIHR Research Programme or NIHR Academy award.Please note that this dataset is currently subject to a limited data quality review. We are working to improve our data collection methodologies. Please also note that some awards may also appear in other NIHR curated datasets. Further informationFurther information on the individual awards shown in the dataset can be found on the NIHR’s Funding & Awards website here. Further information on individual NIHR Research Programme’s decision making processes for funding health and social care research can be found here.Further information on NIHR’s investment in public health research can be found as follows: NIHR School for Public Health here. NIHR Public Health Policy Research Unit here. NIHR Health Protection Research Units here. NIHR Public Health Research Programme Health Determinants Research Collaborations (HDRC) here. NIHR Public Health Research Programme Public Health Intervention Responsive Studies Teams (PHIRST) here.

For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.

Population Health Management Software Market Outlook

According to our latest research, the global population health management software market size reached USD 35.6 billion in 2024, demonstrating robust expansion driven by the increasing need for value-based care and digital transformation in the healthcare sector. The market is forecasted to grow at a CAGR of 13.7% from 2025 to 2033, reaching an estimated USD 110.2 billion by 2033. This remarkable growth is primarily attributed to the surge in chronic disease prevalence, rising healthcare costs, and the growing adoption of healthcare IT solutions worldwide.

A key growth factor fueling the population health management software market is the global shift toward value-based healthcare models. Healthcare systems are increasingly moving away from fee-for-service frameworks, instead prioritizing patient outcomes and cost-efficiency. Population health management software plays a pivotal role in this transition by aggregating and analyzing patient data from multiple sources, enabling healthcare providers to identify at-risk populations, optimize care delivery, and reduce unnecessary expenditures. The integration of advanced analytics and artificial intelligence within these platforms is further enhancing their ability to deliver actionable insights, improve patient engagement, and support preventive care strategies, which collectively drive market expansion.

Another significant driver for the market is the escalating burden of chronic diseases such as diabetes, cardiovascular disorders, and respiratory illnesses. With aging populations and lifestyle changes, the prevalence of these conditions is rising globally, necessitating proactive population health strategies. Population health management software empowers healthcare organizations to monitor patient cohorts, track disease progression, and implement targeted interventions. This not only improves clinical outcomes but also supports regulatory compliance and reimbursement requirements, particularly as governments and payers increasingly incentivize the management of chronic conditions through coordinated care and patient engagement initiatives.

The rapid digitalization of healthcare infrastructure, coupled with favorable government initiatives and funding, is also propelling the adoption of population health management software. Many countries are investing in electronic health records (EHRs), health information exchanges (HIEs), and interoperability standards to facilitate seamless data sharing across the care continuum. These developments are creating a fertile environment for the deployment of population health management solutions, which thrive on the availability of comprehensive, real-time patient data. Furthermore, the COVID-19 pandemic has accelerated the adoption of digital health tools, highlighting the critical importance of population health management in tracking outbreaks, managing resources, and improving public health outcomes.

From a regional perspective, North America continues to dominate the population health management software market, accounting for the largest share in 2024. This leadership is underpinned by advanced healthcare IT infrastructure, significant investments in digital health, and strong regulatory support for value-based care. However, the Asia Pacific region is expected to exhibit the fastest growth over the forecast period, driven by rising healthcare expenditure, expanding insurance coverage, and increasing focus on healthcare modernization in countries such as China, India, and Japan. Europe also remains a key market, benefiting from robust government initiatives aimed at improving healthcare quality and efficiency through digital solutions.

Component Analysis

The population health management software market is segmented by component into software and services, each playing a critical role in the overall ecosystem. The software segment encompasses a wide range of solutions, including data aggregation, analytics, care coordinatio

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Population Health Management Market Size 2025-2029

The population health management market size is valued to increase USD 19.40 billion, at a CAGR of 10.7% from 2024 to 2029. Rising adoption of healthcare IT will drive the population health management market.

Major Market Trends & Insights

North America dominated the market and accounted for a 68% growth during the forecast period.
By Component - Software segment was valued at USD 16.04 billion in 2023
By End-user - Large enterprises segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 113.32 billion
Market Future Opportunities: USD 19.40 billion
CAGR : 10.7%
North America: Largest market in 2023

Market Summary

The market encompasses a continually evolving landscape of core technologies and applications, service types, and regulatory frameworks. With the rising adoption of healthcare IT solutions, population health management platforms are increasingly being adopted to improve patient outcomes and reduce costs. According to a recent study, The market is expected to witness a significant growth, with over 30% of healthcare organizations implementing these solutions by 2025. The focus on personalized medicine and the need to manage the rising cost of healthcare are major drivers for this trend. Core technologies such as data analytics, machine learning, and telehealth are transforming the way healthcare providers manage patient populations.
Despite these opportunities, challenges such as data privacy concerns, interoperability issues, and the high cost of implementation persist. The market is further shaped by regional differences in regulatory frameworks and healthcare infrastructure. For instance, in North America, the Affordable Care Act has fueled the adoption of population health management solutions, while in Europe, the European Medicines Agency's focus on personalized medicine is driving demand.

What will be the Size of the Population Health Management Market during the forecast period?

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How is the Population Health Management Market Segmented and what are the key trends of market segmentation?

The population health management industry 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.

Component

  Software
  Services


End-user

  Large enterprises
  SMEs


Delivery Mode

  On-Premise
  Cloud-Based
  Web-Based
  On-Premise
  Cloud-Based


End-Use

  Providers
  Payers
  Employer Groups
  Government Bodies
  Providers
  Payers
  Employer Groups


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Component Insights

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

The market is experiencing significant growth, with the software segment playing a crucial role in this expansion. Currently, remote patient monitoring solutions are witnessing a 25% adoption rate, enabling healthcare providers to monitor patients' health in real-time and intervene promptly when necessary. Additionally, predictive modeling and risk stratification models are being utilized to identify high-risk patients and provide personalized care plans, contributing to a 21% increase in disease management efficiency. Furthermore, the integration of electronic health records, wellness programs, care coordination platforms, and value-based care models is fostering a data-driven approach to healthcare, leading to a 19% reduction in healthcare costs.

Health equity initiatives and healthcare data analytics are essential components of population health management, ensuring equitable access to care and improving healthcare quality metrics. Looking ahead, the market is expected to grow further, with utilization management and care management programs seeing a 27% increase in implementation. Preventive health programs and clinical decision support systems are also anticipated to experience a 24% surge in adoption, emphasizing the importance of proactive care and early intervention. Moreover, population health strategies are evolving to incorporate behavioral health integration, interoperability standards, and disease registry data to provide comprehensive care. The use of disease prevalence data and public health surveillance is becoming increasingly crucial in addressing population health challenges and improving overall health outcomes.

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The Software segment was valued at USD 16.04 billion in 2019 and showed a gradual increase during the forecast period.

In conclusion, the market is

Population Health Management Market Outlook

According to our latest research, the global population health management market size reached USD 34.7 billion in 2024, reflecting a robust expansion driven by technological integration and evolving healthcare needs. The market is expected to grow at a CAGR of 12.8% from 2025 to 2033, reaching a projected value of USD 102.3 billion by 2033. This impressive growth rate is primarily attributed to the increasing prevalence of chronic diseases, the shift toward value-based care models, and the rising adoption of digital health solutions by healthcare providers and payers worldwide. As per our latest research, the market is witnessing a significant transformation, with a strong emphasis on data-driven decision-making and patient-centric care models.

One of the most significant growth factors propelling the population health management market is the surging incidence of chronic diseases such as diabetes, cardiovascular disorders, and respiratory illnesses. As populations age and lifestyle-related health risks escalate globally, healthcare systems are under mounting pressure to deliver more effective and coordinated care. Population health management solutions offer a holistic approach by integrating clinical, financial, and operational data, enabling healthcare stakeholders to identify at-risk populations, implement targeted interventions, and monitor health outcomes in real-time. This proactive approach not only reduces the overall cost of care but also improves patient outcomes, making it a critical component in the transition from fee-for-service to value-based care models.

Another crucial driver for the population health management market is the rapid advancement and adoption of digital health technologies. The proliferation of electronic health records (EHRs), wearable health devices, telemedicine platforms, and artificial intelligence-powered analytics tools has revolutionized how healthcare data is collected, shared, and analyzed. These technologies empower healthcare providers to gain deeper insights into population health trends, personalize care plans, and enhance patient engagement. Furthermore, government initiatives and regulatory mandates supporting interoperability and data sharing are accelerating the adoption of population health management software and services, especially in developed regions. The integration of advanced analytics and machine learning further amplifies the ability to predict disease outbreaks and manage resource allocation efficiently.

A third major growth factor is the increasing focus on preventive healthcare and wellness programs by both public and private sector stakeholders. Employers, insurers, and government bodies are investing heavily in population health management solutions to reduce long-term healthcare expenditures and improve workforce productivity. Preventive health initiatives, such as vaccination programs, health risk assessments, and wellness coaching, are being seamlessly integrated into population health platforms. These efforts are supported by favorable reimbursement policies and incentives for adopting value-based payment models, which reward healthcare organizations for improving population health metrics. As a result, the market is experiencing widespread adoption across various end-user segments, including healthcare providers, payers, employer groups, and government organizations.

From a regional perspective, North America continues to dominate the population health management market, accounting for the largest share in 2024. This dominance is driven by the presence of advanced healthcare infrastructure, high healthcare IT adoption rates, and supportive government policies such as the Affordable Care Act in the United States. Europe follows closely, benefiting from strong regulatory frameworks and increasing investments in digital health transformation. Meanwhile, the Asia Pacific region is emerging as a high-growth market, fueled by rising healthcare expenditure, expanding insurance coverage, and the growing burden of chronic diseases. Latin America and the Middle East & Africa are also witnessing gradual adoption, although challenges such as limited healthcare IT infrastructure and regulatory complexities persist. Overall, the global market landscape is characterized by rapid technological advancements, evolving care delivery models, and a growing emphasis on population health outcomes.

The data package provides county-level data and rankings for measures that define the population health status and for a set factors with great influence on population health. The measures used to establish counties ranks are related to length and quality of life and to health behavior, clinical care, socioeconomic and environmental factors.

The Population Based Health Services market is experiencing robust growth, driven by increasing healthcare costs, a rising prevalence of chronic diseases, and the growing adoption of value-based care models. The market is projected to reach a significant size, with a Compound Annual Growth Rate (CAGR) demonstrating substantial expansion. While precise figures for market size and CAGR are not provided, considering the substantial interest in population health management and the technological advancements enabling it (such as cloud-based and web-based platforms), a reasonable estimation of the 2025 market size would fall within the range of $15-20 billion USD. A CAGR of 12-15% for the forecast period (2025-2033) seems plausible, reflecting the continued market expansion fueled by technological advancements and government initiatives promoting population health management. This growth is further bolstered by the increasing demand for efficient and cost-effective healthcare solutions across diverse segments such as healthcare providers, government bodies, and other organizations. The market's segmentation by delivery mode (cloud-based, web-based) and application (healthcare providers, government bodies, others) indicates a diversified landscape with multiple opportunities for growth across all segments. Significant trends shaping the market include the increasing adoption of telehealth and remote patient monitoring technologies, the growing focus on data analytics and predictive modeling for improved population health outcomes, and the rising demand for interoperability solutions to facilitate seamless data exchange. However, challenges like data privacy concerns, regulatory hurdles, and the need for skilled professionals to effectively manage and interpret population health data could potentially restrain the market's growth. Nevertheless, the overall outlook for the Population Based Health Services market remains positive, with strong growth anticipated in the coming years driven by continued technological innovation and an evolving healthcare landscape. The prominent players listed—IBM, Verisk Analytics, Health Catalyst, and others—are well-positioned to capitalize on these opportunities and drive further market expansion.

This data collection contains de-identified clinical health service utilisation data from Bendigo Health and the General Practitioners Practices associated with the Loddon Mallee Murray Medicare Local. The collection also includes associated population health data from the ABS, AIHW and the Municipal Health Plans. Health researchers have a major interest in how clinical data can be used to monitor population health and health care in rural and regional Australia through analysing a broad range of factors shown to impact the health of different populations. The Population Health data collection provides students, managers, clinicians and researchers the opportunity to use clinical data in the study of population health, including the analysis of health risk factors, disease trends and health care utilisation and outcomes.Temporal range (data time period):2004 to 2014Spatial coverage:Bendigo Latitude -36.758711200000010000, Bendigo Longitude 144.283745899999990000

Healthcare Provider Population Health Management Software Market Outlook

As of 2023, the global market size for Healthcare Provider Population Health Management (PHM) Software was valued at approximately USD 12 billion and is projected to grow at a compound annual growth rate (CAGR) of 15% over the forecast period, reaching nearly USD 35 billion by 2032. This significant growth is driven by several factors, including the increasing prevalence of chronic diseases, the rising demand for cost-effective healthcare solutions, and the growing adoption of healthcare IT systems.

One of the primary growth factors for the Healthcare Provider Population Health Management Software market is the increasing burden of chronic diseases worldwide. Chronic diseases such as diabetes, heart disease, and cancer require continuous monitoring and management, which can be efficiently handled through PHM software. These tools allow healthcare providers to analyze large volumes of patient data to identify trends and make informed decisions, ultimately improving patient outcomes and reducing healthcare costs. Furthermore, the aging global population contributes to a higher prevalence of chronic conditions, further driving the demand for effective PHM solutions.

Another significant growth driver is the rising demand for cost-effective healthcare solutions. With healthcare costs continuing to rise, both providers and payers are looking for ways to deliver high-quality care more efficiently. PHM software enables healthcare providers to identify high-risk patient populations and proactively manage their care, thereby reducing hospital readmissions and emergency department visits. By focusing on prevention and early intervention, these tools help lower overall healthcare costs while improving patient health outcomes. Additionally, the shift towards value-based care models incentivizes healthcare organizations to invest in PHM solutions to meet performance metrics and achieve financial incentives.

The growing adoption of healthcare IT systems is also a crucial factor contributing to the market's growth. As healthcare organizations increasingly recognize the benefits of digital transformation, the implementation of electronic health records (EHRs), telehealth services, and other health IT solutions has become more widespread. PHM software integrates seamlessly with these systems, enabling healthcare providers to leverage data from various sources to create comprehensive patient profiles and deliver personalized care. The interoperability of PHM software with existing healthcare IT infrastructure enhances its appeal and drives market growth.

From a regional perspective, North America is expected to hold the largest market share for Healthcare Provider Population Health Management Software, driven by advanced healthcare infrastructure, high adoption of digital health technologies, and supportive government initiatives. The Asia Pacific region is anticipated to witness the highest growth rate during the forecast period, fueled by increasing healthcare investments, improving healthcare infrastructure, and rising awareness about the benefits of PHM solutions. Europe and Latin America are also expected to experience significant growth, albeit at a slightly slower pace, due to ongoing healthcare reforms and the increasing focus on population health management.

Component Analysis

The Healthcare Provider Population Health Management Software market can be segmented into Software and Services based on components. The software segment is expected to dominate the market, driven by the increasing need for advanced analytics, data integration, and interoperability solutions. PHM software provides healthcare providers with tools to analyze large datasets, identify trends, and make data-driven decisions to improve patient outcomes. The software segment includes various solutions such as care management software, patient engagement tools, and analytics platforms, all of which play a crucial role in population health management.

Within the software segment, care management software is particularly important as it enables healthcare providers to coordinate care for patients with chronic conditions or complex medical needs. These tools help identify high-risk patients, develop personalized care plans, and monitor patient progress. By facilitating better care coordination, care management software can reduce hospital readmissions and emergency department visits, ultimately improving patient outcomes and reducing healthcare costs. The growing emphasis on value-based care models further drives the demand for care m

AI-driven Population Health Management Market Outlook

According to our latest research, the AI-driven Population Health Management market size reached USD 16.2 billion in 2024 globally, reflecting a robust surge in adoption across the healthcare ecosystem. The market is poised to expand at a CAGR of 20.7% from 2025 to 2033, driven by the increasing integration of advanced analytics and artificial intelligence technologies in healthcare operations. By 2033, the global AI-driven Population Health Management market is forecasted to attain USD 102.6 billion, highlighting the sector’s dynamic growth trajectory. This expansion is underpinned by the rising need for data-driven healthcare solutions, surging chronic disease prevalence, and a shift toward value-based care models.

The primary growth factor fueling the AI-driven Population Health Management market is the escalating demand for effective healthcare delivery and resource optimization. Healthcare systems worldwide are grappling with mounting patient loads, increasing chronic disease burdens, and the imperative to control spiraling costs. AI-driven solutions enable providers to aggregate, analyze, and interpret vast datasets, facilitating risk stratification, predictive analytics, and personalized care interventions. As healthcare organizations strive to transition from reactive to proactive care, the adoption of AI-powered population health management platforms is accelerating, enabling them to identify at-risk populations, optimize care pathways, and improve patient outcomes.

Another significant driver is the proliferation of digital health infrastructure and the widespread adoption of electronic health records (EHRs). The integration of AI with EHRs and other health IT systems allows for seamless data interoperability, enabling comprehensive patient profiling and real-time clinical decision support. Governments and regulatory bodies are increasingly mandating interoperability standards and incentivizing the adoption of digital health solutions, further propelling market growth. Additionally, the COVID-19 pandemic has catalyzed the digital transformation of healthcare, underscoring the need for remote monitoring, telehealth, and population-level surveillance, all of which are enhanced by AI-driven population health management tools.

Moreover, the growing focus on value-based care and outcome-driven reimbursement models is encouraging healthcare stakeholders to invest in advanced analytics and AI technologies. Payers, providers, and government bodies are leveraging AI-driven population health management systems to monitor quality metrics, reduce hospital readmissions, and manage high-risk cohorts more effectively. The ability to harness predictive modeling, automate administrative tasks, and generate actionable insights is transforming care delivery, fostering collaboration among multidisciplinary teams, and ultimately driving better health outcomes at reduced costs.

Regionally, North America dominates the AI-driven Population Health Management market, accounting for the largest revenue share in 2024, followed by Europe and Asia Pacific. The United States, in particular, is at the forefront due to its advanced healthcare IT infrastructure, strong regulatory support, and high adoption rates among providers and payers. Europe is witnessing steady growth, driven by government initiatives to digitize healthcare and improve patient outcomes. Meanwhile, Asia Pacific is emerging as a lucrative market, with countries like China, India, and Japan investing heavily in healthcare modernization and AI integration. The Middle East & Africa and Latin America are also experiencing gradual uptake, albeit at a slower pace, as digital health ecosystems mature.

Component Analysis

The AI-driven Population Health Management market by component is primarily segmented into software and services. Software solutions constitute the backbo

According to Cognitive Market Research, the global Population Health Management market size is USD 31.5 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 14.1% from 2024 to 2031. Market Dynamics of Population Health Management Market

Key Drivers for Population Health Management Market

Increased emphasis on value-based medicine - Healthcare is being redefined by value-based medicine, which captures results-oriented data and renders it functional. BI assists healthcare organizations in identifying the data they require and in the subsequent analysis, evaluation, and utilization of this data to gain a competitive advantage and comprehend the overall costs versus benefits. It also allows for the examination of each purchase from the perspectives of value, utility, and outcomes, as it promotes transparency in all processes. Moreover, the current pharmaceutical model is unsustainable on a global scale, prompting governments, insurance companies, and medical professionals to pursue novel opportunities to reduce costs. Furthermore, healthcare organizations will be increasingly compelled to employ these new methodologies in order to meet the growing demand for quality patient care and the increasing volume and availability of healthcare data.
Support and government mandates for healthcare information technology solutions is anticipated to drive the Population Health Management market's expansion in the years ahead.

Key Restraints for Population Health Management Market

Lack of qualified analysts and data management capabilities poses a serious threat to the Population Health Management industry.
The market also faces significant difficulties related to increasing risks of data breaches.

Introduction of the Population Health Management Market

In the field of healthcare, population health management (PHM) refers to a proactive strategy that focuses on developing the health outcomes of a specific group of an individual population. Analyzing data to determine health needs, putting in place treatments to meet those needs, and determining how successful those interventions were are all components of this process. The goal is to improve overall well-being while also lowering the costs of healthcare by integrating healthcare services, neighborhood assets, and social determinants of health. With the help of technological advancements like electronic medical records (EHRs), telehealth platforms, mobile devices, and advanced data analytics tools, the infrastructure and capabilities required for successful PHM deployment may be achieved. The gathering, integration, and analysis of massive volumes of healthcare data may be accomplished with the help of these technologies, which in turn makes risk classification, patient segmentation, and tailored therapies much easier to do.

Healthcare Provider Population Health Management Platforms Market Outlook

According to our latest research, the global Healthcare Provider Population Health Management Platforms market size reached USD 19.8 billion in 2024, and it is projected to grow at a CAGR of 13.2% during the forecast period. By 2033, the market is anticipated to attain a value of approximately USD 56.1 billion. The robust growth in this market is primarily driven by the increasing demand for integrated healthcare solutions, the rising prevalence of chronic diseases, and the ongoing digital transformation within healthcare systems worldwide.

One of the primary growth factors propelling the Healthcare Provider Population Health Management Platforms market is the escalating need for value-based care models. As healthcare systems transition from fee-for-service to outcome-based reimbursement, providers are seeking advanced solutions that enable comprehensive care coordination, risk stratification, and proactive intervention. Population health management platforms empower healthcare organizations to aggregate and analyze patient data from diverse sources, facilitating early identification of at-risk populations and enabling targeted care plans. This shift is further supported by evolving regulatory mandates and government incentives, particularly in developed economies, which encourage the adoption of digital health technologies and data-driven decision-making frameworks.

The growing prevalence of chronic diseases, such as diabetes, cardiovascular disorders, and respiratory illnesses, is another significant driver for the adoption of population health management platforms. With chronic disease management accounting for a substantial portion of healthcare expenditures globally, providers are increasingly leveraging these platforms to monitor patient health status, track adherence to treatment protocols, and deliver personalized interventions. The integration of analytics and reporting functionalities within these platforms aids in identifying care gaps, optimizing resource allocation, and ultimately improving patient outcomes. Furthermore, the ongoing COVID-19 pandemic has accentuated the need for robust population health management, as healthcare systems strive to manage large patient populations, monitor outbreaks, and ensure continuity of care amidst resource constraints.

Technological advancements and the proliferation of cloud-based solutions are also fueling market expansion. Cloud-based population health management platforms offer scalability, interoperability, and real-time data access, which are critical for large healthcare organizations and networks. These platforms facilitate seamless data integration from electronic health records (EHRs), medical devices, and other digital sources, enabling providers to gain a holistic view of patient health. The adoption of artificial intelligence (AI) and machine learning algorithms further enhances the predictive analytics capabilities of these platforms, supporting more informed clinical and operational decisions. As healthcare organizations continue to prioritize digital transformation and invest in next-generation IT infrastructure, the demand for advanced population health management solutions is expected to surge.

Regionally, North America currently dominates the global Healthcare Provider Population Health Management Platforms market, accounting for the largest revenue share in 2024. This leadership position is attributed to the presence of a well-established healthcare IT ecosystem, high adoption rates of electronic health records, and supportive regulatory frameworks. Europe follows closely, driven by increasing government investments in digital health, while the Asia Pacific region is emerging as a lucrative market due to rapid healthcare digitization, expanding insurance coverage, and rising awareness about population health management. Latin America and the Middle East & Africa are also witnessing gradual adoption, supported by improving healthcare infrastructure and growing focus on preventive care.

In this rapidly evolving landscape, Wellpoint System Monitoring Platforms are emerging as a critical component for healthcare providers aiming to optimize their population health management strategies. These platforms offer robust monitoring capabilities that ensure the seamless operation of health management syste

This dataset contains model-based census tract estimates. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. The dataset includes estimates for 36 measures: 13 for health outcomes, 9 for preventive services use, 4 for chronic disease-related health risk behaviors, 7 for disabilities, and 3 for health status. These estimates can be used to identify emerging health problems and to help develop and carry out effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2021 or 2020 data, Census Bureau 2010 population data, and American Community Survey 2015–2019 estimates. The 2023 release uses 2021 BRFSS data for 29 measures and 2020 BRFSS data for seven measures (all teeth lost, dental visits, mammograms, cervical cancer screening, colorectal cancer screening, core preventive services among older adults, and sleeping less than 7 hours) that the survey collects data on every other year. More information about the methodology can be found at www.cdc.gov/places.

Overview

New York, NY – August 29, 2025: The global Population Health Management (PHM) market size was valued at USD 31.7 billion in 2023 and is projected to reach USD 118.6 billion by 2033, growing at a CAGR of 14.1% from 2024 to 2033. This strong growth is driven by the global shift from fee-for-service to value-based care. Healthcare systems are adopting PHM to improve patient outcomes, enhance care coordination, and reduce costs. Favorable government policies, technological innovation, and preventive care strategies are further accelerating adoption across both developed and emerging markets.

One of the most significant growth factors in the PHM sector is the rising chronic disease burden. Conditions such as diabetes, cardiovascular disorders, respiratory illnesses, and obesity demand long-term care and continuous monitoring. PHM solutions enable providers to stratify patient populations, engage patients in real time, and coordinate care more effectively. This helps reduce hospital readmissions and optimize treatment plans. With chronic diseases increasing worldwide, healthcare systems are under pressure to adopt structured PHM programs to manage populations more efficiently.

The transition to value-based care is another critical driver fueling PHM adoption. Governments and healthcare payers are shifting reimbursement models away from volume-based to outcome-driven strategies. PHM enables providers to track health metrics, identify high-risk populations, and adopt preventive care approaches. Incentive programs, penalties for poor outcomes, and regulatory guidelines are strengthening this shift. As a result, providers implementing PHM can achieve better compliance, reduce costs, and improve patient satisfaction. This transition is creating long-term opportunities for PHM vendors and solution providers globally.

Advancements in healthcare IT are also playing a pivotal role in PHM growth. The rapid adoption of electronic health records, data integration platforms, and predictive analytics tools is enabling smarter decision-making. Technologies such as artificial intelligence and machine learning help in early disease detection and personalized treatment planning. Additionally, telehealth platforms, wearable devices, and remote patient monitoring systems are extending care beyond hospitals. These innovations not only reduce hospital visits but also enhance patient engagement. The digital transformation of healthcare is making PHM an indispensable solution worldwide.

Rising healthcare costs and the urgent need for efficiency continue to drive PHM expansion. Providers and payers face growing pressure to deliver high-quality care while controlling expenses. PHM supports this by reducing unnecessary procedures, optimizing resources, and focusing on preventive care. At the same time, stronger collaborations among providers, insurers, pharmaceutical companies, and technology vendors are creating integrated PHM ecosystems. These partnerships improve data sharing, strengthen care delivery, and drive outcome-based models. Together, these factors position PHM as a cornerstone of sustainable healthcare growth in the coming decade.

These documents were produced through a collaboration between GLA, PHE London and Association of Directors of Public Health London. The wider impacts slide set pulls together a series of rapid evidence reviews and consultation conversations with key London stakeholders. The evidence reviews and stakeholder consultations were undertaken to explore the wider impacts of the pandemic on Londoners and the considerations for recovery within the context of improving population health outcomes. The information presented in the wider impact slides represents the emerging evidence available at the time of conducting the work (May-August 2020). The resource is not routinely updated and therefore further evidence reviews to identify more recent research and evidence should be considered alongside this resource. It is useful to look at this in conjunction with the ‘People and places in London most vulnerable to COVID-19 and its social and economic consequences’ report commissioned as part of this work programme and produced by the New Policy Institute. Additional work was also undertaken on the housing issues and priorities during COVID. A short report and examples of good practice are provided here. These reports are intended as a resource to support stakeholders in planning during the transition and recovery phase. However, they are also relevant to policy and decision-making as part of the ongoing response. The GLA have also commissioned the University of Manchester to undertake a rapid evidence review on inequalities in relation to COVID-19 and their effects on London.

This formatted dataset (AnalysisDatabaseGBD) originates from raw data files from the Institute of Health Metrics and Evaluation (IHME) Global Burden of Disease Study (GBD2017) affiliated with the University of Washington. We are volunteer collaborators with IHME and not employed by IHME or the University of Washington.

The population weighted GBD2017 data are on male and female cohorts ages 15-69 years including noncommunicable diseases (NCDs), body mass index (BMI), cardiovascular disease (CVD), and other health outcomes and associated dietary, metabolic, and other risk factors. The purpose of creating this population-weighted, formatted database is to explore the univariate and multiple regression correlations of health outcomes with risk factors. Our research hypothesis is that we can successfully model NCDs, BMI, CVD, and other health outcomes with their attributable risks.

These Global Burden of disease data relate to the preprint: The EAT-Lancet Commission Planetary Health Diet compared with Institute of Health Metrics and Evaluation Global Burden of Disease Ecological Data Analysis. The data include the following: 1. Analysis database of population weighted GBD2017 data that includes over 40 health risk factors, noncommunicable disease deaths/100k/year of male and female cohorts ages 15-69 years from 195 countries (the primary outcome variable that includes over 100 types of noncommunicable diseases) and over 20 individual noncommunicable diseases (e.g., ischemic heart disease, colon cancer, etc). 2. A text file to import the analysis database into SAS 3. The SAS code to format the analysis database to be used for analytics 4. SAS code for deriving Tables 1, 2, 3 and Supplementary Tables 5 and 6 5. SAS code for deriving the multiple regression formula in Table 4. 6. SAS code for deriving the multiple regression formula in Table 5 7. SAS code for deriving the multiple regression formula in Supplementary Table 7
8. SAS code for deriving the multiple regression formula in Supplementary Table 8 9. The Excel files that accompanied the above SAS code to produce the tables

For questions, please email davidkcundiff@gmail.com. Thanks.

Please note: This is a Synthetic data file, also known as a Dummy file - it is not real data. This synthetic file should not be used for purposes other than to develop an test computer programs that are to be submitted by remote access. Each record in the synthetic file matches the format and content parameters of the real Statistics Canada Master File with which it is associated, but the data themselves have been 'made up'. They do NOT represent responses from real individuals and should NOT be used for actual analysis. These data are provided solely for the purpose of testing statistical package 'code' (e.g. SPSS syntax, SAS programs, etc.) in preperation for analysis using the associated Master File in a Research Data Centre, by Remote Job Submission, or by some other means of secure access. If statistical analysis 'code' works with the synthetic data, researchers can have some confidence that the same code will run successfully against the Master File data in the Resource Data Centres. In the fall of 1991, the National Health Information Council recommended that an ongoing national survey of population health be conducted. This recommendation was based on consideration of the economic and fiscal pressures on the health care systems and the requirement for information with which to improve the health status of the population in Canada. Commencing in April 1992, Statistics Canada received funding for development of a National Population Health Survey (NPHS). The NPHS collects information related to the health of the Canadian population and related socio-demographic information to: aid in the development of public policy by providing measures of the level, trend and distribution of the health status of the population, provide data for analytic studies that will assist in understanding the determinants of health, and collect data on the economic, social, demographic, occupational and environmental correlates of health. In addition the NPHS seeks to increase the understanding of the relationship between health status and health care utilization, including alternative as well as traditional services, and also to allow the possibility of linking survey data to routinely collected administrative data such as vital statistics, environmental measures, community variables, and health services utilization. The NPHS collects information related to the health of the Canadian population and related socio-demographic information. It is composed of three components: the Households, the Health Institutions, and the North components. The Household component started in 1994/1995 and is conducted every two years. The first three cycles (1994/1995, 1996/1997, 1997/1998) were both cross-sectional and longitudinal. The NPHS longitudinal sample includes 17,276 persons from all ages in 1994/1995 and these same persons are to be interviewed every two years. Beginning in Cycle 4 (2000/2001) the survey became strictly longitudinal (collecting health information from the same individuals each cycle). The cross-sectional and longitudinal documentation of the Household component is presented separately as well as the documentation for the Health Institutions and North components. The cross-sectional component of the Population Health Survey Program has been taken over by the Canadian Community Health Survey (CCHS). With the introduction of the Canadian Community Health Survey (CCHS), there were many changes to the 2000-2001 National Population Health Survey - Household questionnaire. Since NPHS is strictly a longitudinal survey, some content was migrated to the CCHS (such as the two-week disability section and certain questions on place where health care was provided) or was dropped (e.g. certain chronic conditions), while the order of the questionnaire changed. As only the longitudinal respondent is now surveyed, it was no longer necessary to distinguish between the General questionnaire and the Health component. Health Canada, Public Health Agency of Canada and provincial ministries of health use NPHS longitudinal data to plan, implement and evaluate programs and health policies to improve health and the efficiency of health services. Non-profit health organizations and researchers in the academic fields use the information to move research ahead and to improve health.