Some of the most important problems in the healthcare industry are connected to the aging population and managing chronic illnesses. Others include rising healthcare costs and health inequity of underserved groups.
There is a way to address all of these problems and that is population health management. This article will explain the key concepts and strategies for using this powerful technique.
Understanding population health
The healthcare system needs to evolve and be more cohesive and proactive in addressing changing needs. Integrated care systems (ICSs) prioritize prevention and seamless care with the integration of health with social care. At the heart of this transformation are the Population Health Management platforms (or PHM). [1]
To understand PHM we have to first define population health. It is a term that has to be distinguished from the term public health.
While public health departments focus on improving the health of entire patient populations, population health is centered around specific groups of people (e.g., patients with diabetes). This means that population health narrows the specific group. Programs driven by the population health system would be, for example, care plans for diabetics that reduce their hospital readmissions.
All in all, population health management is more targeted. It is a method that can be used by healthcare providers, insurers, and others. [2]
The importance of data in population health management
Data forms the backbone of PHM. It plays a crucial role in advancing intervention and research efforts to accelerate disease prevention in population health. It has proven effective in enhancing precision within the population health management process. This is particularly visible in areas such as population segmentation, risk stratification, and tailoring interventions for individuals and specific subpopulations.
Data can be obtained from different places: medical records, referrals, disease registries, health surveys, or questionnaires. [3] Then, this data should be transformed into the right format and analyzed. Also, some PHM systems have a Care Management that generates work lists with patient data for contact.
Why is gathering this data important? First, more data leads to using a patient-centered approach and making evidence-based decisions. Integrating data from different resources such as electronic health records (EHR) and wearable devices, allows personalized patient’s care.
Second, data is needed to identify the population’s needs. It enables dividing it into segments and identifying high-risk groups. Moreover, data can address Social Determinants of Health (SDOH). These are non-medical factors that influence health (housing, employment, etc).
Robust data analytics can let population health management programs make a meaningful change as it improves both the individual and the community life. [4]
Key strategies for population health management
Population health management relies on a strategic approach. Here are some of its approaches.
Data Transformation
To effectively manage population health status, healthcare organizations must integrate diverse internal and external data sources. This enables a clearer view of the population’s health journey. Moreover, the transparency helps in better managing networks, assessing risks, and capitalizing on opportunities to improve care delivery.
Research from the Alberta Health Services initiative revealed that only 8% of the data needed for precision medicine and population health resides in EHRs. This underscores the importance of incorporating a wide range of data types – clinical, behavioral, social, etc. These data sources can guide the delivery of the right services at the right time and place.
Analytic Transformation
Once data integration is achieved, organizations need robust analytic frameworks to support key objectives. For instance, reducing preterm birth rates requires analyzing prevalence patterns and identifying underserved areas.
Then, they have to refine population definitions to target individuals who can benefit from specific interventions. For example, accurately identifying children with asthma requires going beyond diagnostic codes to include symptoms and pharmacy data.
Next, population health managers should identify variations in care to pinpoint areas for improvement. After that, they must assess the total cost of care with comprehensive cost factors. During this process and after, data must be continuously analyzed to ensure initiatives are achieving desired clinical outcomes.
Payment Transformation
Every population health manager may benefit from the transition from fee-for-service payment models to value-based care models. This shift ensures appropriate reimbursement for services under risk-based contracts.
Without a payment model that aligns with value-based care, efforts to improve individual and population health cannot succeed. Understanding the total cost of care and balancing risks under these contracts are essential for effective payment transformation.
Care Transformation
Care transformation focuses on optimizing care delivery processes and outcomes. For example, Cradle Cincinnati, a local initiative to improve infant health, tackled preterm birth rates by addressing modifiable behaviors like smoking and inadequate birth spacing.
The initiative even broadened its approach to educate all women in the community about healthy pregnancy practices. This strategy not only improved outcomes but also demonstrated significant cost savings.
Other opportunities for care transformation include enhancing primary care infrastructure, ensuring care is delivered in the most appropriate settings, and improving engagement with patients and caregivers to promote better health outcomes. [5]
Leveraging technology for population health solutions
Technological advancements are needed in every aspect of digital health, but here, in improving population health, their role is extremely important.
For example, big data analytics is the ability to analyze huge amounts of data. Imagine how hard and even impossible it will be to make predictions and identify patterns without this powerful tool.
Electronic health records are a must when talking about innovations in the health care system. They consist of the most important medical information about the person. This means that they are the first line of knowledge to obtain when making an analysis.
Mobile health applications and their implementation in wearable devices are a trend nowadays. Their main goal is to collect data at every moment. However, more important is the emotional support and control over one’s own health that they give the users. They can be used to promote healthier lifestyles, medical adherence, and many others. [6]
Community engagement and health promotion
Community engagement (CE) plays a pivotal role in health promotion as it fosters collaboration between communities and health organizations. CE emphasizes the active role of community members in decision-making processes.
By empowering individuals and strengthening social networks, CE enhances a sense of ownership over health outcomes and builds trust and resilience within the community. This approach has been shown to improve efficiency, and access to resources and create supportive environments that encourage healthier behaviors from within the community. [7]
Challenges in implementing population health strategies
Community and patient engagement is a powerful tool, but also an uncertain one. Although CE has demonstrated significant improvements in perceived health and social cohesion, its direct impact on physical health outcomes remains different in the specific circumstances. This underscores the importance of focusing on creating sustainable, context-sensitive health promotion strategies. [7]
Another challenge in PHM is risk stratification. It requires a familiarity with data science and special analytics tools to identify community health trends and outline healthcare improvement points. Integrated population health management platforms can provide analytics and reports that contain necessary insights.
The shift to a new workflow that contains PHM may also be difficult. The staff should be encouraged to accept and work with new technology. Also, providers need to ensure training and guidance through this process.
These are only a small part of the challenges along the way of this innovation in the medical field. However, every difficulty can be overcome if there is enough support from the developing team. [8]
Value-based care and population health management
Population health and value-based care are interrelated approaches toward healthcare. They aim to improve health outcomes and create a more efficient and sustainable healthcare system by prioritizing patient outcomes over service volume. They are also both related in terms of preventive care and health promotion, as well as addressing social determinants of health.
As already indicated, population health takes a broader perspective as its core is to analyze data and design targeted interventions for specific groups or communities. In contrast, value-based care operates within healthcare delivery systems and aligns financial incentives with quality and efficiency to promote high-quality care at lower costs. Together, they make healthcare models more proactive and outcome-driven.
The synergy between population health and value-based care lies in their collaboration among stakeholders. Population health data analytics directly supports the goals of value-based care by providing actionable insights for personalized interventions. Additionally, value-based care emphasizes care coordination across providers.
Financial incentives in value-based care models reward providers for meeting quality metrics, while population health initiatives encourage long-term investments in community health and prevention. By integrating these frameworks, healthcare systems can achieve improved health outcomes and greater equity. [9]
Addressing health disparities
Addressing health disparities is a fundamental aspect of population health management. It aims to improve health equity by identifying gaps in healthcare access.
PHM’s approaches, such as population segmentation and risk stratification, are used exactly for this reason. They pinpoint disparities linked to factors like socioeconomic status, race, ethnicity, geography, and social determinants of health.
PHM strategies prioritize targeted interventions in underserved groups. Ultimately, outlining health disparities within PHM fosters a more equitable healthcare system. [3]
Regulatory considerations
Compliance challenges of PHM arise from the vast amount of data that is managed by numerous stakeholders in the care continuum. This means that strong adherence to federal and state laws, including Health Insurance Portability and Accountability Act (HIPAA) and the Health Information Technology for Economic and Clinical Health (HITECH) Act, must be ensured.
This is essential but complex, as it requires interdisciplinary efforts from compliance officers, legal teams, and IT experts.
Organizations must navigate regulations related to data privacy, antitrust laws, and payer requirements. Also, they should address potential pitfalls – breaches, fraud, and discrimination. To stay compliant, organizations must implement robust compliance programs and educate stakeholders on regulatory requirements.
Technological adoption and interoperability are also critical to PHM’s success. Effective Health Information Technology (HIT) systems are needed to process patient data while protecting its security and privacy. Moreover, compliance officers play a pivotal role in ensuring data integrity. [10]
Discover how we can help outsource Healthcare projects efficiently Speak to an expert today, and see how our on-demand IT talent and augmented teams can efficiently deliver value at every step of your roadmap.
Future trends
The future of population health management tools guarantees to be imposed in healthcare systems all over the world. Advances such as artificial intelligence, machine learning, and predictive analytics will enable healthcare professionals to deliver more proactive and preventive care.
Additionally, the integration of social determinants of health (SDOH) into PHM strategies is expected to expand. Taking into account factors like housing, patient education, income, and access to healthy food will help bridge health disparities and promote equity among groups. For this purpose, multi-disciplinary teams will form as a force to implement PHM in the future.
In conclusion, Population Health Management is transforming healthcare by focusing on prevention, personalized care, and addressing the broader factors that influence health outcomes. It holds the potential to create healthier communities while making better quality care that is more efficient and equitable.
Sources
[1] https://www.england.nhs.uk/integratedcare/phm/
[2]https://www.snhu.edu/about-us/newsroom/health/what-is-population-health-management
[3]https://iris.who.int/bitstream/handle/10665/368805/WHO-EURO-2023-7497-47264-69316-eng.pdf?sequence=1
[5]https://www.healthcatalyst.com/learn/insights/4-population-health-strategies-drive-improvement
[7]https://onlinelibrary.wiley.com/doi/10.1155/2024/2448483
[9]https://www.elationhealth.com/resources/blogs/value-based-care-and-population-health-management
