Population health management (PHM) has always been at the forefront of healthcare innovation, but recent trends have elevated its role and complexity. At its core, PHM focuses on analyzing populations to identify specific cohorts or patient groups needing closer management and often, improved health outcomes. For example, managing chronic diseases like diabetes or hypertension often involves stratifying patients into cohorts such as those managing their conditions well, those at risk, and those struggling. This stratification of patients enables care providers to tailor interventions for the best possible outcomes and adjust the intensity of patient management where it’s needed.
Today, PHM is evolving rapidly, with social drivers of health (SDOH) becoming increasingly important to its effectiveness. Factors like housing stability, transportation access, and food security are proving critical in understanding and addressing patient needs. Here are some of the emerging trends shaping PHM, and why its evolution is so critical for health and social care providers.
1. Interoperability and Integration of SDOH Data
One of the most significant shifts in PHM is the growing emphasis on interoperability and the inclusion of SDOH data in health systems. Organizations are increasingly striving to go beyond traditional electronic health record (EHR) data by integrating data that paints a fuller picture of a patient’s life. Federal initiatives, such as the Gravity Project, are setting standards for incorporating SDOH data, while platforms like Health Information Exchanges (HIEs) are working toward more inclusive data frameworks.
While some healthcare providers may struggle to standardize and effectively use SDOH data due to inconsistent data formats and a lack of widespread use and/or availability of data, those who successfully incorporate this data can profoundly improve care coordination for patients. For instance, understanding a patient’s housing status or food security can influence treatment plans, including consideration of storage, costs and other logistical factors associated with the use of medications.
2. The Role of Artificial Intelligence (AI) and Automation
AI is becoming an indispensable tool in PHM. From stratifying patient populations to predicting adverse health outcomes, AI can enable more precise and efficient resource allocation. Large hospital systems are already leveraging machine learning models to combine clinical data with SDOH insights, identifying high-risk patients and automating outreach and engagement efforts. These capabilities need to become more ubiquitous allowing care teams to apply effort appropriately where the demands on their time are at their limit.
For example, AI-driven tools can analyze population data to determine which patients need urgent interventions and which can be managed with low-touch methods like automated text or email reminders. This approach not only optimizes care delivery but also empowers care managers to focus on patients with the most critical needs. By integrating AI with SDOH data, healthcare systems can achieve a holistic view of patient risks and needs, driving better outcomes.
3. Enhancing Patient Engagement Through Technology
Patient engagement is another critical aspect of PHM, with technology playing a pivotal role in two main forms. Firstly, wearables, remote monitoring devices, and digital communication tools are being increasingly used to keep patients connected to their care plans. For instance, a blood pressure cuff or glucometer can provide real-time data, helping care teams monitor progress and compliance. However, integrating data from these devices into broader PHM analytics remains a challenge. Many systems treat this data as siloed information, limiting its utility in larger-scale analyses. Addressing these gaps will be crucial for improving care outcomes and enabling proactive interventions.
Secondly, patient-provider communications, while not a new consideration, is something that continues to evolve. Patients now have more access to emailing a healthcare professional, setting up virtual visits that may be in or out of their network, and can more easily find their records via portals. Using technology as a throttle for the types of communications assists both patients and providers in maintaining appropriate levels of interaction when established correctly, allowing for reallocation of time consumption in cases and in the case of patients reducing their time spent within the health system itself.
4. Community Resource Integration
While the integration of SDOH data into healthcare systems is improving, community resource platforms are still underutilized. Organizations providing platform access to resources, like Unite Us and Find Help aim to connect patients with a variety of services, but many care managers continue to rely on personal networks to refer patients due to the age-old approach “I know who to contact already and it’s just easier for me.” The gap between available resources and actual usage underscores the need for better training, integration across the myriad healthcare systems involved, and system design considerations that may make these tools more effective to their audience.
For instance, let’s consider organizations focused on food as medicine. These groups aim to address food insecurity as a critical SDOH by providing nutritious meals to patients with chronic conditions. By leveraging predictive analytics and interoperable data systems, such organizations can better identify populations at risk and demonstrate measurable outcomes to stakeholders like departments of healthcare services. By showing how improved nutrition impacts disease management, there can be an opportunity to secure additional funding and expand services. This kind of forward-thinking approach exemplifies how integrating SDOH data, AI, and community resources can transform patient care and outcomes.
The landscape of population health management is shifting rapidly, with SDOH taking center stage in the quest for better outcomes. By embracing trends like interoperability, AI, patient engagement, and community resource integration, healthcare systems can better address the complex needs of their populations. While challenges remain, the potential benefits—from improved patient outcomes to reduced healthcare costs—make this a critical area of focus for the future.
John Weir
John Weir, managing director at BluePath Health, has 18+ years of senior management experience in healthcare technology, specializing in EHR and population health software rollout, integration, and client services leadership. He has led large-scale clinical data integration projects, government-funded initiatives, and strategy development for private and public organizations. Weir managed an ONC CMMI grant to enhance care coordination and spearheaded CMS’s DOQ-IT EHR adoption program. He has held executive roles at Phytel, Allscripts, and Lumetra, driving business growth and client satisfaction.
