Enhancing Healthcare Equity Through AI-driven Population Health Management 

Updated on April 8, 2024

Technology plays a critical role in enabling healthcare providers to administer more equitable care to diverse patient populations. Advancements in Artificial Intelligence (AI)-powered solutions are currently essential in diminishing disparities in health outcomes and fostering healthcare equity. One of the most promising advancements in the last decade is the integration of AI into population health management (PHM). This integration can revolutionize healthcare delivery, particularly in enhancing risk stratification and early intervention. By leveraging AI-driven systems thoughtfully, healthcare providers today are working toward ensuring that everyone, regardless of their background or circumstances, can lead a healthy life. The objective of Sustainable Development Goal 3 (SDG 3), which focuses on promoting good health and well-being for all at every stage of life, is to ensure healthy lives for all individuals. Implementing PHM practices can help achieve SDG-3 faster.

Closing gaps in healthcare with AI-driven solutions

At the heart of AI-driven PHM lies the ability to analyze vast datasets. Through sophisticated algorithms, AI can identify high-risk populations and pinpoint areas with higher rates of chronic diseases or lower access to preventive care. This insight empowers healthcare providers to target interventions and allocate resources more effectively, thereby closing gaps in care and promoting equity across communities. 

Individuals residing in rural areas globally often face limited access to high-quality healthcare services. With AI-based solutions, healthcare professionals can improve their efficiency by automating repetitive administrative tasks; this leaves them more time to see more patients. Also, embedded AI technology can decrease costs associated with various testing and screening methods. This not only expands access to healthcare but also narrows the disparities stemming from income levels and geographical location, particularly between rural and urban areas. AI-powered technologies, when integrated into phones, tablets, and other devices, are instrumental in overcoming challenges related to the scarcity of specialists and the affordability of equipment for tasks such as image analysis and decision support.

In 2023, the global population health management market was estimated to be worth USD 31 billion, with projections indicating it will exceed USD 157.87 billion by 2033. According to the Market Research Report, the software segment within the population health management market is poised to exhibit the most significant expansion. The surge can be attributed to its capacity to diminish readmissions, amplify patient engagement, and offer flexibility in customization options.

Keeping stakeholders at the core of AI healthcare

While AI-driven PHM solutions hold immense promise for revolutionizing healthcare, significant hurdles exist in their implementation. Data bias remains a significant concern, as AI systems are only as good as the data that is used to train them. Ensuring that data represents diverse populations is crucial to avoiding exacerbating existing health disparities. Also, accessibility issues, such as limited Internet connectivity in certain areas, can hinder the reach of AI-powered healthcare solutions.

To address these challenges and maximize the potential of AI in PHM, several strategies can be employed. Inclusive development practices involve diverse stakeholders in the design and implementation of AI-powered healthcare solutions, ensuring that the needs of all populations are considered. Transparency and explainability of AI algorithms are also essential, allowing healthcare providers to understand and trust the recommendations provided.

Reshaping AI-driven PHM with GenAI

An innovative approach to AI-driven PHM is the use of GenAI-powered solutions that identify social determinants of health (SDoH) to better predict patients’ non-clinical needs and healthcare costs. By leveraging advanced algorithms, it’s possible to analyze electronic health records (EHR) data to accurately identify SDoH, which often hides within unstructured clinical notes, such as unemployment, early life trauma, loneliness, food insecurity, and income disparities, all of which can significantly impact an individual’s health and well-being. 

Frequently, these factors are not systematically recorded as distinct data fields within healthcare systems; instead, they are often buried within patient notes. This is precisely where AI-driven solutions are making a substantial impact.

GenAI-driven solutions offer a more comprehensive and precise approach, they extract key information from EHRs of patient data, enabling healthcare providers to make more informed and timely care recommendations. This innovative methodology improves patient outcomes and enhances scalability, compliance, and accuracy.

With GenAI, PHM solutions are enhanced, empowering healthcare professionals to provide personalized interventions tailored to individual patient needs. A GenAI-powered PHM can help predict risk factors and identify high-risk patients. These solutions facilitate early interventions, reducing emergency department visits, readmissions, and extended hospital stays. Overall, it helps improve patient engagement and outcomes.

Technological advancements, such as large language models (LLMs), are rapidly maturing, leading to a streamlined ecosystem of vendors offering impactful AI-based solutions. This evolution can extend AI applications beyond administrative functions into direct patient care, potentially blurring the lines between human diagnosis and AI assistance.

The day is not far when AI transcends barriers to care, significantly mitigates health disparities, and enables personalized healthcare instantaneously. The aspiration is for these advancements to occur without reinforcing biases related to socio-economic status, while prioritizing support for individuals with chronic conditions and comorbidities. The vision is for AI-driven healthcare to be seamlessly integrated, empowering patients and healthcare providers alike to navigate and address health challenges more effectively.

Collaborating for quicker AI adoption

Despite the challenges of implementation and bias, there is optimism about the potential of AI to transform healthcare delivery and reduce health disparities. Collaborative efforts between tech companies, healthcare organizations, academic institutions, and government agencies are essential to advancing the development and appropriate use of AI in healthcare. Initiatives such as the Coalition For Health AI (CHAI), which brings together representatives from various sectors to drive innovation in healthcare AI, exemplify the importance of collaboration in this field.

The successful integration of AI into PHM presents a significant opportunity to improve healthcare equity across all demographics. Through continuous collaboration and innovation, AI can mitigate challenges and ultimately create a more equitable healthcare system for everyone. Healthcare leaders and policymakers are exploring this potential and where it can be as we speak. However, equity also needs to be prioritized throughout the AI development process, which will ensure a holistic approach and pave the way for a better and healthier future.

Ganesh Nathella
Ganesh Nathella
SVP & General Manager at Persistent Systems
Ganesh Nathella is Senior Vice President and General Manager, Global Lead for Persistent’s Healthcare and Life Sciences (HCLS) business. Under his leadership, Persistent’s HCLS business is transforming to become a new age digital transformation partner to accelerate health outcomes, quality of care, reduce the cost of care, and improve experiences by working with our clients, employees, partners, and influencers.
Ganesh brings over 25 years of global experience and 18 years of HCLS experience in driving strategy and growth in technology and services, from early-to-market stages to mature enterprises, building and scaling businesses for leading companies across multiple industry segments. He collaborates with clients in the HCLS industry and counsels them on strategy, growth, margin improvement, business building and large-scale transformation through the use of digital technologies, data, cloud, and modern infrastructure.
Prior to joining Persistent, Ganesh started the HCLS business at Mindtree and was responsible for the growth of business including managing the P&L, building industry-specific solutions, contextualizing technology solutions, and advancing Analyst and Advisor relationships, as well as leading sales, domain/industry, pre-sales and inside sales teams.