The Evolving Role of Artificial Intelligence in Population Health

Artificial intelligence, Healthcare, Robots in Healthcare, Healthcare Technology

By Stephen Zander, Chief Analytics Officer at Cedar Gate Technologies 

Our health system is becoming increasingly strained by expanding complexities, threatening mandates, and unsustainable costs. These looming challenges jeopardize our system’s sustainability and circumstances necessitate an innovative and sophisticated response. 

Amid the health industry’s titanic blitz of impending difficulties, population health management is emerging as a valuable instrument delivering needed focus, streamlined logistics, and ultimately helping providers improve patient outcomes. As an interdisciplinary and customizable approach that connects health practices to policy implementation and targeted adjustments, population health is the concept of having a holistic view of understanding the conditions and factors that influence the health of distinct demographics over lifetimes. This also includes the support of the transformation from fee for service model to value-based care. 

Today, advanced value-based care platforms equipped with innovative technology can leverage interpretable artificial intelligence (AI) to help implement population health strategies and support provider productivity, advance patient outcomes, and identify those most at risk. 

The role of artificial intelligence in population health management 

AI represents a set of technologies that consist of automated systems able to perform tasks including visual perceptions, augmenting diagnostics, predictive analytics, and seamlessly processing large amounts of data. 

Interpretable AI has the potential to profoundly impact the public’s health. Applications can assist providers, health system managers, policy-makers, and public health practitioners in making decisions with increased accuracy and effective outcomes. Applicable and effective opportunities exist where AI can provide population health solutions.

Patient identification and risk stratification: Advanced technologies can process external data from various communities, chronicling social determinants of health, along with other public data that offers a deep and quick view of higher-risk patients. AI is used for predictive analysis to identify high-risk patients from EMR data that includes a combination of length of stay, chronic conditions, and previous hospitalizations.

Identifying gaps in care: AI-supplied data provides doctors with progress updates, detailed histories, and other information related to the patient and their demographic trends through predictive analytics. Interpretable AI has the potential to match a physician’s observations with community-related data that provides targeted insight into surrounding circumstances, helping identify missing gaps in care for individuals and communities. 

Community engagement and care coordination: Patient engagement and treatment is the focal point of the medical experience. Interpretable AI allows for a personalized and data-driven approach to patient engagement. Interpretable AI coordinates outreach to targeted patients in various communities and populations, either actively during their hospital encounters or proactively before events occur, with the goal of proper care coordination to keep patients healthy and reduce the length and frequency of hospitalizations. 

By identifying emerging or high-risk patients grouped by specific clinical conditions, co-morbidities, or driven by predictive risk models, patients with the greatest need can be targeted earlier with effective interventions. The result translates into fewer, less severe interventions and reduced hospitalization. 

Workforce optimization: Interpretable AI can help providers expedite responses to interventions. Physicians can spend less time capturing information from unstructured reports, and less time sitting in front of a screen to get a complete picture of the patient. A great benefit available to the health care industry receives from adopting artificial intelligence is that it removes unnecessary, often manually-related workloads. This not only saves time but also conserves resources, often wasted on excessive processes. AI maximizes the time between doctor and patients and alerts the provider to early intervention options.

Interpretable artificial intelligence elevates population health management
Interpretable AI connects and processes vast amounts of information across wide demographics and allows providers to offer quality care with seamless ease and convenience. These innovative solutions improve the approach to population health and deliver a frictionless, integrated experience for both the patient and provider. 

Interpretable AI is positioned to evolve and play an increased role in supporting population health care operations. Its potential is boundless to help initiate a new system centered on improved efficiencies, reduced costs, and a structure that engages, empowers, and educates patients.