Key Takeaways
- An estimated 129 million people live with at least one chronic condition in the U.S.
- Care teams spend twice as much time on admin work than on patient treatment, challenging effective chronic care support.
- AI can help care teams scale chronic care management and cut down on routine tasks.
- [REPORT] Find out how leading health system innovators are making care more intelligent.
Around 129 million people live with at least one chronic condition in the U.S. Treating chronic conditions assumes 90% of the nation’s $4.5 trillion healthcare spending. Unlike some other care journeys that have a distinct beginning and an end, chronic conditions require ongoing support, monitoring, and treatment plans — all of which demand more time and effort from clinicians.
As more and more patients are predicted to develop chronic conditions over the next decade, how can providers ensure they’re prepared and supporting their workforce to meet chronic care challenges head-on?
Let’s dive into these challenges and how AI-backed platforms can help mitigate them.
What are some challenges to effective chronic care management?
Chronic care management is a service provided by healthcare professionals to help patients with chronic conditions like diabetes, cancer, obesity, heart disease, and chronic kidney disease to manage their health and improve their quality of life. Challenges to assisting individuals managing these conditions include:
- Patient disengagement and non-adherence: Patients might find it difficult to follow prescribed treatment regimens, including medication schedules, lifestyle changes, and regular follow-up appointments — especially outside of the clinical setting. Importantly, individuals might not fully understand their conditions or the importance of adhering to treatment plans in the first place, leading to poor self-management. As care teams spend two hours on administrative work for every hour of engagement with patients, standing by whenever someone has a question or concern during their care journey is near impossible.
- Healthcare system limitations: Patients in rural or underserved areas might have difficulty accessing healthcare services, specialists, and necessary resources for chronic condition management. Simultaneously, healthcare’s workforce is increasingly stretched thin, meaning less time and resources available to allocate toward effective chronic care management.
- Insufficient coordination among healthcare providers: Inadequate communication and coordination between primary care providers, specialists, and other healthcare professionals can lead to gaps in care, duplicated efforts, and inconsistent treatment. Transitions between different levels of care (e.g., hospital to home) can be poorly managed, leading to a lack of continuity in care and, subsequently, adverse outcomes.
- Technological and data barriers: Simply put, most of healthcare uses outdated technologies and systems for managing patient data, corresponding with individuals, and keeping tabs on care plans. Healthcare providers can be overwhelmed by the volume of patient data needed to effectively treat individuals, making it challenging to identify key information and insights necessary for effective care management.
- Socioeconomic and behavioral factors: SDOH such as poverty, lack of education, insufficient housing, and absent or subpar social support can significantly impact a patient's ability to manage their chronic conditions. Coexisting mental health conditions, such as depression and anxiety, can also complicate chronic care management and require additional resources and support.
Why is AI important for unburdening chronic care teams?
Chronic care management will only improve with the help of advanced technologies purpose-built to empower patients and, ultimately, streamline burdensome workflows for care teams. Some ways AI might help accomplish this two-pronged goal is through:
1. Comprehensive support for symptoms and side effects
One signature challenge to managing chronic illness at home is the possibility of a flare-up — a sudden, often temporary worsening or increased severity of an experienced disease. Patients can also encounter unexpected side effects due to the medications they’re prescribed. Though these episodes usually subside, they can cause individuals to worry about their health statuses, leading to unnecessary readmissions, increased outreach to care teams, and even deviations from original care plans — putting more strain on clinicians in the process.
That’s where digital platforms backed by AI are helping significantly. Memora Health’s intelligent care enablement platform uses AI and natural language processing (NLP) to instantly answer most patients’ symptom-related concerns and questions within the context of their specific care journeys. Furthermore, any guidance surfaced to individuals experiencing a flare up is retrieved from a clinician-curated, client-assured database that care teams can rely on. When this aspect of symptom management moves upstream from care teams, fewer messages hit their inboxes and fewer patients reenter the hospital unnecessarily.
2. Enhanced data collection, organization, and visualization
Data is essential for helping patients manage their chronic conditions. However, collecting, organizing, and visualizing information to make it actionable have traditionally been left to manual processes — which clinicians have been responsible for executing. One analysis placed the average time doctors spend in the EHR at 4.5 hours per day.
Advanced healthcare AI platforms can help solve this issue by intelligently collecting and organizing data for care teams automatically. Memora’s forward-thinking technology gathers patient data through SMS — as well as monitoring devices — and tracks longitudinal changes across indicators such as blood pressure, blood glucose, weight, and more. This information is then displayed visually in a clinician-facing, EHR-integrated dashboard for accessible and actionable insights available right when care teams need them — all without the hassle of having to manually input and interpret data.
Dive deeper into how digital advancements can help patients manage their chronic conditions.
3. Advanced SDOH support
SDOH present distinct, pervasive barriers to patients navigating their chronic care journeys. Although these obstacles — such as food insecurity, lack of transportation, and insufficient health literacy — often manifest outside the four walls of the hospital, the burden of helping patients overcome them still rests on the shoulders of care teams.
Innovative AI platforms are enabling clinicians to extend SDOH support to their patients without piling on extra work. Memora’s technology consistently assesses individuals along chronic care journeys to understand the SDOH barriers they face so that care teams have a thorough understanding of the obstacles impacting treatment plans. Beyond data collection, it also surfaces helpful resources individuals can leverage to find proper nutrition, access transportation services to get to appointments or obtain medications, and more.
4. Improved provider communication at scale
Patients with chronic conditions — especially those facing more than one — must often engage multiple specialists and providers for care. This obviously puts immense pressure on individuals to juggle different doctors for specific treatments and screenings, but also presents clinicians with care coordination challenges.
AI-backed healthtech is streamlining care coordination by intelligently automating specific aspects of collaboration and helping prioritize patient concerns. Memora’s platform allows providers to collaborate and tag one another in-thread to coordinate patient care and communication. Furthermore, it intelligently triages concerns to the right team members, ensuring individuals receive timely and personalized follow-up support — no matter how many patients care teams are treating.
Achieve better chronic care management with AI
Helping patients manage their chronic conditions is clearly challenging. But innovative platforms are already providing comprehensive symptom and side-effect support, improving data collection and organization, helping break through SDOH barriers, and enhancing care coordination. With the development of AI advancements in this area of care accelerating, there is hope for a future where extending high-quality assistance to individuals with chronic illnesses will become even simpler.