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The Role of Artificial Intelligence (AI) in Chronic Disease Management

Jon-Michial Carter
Written by Jon-Michial Carter

Artificial Intelligence (AI) has the potential to play an important role in chronic disease management, including in Chronic Care Management (CCM). The Centers for Medicare & Medicaid Services designed CCM to help Medicare patients living with two or more chronic illnesses improve their health outcomes. AI tools help by making CCM coordinators more efficient.

Through the use of machine learning and AI, care coordinators can remove less impactful busywork and focus on patient care. However, AI should never replace a human care coordinator who can connect and engage with patients each month.

In this post, we'll explore the pitfalls and the potential of incorporating AI into Chronic Care Management services, and break down where it should and shouldn’t be used. 

Where AI Shouldn’t Be Used in Chronic Disease Management

AI can provide care coordinators with insights into patient sentiment, condition management, and available resources—but it can’t replace the human connection between two people. 

“A nurse or a clinician knows what the patient needs better than any computer could,” Nic Erickson, Vice-President of Operations for ChartSpan, said when asked about AI. “So all patient-facing interactions should be with a real person.” 

ChartSpan employs nurses and care coordinators to call every patient, every month, and Erickson doesn’t foresee that changing. “The intent is for patients to have access to a clinician that can help support their chronic needs,” he stated. 

Commitment to Human Connection Over AI

ChartSpan will continue to use nurses and care coordinators to talk with patients, direct them to resources, and help them follow their provider’s established care plan. The 24-hour nurse line will also always be staffed by certified nurses who can respond quickly to emergencies. 

Additionally, AI can’t take the place of a person when it comes to emotional support. A patient struggling with loneliness or illness often needs someone to talk to just as much as they need assessments or care goals. 

Because ChartSpan uses personal care coordinators for each patient, the patient will have the opportunity to speak to the same person multiple times and connect with them on a deeper level. 

While human care coordinators will never be replaced, CCM offers opportunities to use automation and AI in other areas, such as quality improvement, risk assessment, and patient engagement. 

Opportunities to Use AI in Chronic Disease Management

AI has the potential to assist care coordinators with: 

  • Improving the quality of patient calls
  • Identifying patients who are at risk of worsening illness
  • Crafting condition management strategies
  • Finding educational resources for patients
  • Managing records more efficiently

Here’s a breakdown of how CCM providers and practices can embrace AI for productivity, without sacrificing the human component of healthcare: 

1. Quality Improvement

AI can play a crucial role in improving the quality of patient-care coordinator interactions. For example, AI-driven call auditing and sentiment analysis tools are now being used. These tools analyze care coordinators’ calls with patients and offer insights for the care coordinator on how to be more supportive and engaging when discussing care goals or assessments. 

AI also improves the quality of CCM enrollment calls. After examining enrollment calls, the software will generate tips for how enrollment specialists can make Medicare patients feel more comfortable and better understand Chronic Care Management. 

2. Risk Assessment

Providers can use AI's predictive modeling capabilities to have a better grasp of the likely progression of chronic diseases. AI can analyze data like blood glucose levels, blood pressure, Social Determinants of Health (SDOH) screening results, and medication use. Then, it can alert providers to look more closely at high-risk patients and intervene to prevent further complications.

Care coordinators can also benefit from predictive modeling capabilities. Machine learning programs can review patients’ self-reported health data, their assessment results, and the medical records shared by their provider. The AI will then offer alerts about issues care coordinators may want to bring up with the patient and discuss with the patient’s provider. 

3. Condition Management

Care coordinators work with patients to create care plans that address their chronic conditions. Generative AI can help by suggesting reasonable care goals based on a patient’s history, conditions, and lifestyle.

For example, if a patient wants to cut back on how much soda they drink, the AI suggests a plan for gradually reducing their intake over the course of a few weeks. The care coordinator can then present the plan to the patient as a jumping-off point, and the patient can modify it to match their needs. 

AI even helps care coordinators with resources. For example, if a patient needs help with healthy food, AI generates a list of food pantries or food delivery services in their area that have fresh produce. The care coordinator then shares that list with the patient. With AI, care coordinators can spend more time with patients and less time scouring the web for ideas or resources. 

4. Patient Engagement and Education

Chronic Care Management engages patients as partners in their health. For the program to work, patients must help create their care goals, take accountability for those goals, and communicate their needs to their personal care coordinator. 

AI supports this process by suggesting reliable educational resources for patients, like peer-reviewed articles, videos, and infographics. If a patient requests more information on one of their chronic conditions, care coordinators can use AI to locate reliable resources in multiple languages, written at an appropriate reading level, or in a variety of formats. 

5. Efficiency Changes

AI and automation also helps care coordinators complete their work more efficiently. ChartSpan care coordinators use an autodialer to move onto their next call without wasting time manually checking which patient is next. This allows them to spend a greater percentage of their day actually talking with patients. 

They also use automation to pull up a patient’s chart, then quickly identify which topics are most important to address during a call. This saves care coordinators from spending excessive time each day rereading every patient’s chart to determine what they need to discuss. 

The Future of AI in Chronic Disease Management

As CCM providers and practices begin to integrate AI into Chronic Care Management, we need to remember that AI can’t replace the connection between patients and care coordinators. CCM is meant to give patients ongoing access to healthcare professionals, not to AI software. 
Still, the strategic implementation of AI could transform chronic disease management by making it more personalized, efficient, and equitable. Care coordinators can use the technology to make their calls more empathetic, to identify health risks providers should know about, and to find accessible local resources for patients. By using AI to empower care coordinators, not replace them, we can help Chronic Care Management programs bring even greater value to patients.

To learn more about how CCM can improve outcomes for patients with chronic illness, check out our whitepaper on Empowering Healthier Lives.

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