Effectively managing chronic diseases such as asthma, diabetes, cancer, and several others have been one of the biggest challenges for healthcare providers worldwide. According to a study, chronic diseases are responsible for 70% of deaths and about 50% of the disease burden globally. Owing to this, we will discuss how AI in chronic care management can change these numbers.
As the pandemic unleashed a global health crisis, many countries faced a shortage of healthcare professionals and medical resources. This caused several hurdles for patients with chronic conditions to get treatment at the right time. Such conditions forced chronic patients to adapt to remote and digital treatment, which is the new normal in the current world.
For medical professionals to deliver quality remote healthcare, it has become essential to leverage fast-emerging technologies like Artificial Intelligence (AI) and Machine Learning (ML).
Both AI and ML have already shown how they can significantly improve the efficiency of operations in various other industries like e-commerce, manufacturing, automotive, etc. In this article, we will take a look at the role of AI in Chronic Care Management (CCM).
Key Benefits of Chronic Care Management
Before we understand the importance of AI in Chronic Care Management, let us look at some key benefits of Chronic Care Management:
- Chronic Care Management or CCM offers an organized approach to dealing with chronic conditions, making the process more coordinated for patients as well as the healthcare provider.
- Healthcare providers can build long-term relationships with patients through their CCM services, which can result in increased revenue.
- It can prevent unnecessary visits to partitioners.
- Researchers have proved that CCM can offer quality healthcare to patients at a lower cost.
What is the Role of AI in Critical Care Management?
Here is how AI in chronic care management can turn around the situation:
● Medical Data Analysis
An extensive medical data set will be required to utilize AI in chronic care management at its full potential. In today’s digital world, it can be easily gathered throughout the patient life cycle via mobile applications, IoT devices, and patient portal software. An Al-based algorithm can analyze this pool of data and generate new insights and opportunities for both patients and medical professionals in CCM. This can streamline the overall chronic care management processes.
● Prognosis and Prevention of the Disease
One aspect of CCM is to prevent diseases from happening. With the help of AI, practitioners can identify the choric disease to which the patient is susceptible. This allows the doctors to take the correct preventive measures and circumvent the chronic condition.
In a study published by Yannis Paschalidis in Harvard Business Review, healthcare professionals were able to forecast hospitalizations due to diabetes and heart disease a year in advance using machine learning and Electronic Health Records (EHRs) with an accuracy of 82%.
● Diagnosis of Diseases
Many recent studies have proved that AI can also be indispensable when it comes to the diagnosis of diseases. Al-algorithms can easily detect diseases based on data points like medical imagery, ECG data, patients’ demography, and their medical history. Such developments have led to time and cost-effective CCM service. It also has significantly improved remote diagnosis.
The healthcare data can be used to create AI/ML models that can assist physicians in medication modeling and treatment suggestions. These models can be further applied to suggest appropriate dosage and treatment plans for the patient.
A personalized plan and treatment for individual patients can also be created by AI. The personalized treatment can enable clinicians to intervene before a patient’s condition becomes critical, making CCM more effective.
Recently, a company named IBM Watson has achieved some remarkable results by utilizing AI in the field of oncology. The organization performed genetic data analysis and was successfully able to identify the rare secondary leukemia caused by myelodysplastic syndromes.
● Remote Patient Monitoring (RPM)
With an AI-powered CCM, healthcare professionals can constantly monitor a patient’s vitals like blood pressure, pulse rate, temperatures, etc., from the comfort of their home. The AI can also send an alert to health professionals if there is any sudden or critical change in the vitals of a patient.
● Virtual Assistant
Chronic diseases generally last for a lifetime. As the patient gets older, it gets difficult for them to keep track of medication and appointments, which causes disturbance in their chronic care management. In such cases, an AI-powered virtual assistant can come in handy for the patient. It can assist them by ensuring drug adherence and also monitor their vital data.
For example, a Meditech company created AI-embed nurse avatars that send notifications to the patient each morning for a check-in routine, record their vitals, and sends alerts for timely intake of medicine.
Another aspect of chronic care management is measuring and managing the patient’s chronic pain. Here again, AI can assist in detecting chronic pain by monitoring the facial muscle movements of patients who are unable to self-report the pain to their physicians.
Artificial Intelligence can offer actionable insights to guide clinical decisions and allow physicians to diagnose, treat and handle chronic conditions remotely, thus making chronic care management more efficient, accessible, and affordable.
That’s why many healthcare organizations have begun to utilize AI in their chronic care management services. If you are also looking to leverage AI to improve your chronic care management, you will need to hire or work with people who have relevant expertise and skill set.
Mindfire Solutions is an IT-service provider that has worked with several healthcare organizations over the years to provide customized healthcare tech solutions that are highly cost-effective, secure, and scalable. Visit Mindfire Solutions to learn more about us.