.svg)
.svg)
.svg)
.svg)
This is a summary of an episode of Pioneers, an educational podcast on AI led by our founder. Join 2,000+ business leaders and AI enthusiasts and be the first to know when new episodes go live. Subscribe to our newsletter here.
TL;DR
- Individualized healthcare addresses unique patient needs, enhancing care quality and engagement.
- By leveraging vast amounts of patient’s medical information and advanced analytics, AI can help medical care providers understand individual needs and simplify the patient journey.
- AI helps identify care gaps, recommend individualized healthcare plans and treatments, and simplify patient navigation.
- AI-driven tools empower patients with personalized education and support, improving patient’s health and outcomes.
- The future of healthcare involves AI for customized healthcare solutions and remote monitoring.
Before we dive in, be sure to check out the full episode here:
Who Is Jayodita Sanghvi?
Jayodita Sanghvi is a Senior Director of Data Science at Included Health, where she has led the data science team for about nine and a half years. Initially an academic, she earned her PhD and completed postdoctoral research in computational simulations of living systems, notably creating the first comprehensive computer model of a cell.
Driven by a desire for immediate impact, Jayodita transitioned from academia to industry, using her statistical modeling skills to enhance healthcare services. At Included Health, she integrates AI and data analytics to guide patients through their health care journeys, ensuring high-quality care.
Her leadership at Included Health focuses on making healthcare more accessible and effective. Jayodita's work significantly contributes to better health outcomes and a superior healthcare experience for all members.
The Growing Need for Personalized Health Care
The healthcare industry has witnessed significant advancements in medical technology and treatment options in recent years. However, patients often find themselves navigating a complex, one-size-fits-all system that fails to address their unique needs and preferences.
This lack of personalization can lead to suboptimal care, poor patient engagement, and, ultimately, worse health outcomes. By tailoring individualized healthcare plans, educational resources, and support services to each individual's specific needs, healthcare providers can ensure patients receive the most effective care. This approach also enhances patient engagement and outcomes.
Because of her expertise in this area, we sat down with Jayodita to discuss this topic.
She hopes for a health care service that is intuitive and personalized, where patients don't need to understand its complex details, unlike the current situation that often requires in-depth knowledge to navigate.
AI has the potential to revolutionize healthcare by enabling hyper-personalized care tailored to each individual's unique needs. So, let’s dive deeper into the key takeaways from this podcast.
AI's Role in Data Analysis to Understand Patient Needs and Deliver Individualized Care
Accurately understanding each patient's unique needs is a significant challenge in personalized healthcare. AI can assist by leveraging vast amounts of patient data and advanced analytics to understand clinical and demographic characteristics. This enables doctors to identify care gaps and offer personalized recommendations for optimal health outcomes.
AI algorithms can process vast amounts of patient data from various sources, such as electronic health records, wearable devices, and patient-reported outcomes. By analyzing this data, AI can identify patterns and insights that may not be apparent to human clinicians, enabling early intervention and personalized treatment.
The global market for big data analytics in healthcare, which involves leveraging vast amounts of complex data generated from various sources, is projected to surpass $34 billion. This highlights the immense growth and value of data-driven insights in transforming the healthcare industry and improving patient care.
AI leverages its unique position to process large datasets quickly and accurately, identifying relevant insights for personalized care. AI-powered tools, such as predictive analytics platforms and clinical decision support systems, can analyze patient data to:
- identify care gaps,
- predict risk factors,
- recommend personalized interventions.
Jayodita emphasizes AI's potential in understanding individual needs:
"AI has the power to enable us to deeply understand each individual, what their clinical needs are, what their demographic needs are, if they have any care gaps." — Jayodita Sanghvi
By leveraging AI, caregivers can comprehensively understand each patient's unique circumstances, enabling them to deliver more targeted and effective care. AI can also help identify social determinants of health (SDOH), which are non-medical factors influencing health outcomes, such as income, education, and access to healthcare for the general population.
A study published in the American Journal of Preventive Medicine highlighted that SDOH accounts for 84% of health outcomes, emphasizing the critical role these factors play in healthcare.
Additionally, McKinsey's analysis of state Medicaid data showed that interventions targeting SDOH, such as reducing potentially avoidable complications linked to factors like poor housing or food access, could significantly cut healthcare costs.
Simplifying the Individualized Healthcare Patient Journey With AI
Navigating the healthcare system can be daunting for patients, with countless options and decisions to make at every turn. Decision fatigue can significantly impact patient engagement and adherence to care plans.
AI can guide patients, helping them navigate the complex healthcare landscape by providing clear, actionable recommendations tailored to their specific needs. As Jayodita notes:
"Instead of the member having to know: here are my 50 different options provided by my health insurance, here are my options provided by my employer…they will just have a path laid out for them. Here's a much more simplified view of maybe one or two best next actions that each member should take." — Jayodita Sanghvi
By analyzing patient data and treatment guidelines, AI can generate personalized care plans detailing the most appropriate next steps for each individual. This approach helps reduce decision exhaustion and improve patient engagement, as patients are more likely to adhere to care plans that are easy to understand and follow.
How AI Can Benefit and Empower Patients Through Engagement and Education
Patient empowerment is a critical component of personalized healthcare, enabling patients to take an active role in their own health and well-being. AI can empower patients by delivering personalized educational content and resources that help them understand their conditions, treatment options, and self-management strategies.
Jayodita explained that patients might have unanswered questions, misunderstood terms, or forgotten side effects even after a medical visit. AI enables them to have ongoing interactions beyond the typical short appointment, allowing them to delve deeper and understand the information they need at their own pace.
Research has demonstrated the link between patient empowerment and improved expected outcomes. A systematic review in the Journal of Medical Internet Research found that patient empowerment interventions, such as personalized education and self-management support, improved clinical outcomes, patient satisfaction, and quality of life for various chronic conditions.
Sanghvi highlights AI's potential in creating an empowering patient experience:
"Instead of being a confusing system that people try to avoid and dread, you kind of feel empowered. You do feel like you're in control of your destiny through your healthcare journey." — Jayodita Sanghvi
AI-powered chatbots and virtual assistants are emerging as powerful patient empowerment and engagement tools.
AI's Impact on Clinical Effectiveness Through Individualized Care
The ultimate goal of individualized healthcare is to achieve better patient outcomes.
AI can support clinical decision-making and help healthcare providers deliver more accurate, targeted, and effective care by analyzing vast amounts of patient data and clinical evidence.
AI can assist in various aspects of clinical care, from diagnosis and treatment selection to medication management and monitoring. For instance, AI algorithms can analyze medical imaging data to detect early signs of disease, such as lung cancer or diabetic retinopathy, with high accuracy. This enables earlier intervention and more targeted treatment, improving patient outcomes and reducing healthcare costs.
In treatment selection, AI can help providers identify the most appropriate therapies and medications based on a patient's characteristics, such as their genetic profile, medical history, and lifestyle factors.
A study published by researchers at the National Institutes of Health (NIH) in Nature Cancer detailed the development of an AI tool that uses single-cell RNA sequencing data to predict whether a patient's cancer will respond to specific drugs. This tool, known as PERCEPTION, accurately predicted patient responses and the development of drug resistance based on high-resolution gene expression data from individual tumor cells.
By leveraging AI-powered medication management tools, healthcare providers can analyze patient data to identify potential drug interactions, adverse events, and optimal dosing strategies. This allows them to create effective individualized healthcare plans, reduce adverse events, and improve patient response rates.
“Moving on to routing members to the highest quality of care, and then ultimately delivering care, but in a way where it is information complete and our providers have the whole story behind the members, and are really able to help them through their entire journey in a way that seems very connected.” — Jayodita Sanghvi
Another example is the AI-powered platform Medisafe, which uses patient data and behavioral insights to provide personalized medication reminders and adherence support. A study published in the journal JMIR mHealth and uHealth demonstrated that this approach leads to significantly higher medication adherence rates than patients who did not use the platform.
The Future of AI-Driven Individualized Health Care
The potential for AI to transform healthcare by enabling personalized care tailored to each individual's unique needs, preferences, and circumstances is immense.
However, implementing AI in healthcare is not without challenges and ethical considerations. Ensuring patient data and medical information privacy, addressing AI biases, and maintaining human oversight are critical for responsible AI integration into health care.
As AI technologies advance and mature, we will see more customized healthcare solutions and tools, including individualized treatment plans and AI-driven remote monitoring.
“There's a power of AI and what you can do to make healthcare much more understandable, much more easy. It can actually get people to the right providers within the system that actually have the right experience to treat this member of this community at this moment of need, and the power to just kind of integrate across the whole system.” — Jayodita Sanghvi
To realize AI's full potential in personalized health care, healthcare organizations must embrace these technologies to enhance the patient experience and improve outcomes. This will require significant investments in data infrastructure, AI talent, provider education, and close collaboration between healthcare stakeholders, technology developers, and patient advocates.
The journey towards a more patient-centric, outcomes-focused healthcare system is well underway, and the possibilities for transforming the patient experience through AI are truly exciting.
By harnessing the power of AI to deliver individualized healthcare, we can empower people to take control of their health and well-being, ultimately leading to better health outcomes for all.
