How AI can unlock a customer-centric approach towards healthcare

You probably read that title and think, “that’s an oxymoron — AI and consumer focus are surely at odds with one another.” After all, the perception with AI is that it cannot possibly be as personal as a human touch, which is vital in patient care. However, during this age of rapid technological advancement in areas such as travel and retail, people now expect this same accessibility regarding healthcare services. Benefits explanations, provider directory access, telehealth, and appointment scheduling are all features that can be beneficial to patients, while also encouraging new membership for private providers and improving patient satisfaction.

According to a recent ‘AI in Healthcare’ study conducted by ZS, 80% of physicians already utilize AI in some form in their practice, while another 21% have been mandated to do so by their organization. From a healthcare standpoint, these algorithms are helpful in assisting physicians with administrative duties, aiding them in making better decisions, and even providing treatment, such as analyzing a radiology report in the same way as a fellow doctor.

Healthcare professionals need to abandon outdated concepts in the healthcare industry and embrace a modern business model that offers more efficient processes to better meet the current demands of the health sector. This is something that companies such as Nisum, Koru, and Star—who are all involved in healthcare tech innovation—are working towards by tapping into principles such as ‘design thinking’ to enable patient centricity. 

Let’s dive into the key areas where AI can truly assist doctors and patients alike, to provide an overall customer-centric healthcare approach.

Data Management

AI technology is revolutionizing the way doctors diagnose and treat their patients. With the help of data mining, providers can access a wealth of information from thousands of other doctors, giving them the ability to search for symptoms they might not have seen before. Modernizing Medicine is just one example of a platform that collects records and insights from nearly 3,700 doctors and 14 million patient visits—the equivalent of having Google, but only with results from qualified professionals.

Physicians also need to access clinical data in real-time to make the best decisions for their patients. For example, if a patient is diagnosed with heart failure, their doctor should have comprehensive knowledge of their history of heart attacks, blood clots, and other related clinical data. Unfortunately, in many cases, physicians are not fully informed of a patient’s clinical history. Artificial Intelligence can serve as a single source to track this data, learn from its experiences, and provide the best solution for the patient.

Furthermore, AI can help patients adhere to post-hospitalization guidelines to help maintain their health.

Data security is one of the most pressing issues when facing AI-driven healthcare. To alleviate their concerns, health plans must give members more detail about the precautions they are taking to safeguard their data, including data potentially obtained from social media. To earn the trust of patients, health plans and startups in the health AI industry must make it clear how the patient information is being secured and only used to benefit the patient.

Telehealth Advancements

Telehealth platforms are making it possible to overcome the time and location barriers in receiving care. Whether it’s an elderly member in a rural setting who wants to get advice from a world-class specialist or a parent who wants to ask a quick question in the middle of the night about her child’s high temperature, telehealth platforms are making it easier to get help at the time and location that works for the consumer.

According to a recent survey, there is a high degree of receptivity among both patients and physicians towards telemedicine, as 22% of physicians work in an organization where patients can access a virtual physician through a telehealth platform or application, and 45% of patients have received care outside of the doctor’s office through devices such as computers, tablets, and smartphones.

Connecting a patient to the right physician is not always a foregone conclusion. In the process of a patient looking for a specialist for their particular condition, they might need the advice and help of their primary care physician. However, this process might take too long, and this is where AI can help by making the proper connection between past interactions, medical history, and other preferences to match a patient with a specialist. Lemonaid is an example of a platform offering this service, where AI and machine learning are harnessed through a voice-activated bot that can listen to patients’ symptoms.

Biopharma and Enhanced Treatment

In recent years there have been countless examples of biopharma companies utilizing AI and machine learning to enable data-driven understanding of disease prevention. It’s becoming increasingly imperative to treat patients faster, and companies such as ChemBeads are using automation to dispense chemically-coated beads to accelerate the process of creating the conditions to make chemical compounds in a few days instead of weeks.

Researchers have used magnetic resonance imaging (MRI) to differentiate between brain scans of individuals with and without fibromyalgia—a condition that causes musculoskeletal pain. A study utilizing machine learning (ML) to diagnose fibromyalgia was able to achieve nearly 90% accuracy, as it identified a combination of microbiome-associated species that either increased or decreased in patients with the condition. Moreover, an ML study involving neural networks was able to locate the best biomarker for diagnosis.

Monitoring and Insights

By combining wearable technology with AI, healthcare providers can better manage chronic conditions. AI-enabled wearable devices not only provide real-time data on the condition but also offer insights into trends and patterns that can inform personalized treatment plans. AI-powered wearable devices can detect early signs of a flare-up or worsening of the condition, allowing healthcare providers to intervene sooner and provide more effective care. 

Wearable technology and AI can also help patients better understand their condition, allowing them to adjust their lifestyle and medication accordingly. AI-enabled wearable devices provide a comprehensive and proactive approach to health management, helping to reduce the burden of chronic conditions on both patients and healthcare providers.

No matter what AI applications are included by healthcare providers moving forward, plans must devise a strategy for engaging doctors and patients. This needs to be done with flexible design thinking in mind and is essential for improving AI-driven care that is specifically tailored to each patient, as Nisum stress in their health tech ebook:

“Creating products and services with new-age digital capabilities requires a business model that emphasizes value and results-based outcomes. Design thinking, lean thinking, and empiricism are three principles that help create efficient customer-centric processes and facilitate successful digital transformation within the healthcare industry.”

As research and patient data continue to accumulate, patient-centric approaches such as targeted drugs, more accessible diagnostics, and remote care tailored to the needs of the patient are becoming increasingly attainable.

If we take the time to develop AI correctly, we could unlock a range of benefits for both businesses and society. Personalized drugs, improved diagnosis, and tailored health and wellbeing regimes could be just the tip of the iceberg.

This article includes a client of an Espacio portfolio company