Through surveys and applications, mobile technology—including smartphones and wearables—gathers health-related data, including sleep patterns, self-reported health information, and physical activity measurements (e.g., heart rate, step counts).
A Stanford University study from 2022 demonstrates how these data let AI systems track health patterns, anticipate possible problems, and tailor medical treatments, improving patient outcomes and encouraging preventative health care.
Additional Harvard research that was published in Nature emphasizes how combining AI and data from mobile health technology allows for the creation of individualized healthcare solutions that are catered to the needs of each patient. In order to improve patient outcomes and engagement, AI algorithms evaluate this data to forecast health risks, suggest preventive actions, and personalize treatment regimens.
Blue Cross Blue Shield’s Ylan Kazi recently spoke with Matthew DeMello, Senior Editor at Emerj. They looked at how AI and mobile technologies may improve patient engagement, personalize healthcare, and give patients greater control over their health.
They also talk on the need for innovation to get past regulatory obstacles in the healthcare sector, the increasing demand for real-time data, and tailored AI applications.
Make the most of mobile technology to transform diagnostics: Real-time patient insights can be obtained using smartphone data, which enhances healthcare outcomes, decision-making, and care coordination.
Applications that are specifically targeted for optimal healthcare impact: transforming AI use cases into focused solutions that improve patient involvement, facilitate communication, and provide quantifiable benefits while emphasizing appropriate testing and data accessibility.
Below, you can hear the entire episode:
Make The Most Of Mobile Technology To Transform Diagnostics
In his opening remarks, Ylan highlights the need of individualized medicine. He wonders why individual variables like body size or heredity aren’t taken into consideration while determining uniform medicine dosages. He believes that using genetic data to customize medicines could improve their efficacy and safety in the future.
Ylan starts his discussion of diagnostics by outlining certain difficulties, even if he also finds AI advancements in the pharmaceutical industry fascinating because they hold the potential to speed up, improve efficiency, and customize medication research. It can be challenging to separate these difficulties from data-driven opportunities, perhaps more so than in most regulated sectors like healthcare.
He begins by outlining how mobile technology has revolutionized healthcare by making diagnostic tools more widely available outside of conventional clinical settings. He notes that being a patient was mostly connected to going to a clinic or hospital until recently.
But thanks to the quick development of mobile technology, smartphones—which now have sensors, speech recognition, and navigation—have developed into effective medical instruments.
These characteristics allow phones to serve as diagnostic instruments, gathering important health information. According to Ylan, if doctors and nurses had access to this real-time data, they could create a more thorough patient profile, which would help them make better clinical judgments and deliver better patient care.
The main lesson for healthcare executives, according to Ylan, is that the same mobile technology—GPS systems and personal biodata from personal devices—is at the heart of advancements we observe in the manufacturing and insurance-related sectors of the average healthcare organization.
He mentions, for example, how AI is influencing the healthcare supply chain, especially on the provider and delivery side, while also being essential in optimizing the payer side, particularly in the processing of medical claims. He goes on to say that processing claims is a complicated procedure that includes maintaining payment integrity and making sure that services are paid on schedule and appropriately.
Many firms still rely on expert human evaluations because of this intricacy, but AI is helping to automate these procedures and cut down on inefficiencies. If healthcare administrators use mobile data-driven AI with the appropriate technology, it can eventually improve the overall healthcare experience for patients and providers by increasing accuracy and expediting claims handling.
Targeted AI To Have The Biggest Effect On Healthcare
Ylan admits that although AI was once thought to be a panacea, numerous applications did not produce the desired outcomes. These days, AI partners and vendors are adopting a more focused strategy, concentrating on particular healthcare domains or use cases where AI can result in quantifiable value and considerable cost reductions.
He believes that AI, such as ChatGPT, has the potential to enhance patient involvement and expedite medical correspondence. He draws attention to the current system’s frequent fragmentation, which results in inefficiencies. Patients see doctors, undergo lab testing, and receive results through a variety of channels at different times.
He used his own experience of getting lab results online from a vendor almost two weeks before his doctor’s office received a physical copy to highlight communication breakdowns. According to him, AI might facilitate better communication between labs, patients, and clinicians by assisting in the coordination of the whole patient experience.
He does, however, also recognize the necessity of exercising caution, conducting adequate testing, and being aware of AI’s limitations. In the end, he believes AI has the potential to enable people to take a more active role in managing their health instead of depending on healthcare institutions, which frequently serve as gatekeepers to their own data.
According to Ylan, external factors rather than internal industry dynamics will drive significant innovation in healthcare data. He ascribes this to the strict laws governing data security and privacy, especially at the hospital level, which make it difficult to enact revolutionary reforms.
“When you want to use data to innovate, particularly in a medical setting.” However, when I consider the general direction of the world and the general consumer experience, I find that when you buy something on Amazon, you can view your past history and know exactly when your package will arrive.
An increasing number of people are beginning to desire that with their personal health information. Therefore, I believe that there will come a time when enough people will demand it, which will increase the pressure on hospitals to alter their approaches to data security and protection while also taking into account the fact that this is personal patient information.
-Ylan Kazi, Blue Cross Blue Shield North Dakota’s Chief Data and AI Officer