Healthcare personalization trends
Today’s patients have access to a greater amount of health data than ever before – and they want that data to be used for their benefit. This creates a vast number of opportunities for healthcare personalization to engage patients in their own care, drive better health outcomes and decrease costs.
The demand for personalization is most prevalent with younger patients, who grew up with technology integrated into their everyday lives. These digital natives stand to have increasing influence over the health system as they age.
“We’re already seeing that millennials and younger generations won’t be the same kinds of patients as their parents,” Eric Dishman, general manager of Intel’s Health and Life Sciences, told Phys.org. “18-to-34-year-olds already expect to have data and tools to help them manage their health, just like they do for everything else in their lives.”
With the aid of advancing technology, health care is evolving to meet these demands. Those who capitalize on the personalization trend are expected to emerge as market leaders.
Unveiling connections in patient data
Adoption of artificial intelligence is becoming widespread in health care, in large part due to three factors laid out in a recent report commissioned by the U.S. Department of Health and Human Services: patient frustration with the medical system, the pervasiveness of smart devices today and growing expectation of on-demand services such as those offered by Amazon. AI’s ability to drive personalization at scale is expected to change how health care companies interact with their patients and members and help them evolve for this new status quo.
One example of this in action is machine learning software developed by GNS Healthcare, which identifies relationships in patients’ health records and other data such as patient notes. It uses those relationships to produce hypotheses and determine which most likely occurred, and has identified a previously unknown drug interaction.
Recently, PK partnered with Intel and Sharp HealthCare to develop a Proof of Concept that health care organizations can use for machine learning-powered patient risk scoring. Designed for inpatient hospital populations, the PoC is built on a model that draws on electronic medical records to predict imminent patient health decline. The model is built using open source machine learning tools, which identify patterns in health records data and predict the likelihood of a Rapid Response Team event taking place in the next 12 hours. This allows health care organizations to achieve better outcomes through better prioritization and enablement of personalized care.
New and innovative applications of AI in healthcare personalization such as these are certain to enter into force over the next several years.
Personalized digital content
Healthcare personalization has become a priority for health care marketers for good reason: 80 percent of consumers are more likely to do business with a company that offers personalized experiences. For Dignity Health, which delivers care in 22 states, personalization extends far beyond the exam room. To offer better communication with its care providers, access to medical records and streamline appointment setting, Dignity Health and PK developed a mobile app for iOS and Android. With the resulting app, patients can easily schedule appointments and review their appointment history without the need to call. Its dynamic dashboard displays personalized content based on the patient’s profile, health data and location, offering a one-of-a-kind health care experience. For more patients today, turning to their smart phone or computer for health information is a typical behavior — 62 percent of patients search for info on drug prescriptions, and 58 percent search online to diagnose their symptoms. Platforms such as these enable health care companies to provide a customized experience that aligns with modern patient demands and their own offerings.
Blockchain is solving health privacy concerns
Following numerous health care data breaches over the last few years, many patients have grown concerned about how their data is being used and stored. This presents a challenge to personalized medicine because health care providers and insurers already balance the use of patient data with HIPAA concerns. A new health care startup is seeking to alleviate these privacy concerns – using blockchain technology – to deliver healthcare personalization. Bowhead Health uses the combination of a smart home testing device and blockchain technology to offer at-home health monitoring and personalized supplements based on blood and saliva tests. Users are incentivized with digital currency tokens in exchange for health-promoting activities and sharing their health data with researchers. The decentralized, blockchain-powered technology securely stores and encrypts customer data, and patients are in control of how their data is shared and used. The company is currently beginning to manufacture its first nutritional supplements and is targeting the integration of its at-home testing kits later this year.
AI, personalized content and blockchain are among the top technologies that stand to change how care is delivered to patients. By adopting these new technologies, healthcare companies can develop engaging new experiences that deliver better outcomes and meet patient concerns.
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