The classic story of disruptive technology is all too familiar. Travel websites replace agents by giving consumers access to the same rates. Uber offers transportation outside of the established taxi cab system. Amazon brings outlet shopping into our homes. The common thread in all these examples is the transfer of more power to consumers. These changes usually cut costs, increase efficiency and often force out those who cannot keep up. Most of these fundamental developments occur in fields that do not require highly technical expertise, such as housing and transportation, allowing consumers to take control without extensive training.
The specialized knowledge and professional barriers in medical practice have, for many years prevented consumer involvement—leaving control and decision making solely in the hands of the healthcare provider, with the patient largely on the receiving end of information that directly affects their care.
However, these barriers are beginning to crumble.
Over several decades, patients have become more active in pursuing better care and are looking for knowledge sources that can help them become more educated and active participants in their care. Recently, advancements in AI (artificial intelligence), big data analytics, mobile technology and cloud computing have started to enable patients to take greater control of their medical care, leading towards a major shift in the patient-physician relationship.
Patients’ Growing Access to Information
The first hint of the evolving physician-patient relationship started when medical information became accessible to the layperson. Websites such as WebMD began to make medical literature comprehensible, accessible and searchable. Beyond this, social media and patient blogs allowed people to compare their experiences with others’, creating a better understanding of what their symptoms may be telling them. However, this data was still too general and not personalized.
Patient access to their personal health records (via patient portals) was the next important step in enabling patients to inquire about their own personal health.
Next, mobile technology has allowed patients to track, store and manage their medical history with increasing accuracy. Furthermore, FDA-cleared wearables have advanced to provide vital signs and other sensor-related data, adding more dimensions to the personal clinical data stored on the consumer’s mobile.
Now, consumer-focused companies such as Apple, are providing consumers with access to their full medical records from multiple healthcare providers on their mobile devices. Together with the wearable sensor and patient-entered data, the patient now has access to a far more enriched, comprehensive and accurate up-to-date data than any of the individual healthcare providers treating him/her.
However, understanding the clinical implications of the data to the individual is challenging for most consumers. Consumers are flooded with their own clinical data, with limited ability to utilize this data to benefit their own health.
Making use of the personal data by providing real-time clinical insights and risk assessment to the individual patient is key in empowering patients and care givers to enrich the dialog with their providers and in facilitating better care for themselves and their loved ones.
This is where big data analytics and AI may facilitate this change. The application of these technologies on large scale personal health records can be used to learn behavioral patterns of providers and patients in the process of care, and ultimately, apply the insights derived from these analyses to the individual patient. This may help consumers identify emerging risks, such as medication related adverse drug effects, gaps in care or early identification of clinical deterioration necessitating medical attention. Moreover, this technology may help patients in choosing between alternative care paths which are optimal to their own personal clinical state.
In turn, physicians are also being armed with AI-based tools of their own to enhance their clinical decision-making and provide greater transparency into patients’ activities between visits. An increased understanding and practice of machine learning has allowed health technologists to explore millions of patient records, identify patterns, and derive “needle in a haystack” insights they may not have found otherwise.
Data access combined with AI and big data analytics will empower clinicians and patients towards better healthcare delivery. This means that the two can meet on a higher plain of understanding and pursue data-driven care plans, in partnership.
The Future of the Medical Industry
The same principles that changed the financial and transportation industries are now becoming a reality in medicine. Consumers are gaining access to both the information and insights that will position them as drivers in their medical journeys, and this change is just around the corner. It is no accident that according to a 2018 Ernst and Young survey on the Future of Health, consumers are expecting a modernized physician-patient relationship and are already comfortable utilizing digital technologies.
Physicians, for their part, also seem to be ready for this change. A 2016 survey by the American Medical Association showed that the majority of physicians welcome digital health tools, including those driven by AI. According to the survey, physicians will embrace the tools that can improve practice efficiency, patient safety, diagnostic ability, reduce burnout, and improve the physician/patient relationship.
Accordingly, AI should be thought of as a medical liaison to physicians and patients alike, that provides quick and accurate insights to enhance optimal care. Ultimately, these advancements can return medicine to what it used to be: a practice focused on care and interpersonal relationship, in which patients and physicians act as partners in care. These developments are positive for the healthcare industry, and physicians that adapt and adopt will benefit.
Dr. Gidi Stein is a practicing physician, researcher and serial entrepreneur. In 2012 he co-founded MedAware, utilizing machine learning algorithms to eliminate prescription errors and promote patient safety.
