The increasing convergence of technology and healthcare continues to marvel both healthcare providers and technology enthusiasts alike. The drivers of innovating in this space include increasing access to care, providing patients with more personalized diagnostics, and ultimately, increasing societal health standards.
However, to prevent a purely myopic view of this booming discipline requires an examination of not only where this technology currently stands, but also its potential impacts on shaping the future of healthcare delivery.
Where the Technology Stands
One of the most novel innovations in healthcare technology emerged with IBM’s Watson platform, first developed by the company as a query-response system which could digest and synthesize substantial amounts of data in order to respond to delineated queries. Scaling this same technology for industrial use, Watson Health was created to aid the clinical decision making portion of the healthcare delivery model. Proponents posit the system’s advanced cognitive capabilities, noting its ability to read 200 million pages of text in 3 seconds, and highlighting its efficacy in synthesizing copious amounts of unstructured data to determine macro-scale patterns and propose models to aid the diagnostic process. Years of development and fine-tuning have increased the capabilities of Watson; the latest frontier has been Watson for Oncology, which mines multitudes of oncological patient diagnoses and case studies to present potential courses of treatment with their respective confidence intervals for physicians to use in their diagnostic process. The applications of this technology are endless, as Watson is attempting to scale this technology into other verticals of medicine.
Other notable ventures in this space have focused on increasing personalization in medicine, recognizing the potential in utilizing mobile technology and other interactive hardware (e.g. wearable technology) in effectuating healthcare delivery. One such startup that is venturing into this space is Ginger.io, which uses a smartphone application to analyze a user’s social interactions (frequency of texting, geolocation factors to determine where a person visits, and even speed of typing) as metrics of determining well-being. The app can then automatically compile and send this data to both the patient and the patient’s healthcare provider, who can then follow up for a formal consultation.
Mobile applications as such also contribute to increased efforts in telemedicine, a branch exclusively dedicated to incorporating healthcare delivery with traditional telecommunication platforms. Notable companies such as Healthtap and Doctor on Demand provide patients with real time access to physicians from the comfort of their homes. The call for such convenient access platforms is being met by investors, as increasing amounts of capital are being invested to develop this space. Doctor on Demand raised $50 million in Series B funding alone, and continues to grow its market share in the telemedicine arena. As more companies enter this space, telemedicine will become a cheaper and more viable option for patients seeking real-time care.
“Wearables” technology such as heart rate monitors, motion trackers, and fitness accessories, have also made strides in the healthcare industry, providing physicians access to an increased granularity of patient-data to use in determining appropriate treatment plans. Massachusetts General Hospital’s cardiology department was among the first to incorporate this technology as a part of their diagnostic routine, using data from patient’s wearable accessories to set up virtual appointments and to create tailored treatment plans. Accordingly, the wearables and health accessories industry will continue to expand, as companies and consumers continue to demand new and creative ways to analyze personal health metrics.
Impacts on Healthcare
Ultimately, the ability of cognitive platforms, applications, and accessories in collecting large amounts of patient data over an extended period of time, and synthesizing that data to provide a broader picture and a larger sample size of a patient’s health, will be invaluable to physicians. As healthcare delivery models are increasingly focusing on holistic health and moving away from acute symptom management, physicians with access to such increased patient metrics will be at an advantage to foster a proactive rather than a reactive patient relationship.
However, with increased emphasis on delivering healthcare through novel platforms, there are looming concerns of human providers being replaced by technology. While proponents of autonomous healthcare models may cite reduced costs and uniformity in diagnosis, examining the realities of practicing medicine illuminates the difficulties of removing the human element completely.
A standard example is an emergency room triage situation. If two patients come in with equally dire medical needs, a data-driven intelligence platform cannot be expected to rationalize who to treat first and apply the ethical considerations that a physician would; rather, the system will choose to treat purely based on who it thinks has the most viable chance to live. Experimental studies have confirmed this pain point: when an automated robot system was given only one “dummy” robot to save, the robot could prevent the fatality. When confronted with two such dummy robots at the same time, the automated system failed 14 out of 33 times in saving either of the victims.
Relay this difficulty to stronger ethical conundrums such as palliative, or end of life care. Software with access to millions of stored diagnostic patterns and outcomes may be able to dictate statistically favorable prescription dosages or procedures which the patient should attempt. However, the art of clinical decision making is a premium which no software can match, giving a physician an opportunity to connect with the patient and ultimately determine that sometimes, the best care plan provided to terminally ill patients is one which values quality of life over longevity. Regardless of the ethics behind balancing those sometimes mutually exclusive values, automated diagnostic tools or data-crunching software will not be able to fully replace the need for a human perspective.
Technology in healthcare that allows for more data driven decision making and augments a physician’s diagnostic ability will prove to be significantly useful to physicians of the future. Overall, this technology will provide physicians the information required to make more informed decisions, based on larger sets of patient data. However, proponents of this technology must remember that the purpose of medicine is not to blindly promulgate successful clinical outcomes, but is rather about promoting successful clinical outcomes while balancing patient care, and the soft, human factors that are inherent to the patient-physician relationship.