Is Healthcare Ready for an Uber-Type Patient Application?

Andrew L. Pecora, MD

Genomics, proteomics, precision analytics, Big Data analysis, and artificial intelligence now in use or in late phases of development can help healthcare providers to achieve the promises of the Triple Aim of medicine: improve clinical outcomes for all, reduce total cost of care for the populations served, and improve patient experiences.

For quite some time, oncology has been at the forefront of using genomic information to target therapy against genetically driven molecular mutations, leading to improvements in overall survival. Proteomics is now the leading edge of the sword in improving outcomes because it prevents the synthesis, or translation, of damaging proteins. Applied immunology is another breakthrough technology that can dramatically improve outcomes when used properly and with good timing.

As medical data accumulate, physicians are losing the ability to acquire, process, and utilize this information in real time to help their patients. Many physicians are not keeping up with the rapidly evolving knowledge base, and patients are not achieving optimal outcomes in all cases due to adverse variance in care (too much or too little care). Adverse variance leads to increased costs of care and lessens the return on investment for companies that develop new therapies and devices. This is because the marketplace is slow to accept innovations it doesn’t understand well enough.

Enter precision analytics, Big Data, and artificial intelligence. The dream is to provide the current world’s medical knowledge at the point of care along with real-world evidence and precise patient stratification, thereby enabling optimal care choices and outcomes. Indeed, this issue is of particular importance to researchers at Dana-Farber Cancer Institute and Brigham and Women’s Hospital. They are among those making strides for personalized medicine by analyzing patient DNA data for actionable DNA mutations. We write about this effort on page 34.

Physicians have a moral duty to do what is in the best interest of their patients and, based on their knowledge and experience, they clearly are capable of doing so when provided with the information needed to make the best decisions. However, the fundamental question remains: what about patients? How much baseline knowledge is required by a patient to use medical information resources effectively and without distress? I use Uber all the time, and I know very little about how a satellite is launched or how a GPS works on a technical level. Despite this, I am very comfortable in my knowledge that after the input of my current and desired locations, I will arrive via the most direct route at a set price. Can we do the same in healthcare? This is a fundamental issue that holds the greatest promise to transform healthcare transparency and, hopefully, quality and affordability.

If every patient knew precisely where they were starting and what route of care would get them to their desired outcome at the lowest possible cost, we would have an Uber version of healthcare. Is this practicable? Will patients find this useful or frightening? Only time will tell.