The ongoing political discourse on the best care model, mergers and acquisitions forming unexpected pairings, and emerging and transforming companies tackling everything from health monitoring to gene testing make this is a uniquely exciting and challenging time for healthcare in the U.S. and around the world.
Of course, the growing use of digital technology in clinical practice is also a factor, adding pressure on practitioners and medical researchers and educators to remain agile and adopt new (or renewed) schools of thought.
In the case of precision medicine, more healthcare providers will soon have to adopt and train for this burgeoning treatment model, tailoring solutions with consideration for a patient’s genes, health choices and life circumstances. Considering the formidable government investment over the past few years, especially with the launch of NIH’s All of Us Research Program, precision medicine is being heralded as the next big thought-shift in modern medicine.
With this national effort to gather data from one million or more U.S. residents to accelerate research, an individual’s differences in lifestyle, environment, biology and other factors will be accounted for to improve treatment and health outcomes. Essentially, this combines genomics and analytics to create custom care regimens.
However, the tremendous volume of varied data generated by this merging of data science and bioscience creates a challenging opportunity for educators to design learning modules for optimal real-world application and outcomes.
So, how should academic institutions and clinical training programs prepare medical students and residents for this new era in healthcare?
First, we need to build clinicians’ competencies in analytical tools and cater to millennial learning styles through seamless integration of technologies into students’ learning environment, 24/7 access to digital libraries, and online simulations of clinical scenarios. Dissecting data quickly and accurately will be key to delivering insights for clinical advancement. The sheer volume of data will be meaningless and probably overwhelming if the technical expertise or appropriate tools are not in place to effectively unravel it.
Second, we need to coach students and interns on the markers of verified data sources and instruct them on how to distinguish between different data sets to extract evidence-based insights. Assessing and analyzing data is the new road to discovery. Clinicians will not only be tested on their ability to understand data but to configure data in different ways.
Third, we need to encourage clinicians to pressure-test theories gleaned from data among their peers and in real-world settings. Trial via team-based learning is the marker of success for data interpretation. While we are all tethered to our mobile devices, face-to-face and collaborative decision making and information sharing is still critical for effective patient care.
Fourth, we need to remind future practitioners about the other component of care: the non-digital, non-analytical bedside manner that patients crave and deserve. Authenticating precision medicine by keeping it as personal in practice as it is on paper (really, in digital form) enhances our intentions to provide more customized care through data analysis.
The above approach to address the skills gap for our next generation of clinicians is critical to scaling the delivery of precision medicine, especially amidst the looming shortage of clinicians in the U.S. But what an exciting time to be in healthcare and at the forefront of this revolutionary model of care.
Dr. John Danaher is President of Clinical Solutions at Elsevier, a global information analytics business that helps institutions and professionals advance healthcare, open science and improve performance for the benefit of humanity.