The Future of Healthcare

This week I read an interesting article on the future of medicine. This has always been something of interest to me, not least because it determines the sort of workplace that I hope to be stepping into. A future where medicine will be a team sport, with humans and machines working together, and consumers playing an important role seems a very positive one to me. To prepare for this future, healthcare and medical leaders should shift the focus of both training, and the definition of physicians’ work: from an ability to memorize and quickly retrieve complex scientific information to even greater empathy and cultural competence; from autonomous decision-making to being team players and team leaders; from sick care to well-being and prevention; from periodic continuing medical education seminars to lifelong learning, enabled and supported by their organizations. To set priorities for physician workforce development, organizations could zoom out to envision themselves 10 years from now, considering where they want to be. Then, leaders can zoom in to identify some key initiatives that they can undertake in the near future, to solve short-term problems in a way that can accelerate the progress toward a long-term vision.

Over the past few months, physicians have been at the forefront of patient care, making challenging decisions under enormous stress and personal risk. The article that I read, gathered its information from interviews conducted with American physicians, who seemed to have an optimistic outlook on technological and scientific advances in medicine. They believe technology and new models of care can augment, not replace, physicians and help them focus on meaningful work.

As the Fourth Industrial Revolution (a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres. It is marked by technological breakthroughs in robotics, AI, nanotechnology, quantum computing, fifth-generation wireless technologies, 3D printing, and material science) takes hold, technological and scientific advances—such as artificial intelligence, robotics, data visualization, and genomics—can transform the practice of medicine in positive ways. For example, technology can:

  • Automate mundane tasks such as clinical documentation, patient scheduling etc..
  • Consolidate and analyse data from multiple sources.
  • Provide clinical decision support for diagnosis and treatment in line with the most up-to-date research and evidence base.
  • Help physicians deliver personalised concierge-like care that focuses on prevention, providing actionable recommendations to support patients’ well-being (holistic care) and to delay and even avert disease.

The physicians interviewed believe that big changes are coming to the practice of medicine. Furthermore, they believe that the composition of clinical teams is expected to evolve. Physicians estimate that 30% of their current work can be performed by nonphysicians and 18% can be automated. In addition, the role of the consumer is expected to change: Consumers will own their health data and control who can access this information. They will assume greater ownership in their care and become an important part of the care team. In fact, 65% of physicians expect that in 5–10 years, it will be standard practice for consumers to own and control their health data. Collectively, these changes can improve outcomes, increase physician productivity, and optimally allocate resources, but most importantly, they can improve work for physicians, freeing them from rote tasks, restoring the humanity in patient care.

In the future, there will be a shift in the skills required of physicians, but will this look like? This article suggests that the following will be important:

  • Empathy, cultural competence (knowing how to deal with people of different cultural backgrounds), and storytelling to get at motivational levers for patients. As our patient population and health care workforce get increasingly diverse, physicians should be able to connect with patients and colleagues of different cultural backgrounds, and often do so using remote rather than face-to-face modalities.
  • Leadership and influencing capabilities to be an effective team leader and team player might be required for physicians in leadership positions and in everyday clinical practice.
  • The ability to accurately interpret genetic information, even if aided by AI, might be required not only for clinical decision-making around treatment but also for prevention and preserving well-being.
  • The ability to look under the hood and understand the algorithms behind clinical decision support systems, so that physicians can critically assess weaknesses in software and research results.
  • Better knowledge base on prevention, which would include a deeper understanding of diet and nutrition, the interplay between clinical and nonclinical drivers of health, ability to integrate information across body systems, and think more holistically about physical, mental, and spiritual well-being.
  • The business and economics of medicine, which involves understanding of cost and revenue drivers, direct and indirect costs from the perspective of the organization, the patient, and the health care system. This can better equip physicians to apply a population health lens, something that many find difficult today.

Surveyed physicians believe that for the next generation of physicians understanding the business of medicine and a focus on prevention will be important

In the future, this article suggested that physicians can forget the cumbersome and archaic acts of having to document what they do, as technology will record, filter, and edit everything needed for documenting an encounter. Furthermore, they think that many routine activities (medication refills, diagnosis of acute illnesses, or even dose titration) will move to self-service. Lastly, they thought that technology would be able to relieve physicians from having to remember differential diagnoses and trying to sort therapeutic options based on limited data the human brain can store. This can create opportunities for physicians to focus more of their energy on patient care—restore the humanity of physician work and allow more time with the patient. Even if all AI is doing is guiding physicians through a decision tree, that reduces the cognitive burden so physicians can use the cognitive bandwidth for all the other important things: empathy, asking intuitive questions, connecting the dots. AI gives physicians superpowers through computational and visualization infrastructure.

Like today, they suggest that consumers will turn to physicians with issues that cannot be resolved through other means, at times when they are vulnerable and confused. And physicians’ role will be to help them navigate complex decisions about treatments and consequences, using critical thinking, intuition, and compassion to ask the right questions, identify tradeoffs, and offer comfort.

Dealing with clinical as well as social and psychological barriers to health—hard topics such as end of life conversations, why patients don’t take their drugs, or why they choose not to vaccinate—may require a renewed focus on relationship-oriented capabilities. Just giving people information does not address the concerns, nor does it get at the issues that bother them or lie at the root of their problem. For example, in an encounter with a person who opposes vaccination, what levers can a physician pull to get through? Is it fear of the government? Do the parents believe vaccines make their child’s body dirty? Or is it because no one else in their community vaccinates?

As family history is augmented with genomic data, care may become proactive and personalised. Consequently, the information about risks and probabilities that physicians must explain to patients and parents will be vastly greater than today, and knowledge of genetics will be routinely incorporated in medical decision-making just like weight, activity level, and LDL cholesterol. At the same time, use of clinical decision support algorithms can give rise to questions about medical liability (similar to the classic driveless care question, of who gets the blame when it crashes) and this amplifies the need for a deeper skill set around probability, uncertainty, clinical decision-making, and basics of computer science. I think that when a health system uses a predictive algorithm about a patient, as a physician you are legally accountable, whether it’s used accurately or not.

Here is an example that they gave of how personalised medicine might work in the future:

“Jim had his genome sequenced at birth and it became part of his medical record. At age 16, new research indicated that a specific combination of genes that Jim had was associated with a particularly high risk of colon cancer. A genetic virtual assistant alerted Jim’s doctor to this fact and provided updated clinical guidelines for patients such as Jim. Because Jim’s genetic risk came through the maternal side, his doctor set up a meeting with Jim and his mother to explain the new research and guidelines to begin regular colorectal screenings at age 35 and offered personalized nutritional recommendations.”

The amount of data to inform wellness-oriented care will continue to grow. In addition to motion tracking, sleep monitoring, and data from clinical information systems, health data could include DNA and microbiome analyses, as well as data trails from purchasing decisions, consumption patterns, voice searches on smart speakers, or even keystrokes (that might be indicative of early dementia or neurological concerns). This would be amazing, because imagine a gastroenterologist or endocrinologist who manages the issues in the right way at the right time working hard upstream, preventing consequences from particular issues so the patient does not need bariatric or heart surgery down the line.

So, healthcare leaders need to begin to ‘zoom-out’ and then ‘zoom-in’ to begin to prepare for the future. Furthermore, they need to begin teaching relationship-oriented, and hiring based on these skills, which can be targeted interview feedback, online assessments, or even more advanced programs that use technologies such as AI or VR.

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