Healthcare is replete with data. But many in the industry believe they could make far better use of this vast information trove, encompassing everything from patients’ vital signs to laboratory data to statistical studies — especially given the powerful data analytics tools now available to them.
The Economist Intelligence Unit explored this issue in a recent survey of more than 600 companies globally. Nearly half (48 per cent) of the healthcare executives and board members who responded to the survey said they expect artificial intelligence (AI) and machine learning (ML) to play a significant role in their digital strategy three years from now — the most of any technology or practice — followed by augmented reality and virtual reality (38 per cent). And nearly one in three (32 per cent) expect that assessing and adopting new digital tools such as AI and blockchain will be one of the three most critical aspects of digital decision-making in the coming year.
Healthcare companies’ prioritisation of AI and ML is facilitating the rise of precision medicine, which aims to tailor medical treatment to each individual’s specific profile by employing digital analytic tools. In 2015 the U.S. federal government launched the Precision Medicine Initiative (renamed “All of Us” the following year), with an initial $215 million budget, which includes mapping the DNA of 1 million people using AI, researching genetic causes of cancer and evaluating new diagnostic drugs.
Precision medicine enables physicians to explore a wide range of data — including not just the standard information taken from patients but also molecular and genomic tests — and cross-reference it with the vast amounts of data that other physicians and medical institutions collect from other patients. They can then determine how susceptible their patient is to particular diseases and what their response might be to a particular treatment.
ML tools take the process a step further, as systems “learn” to create more accurate and effective diagnoses and treatments with the more data they receive and the more experience they accumulate analysing it.
“The goal is to surface different insights and connections we’re not trained to make and haven’t spotted in the past, and to do it more rapidly,” says Kristin Darby, former chief information officer at Cancer Treatment Centres of America (CTCA), which began implementing an ML platform and other precision medicine tools last year.
Developing new tools out of these technologies is an especially high priority for healthcare companies like CTCA. A third (33 per cent) of healthcare respondents in our survey cited improving research and development (R&D) as one of their top three business priorities compared with 25 per cent of respondents overall, while 42 per cent say they have digitally enabled R&D and innovation, compared with 35 per cent in the overall sample.
“Precision cancer medicine is accelerating our ability to bring basic research to our patients,” says Jeff Golden, chief of pathology at Brigham and Women’s Hospital, which, together with the Dana-Farber Cancer Institute, runs the DanaFarber/Brigham and Women’s Cancer Centre. “It also reverses the flow of information and completes the circle by bringing what we learn at the bedside right back to the laboratory to keep the process of discovery going.”
Fitting the patient profile
The goal is not to “automate” doctors’ and patients’ decision-making, says Ms. Darby, but to give them more accurate information about the patient’s condition, the population subset they belong to and the treatments that are most effective for that group. This enables doctor and patient to decide on a course of action that’s more precisely suited to the individual’s profile.
“If a patient has breast cancer and you Google ‘breast cancer,’ you’ll get a lot of information,” Ms. Darby notes, “but it’s different depending on whether the patient is in her 20s, 30s, 40s, etc.” Now, she says, it’s possible to focus even more precisely on factors that could make the difference between more or less effective treatment. Precision medicine will become even more critical, Ms. Darby says, because it enables physicians and nurses to more quickly absorb and act on the growing flood of data they record and work with.
“How do you stay current with the explosion of advancements in science and technology?” she asks. “The pace of learning is increasing at rates humans can’t consume. So, doctors have to rely on things being surfaced by a computer and develop a confidence level in the tools. The physician is still in the driver’s seat, but the tools are very different.”
Accomplishing all this costs money. While most industries we surveyed expect to increase their investment in digital transformation, healthcare companies’ commitment is especially dramatic.
Ninety-one per cent of healthcare respondents say they expect their investment in digital technologies to increase in the coming year. That’s partly because they are already seeing results from the investment; more than two-thirds (68 per cent) say their digital strategy has increased annual profitability over the past three years.
“A simpler, frictionless experience”
By forming a more personalised picture of the patient’s condition and treatment options, precision medicine dovetails with a parallel challenge to organisations like CTCA, Ms. Darby says: “to create a consistent user experience for our employees, and externally, a simpler, frictionless experience for our patients.”
This requires “bringing all the data from our legacy systems together so that we can create a seamless patient journey with an efficient evaluation process that doesn’t overwhelm anyone with complicated diagnoses and instead gives them better access to information in a timely manner.”
The most visible parts of these efforts are the technologies that support it from the patient side: for instance, smartphones that can track its user’s heart rate, let them know if their heart rate is too high or low, make an electrocardiogram of their heart, and collect and transmit this information to a physician, etc.
No one looks forward to a visit to the doctor, or the administrative steps involved, but such tools can make the patient journey much less onerous and time-consuming.
Cultural change = competitive advantage
Improving the patient journey requires a cultural shift, in addition to the investment in AI, ML and other technologies that precision requires.
“We need to educate our employees on what these technologies are and how they work and function,” says Ms. Darby. “Even respected physicians can take a couple of days to wrap their heads around the technologies and build a comfort level that enables them to improve options for their patients.”
In recruiting staff, she says, “we look for ‘physician champions’ from a digital perspective, who can help other physicians learn and adapt based on their experience.” The C-suite can help foster a culture of continuous learning by “creating and modelling standards throughout the organisation, where lower-level managers know what’s needed within each department.”
This concern for cultural fit helps explain why 39 per cent of healthcare respondents in our survey cited the lack of a tech-savvy workforce as a major barrier to implementing their digital strategy and 34 per cent mentioned internal cultural resistance: in both cases, a larger percentage than for the overall survey sample.
When providers learn to harness the data flood and the tools available for analysing it, they have an opportunity to gain a competitive advantage.
They are also better able to fulfil a fundamental goal of any healthcare organisation, Ms. Darby says: “better access to information, diagnosis and treatment in a timely manner.” As technologies like precision medicine continue to change the practice, adopting them will only become more urgent. “Change is already fairly dynamic,” Ms. Darby says. “Leaders who don’t embrace it will be in trouble.”