Could artificial intelligence transform healthcare?
Insights from Morgan Stanley Research05/28/21
Summary: MedTech’s adoption of artificial intelligence could deliver increased productivity, lower costs, and improved patient outcomes in the coming years. We explore what investors should consider in this industry.
Scenario: A patient suffers from abdominal pain, along with symptoms in atypical locations, which makes diagnosis tricky. An astute examination reveals the cause: an unusual form of appendicitis. However, credit doesn’t go to the radiologist. Instead, an imagery machine built with artificial intelligence technology, which can draw on knowledge of tens of millions of similar scans, recognizes the anomaly and makes the diagnosis.
That scenario is no longer the stuff of science fiction. Pressed to reduce costs, boost productivity, and drive growth across the healthcare value chain, medical equipment manufacturers and technology companies are increasingly investing in AI.
Medical technology, or MedTech, offers fertile ground for a range of AI applications. “Based on our analysis of AI capabilities, as well as discussions with executives and industry experts, we’re seeing a number of applications across the entire healthcare spectrum, from prevention to diagnosis to follow up,” says Michael Jungling, head of Morgan Stanley Research’s Medical Tech and Services team.
Morgan Stanley estimates that the global market for AI in healthcare could surge from $1.3 billion today to $10 billion by 2024, growing at an annual compound rate of 40%. For investors, large MedTech companies and equipment providers, as well as AI tech providers and emerging startup disruptors could all present opportunities.
Applications of AI in healthcare
Relatively modest deployments of AI, such as assistive intelligence, can reduce repetitive tasks like appointment scheduling, leaving skilled medical staff with more time for specialized and revenue-generating work.
More advanced AI aims to mimic human cognitive processes through machine learning, where a model is trained on a data set—such as the intestinal scans of millions of patients noted above—to improve diagnostics.
AI could eventually perform such diagnostics without user input, dramatically increasing productivity in clinical settings where specialist resources are limited. But such scenarios remain far down the road. “The timelines for adoption of AI-enabled MedTech will likely be determined by the tangible economic benefits produced by the product and the ease of usability and integration into existing workflows,” Jungling says.
Which areas and applications show the best promise for AI? Diagnostic imaging, radiation therapy, and large hospital equipment may offer the most significant prospects for fueling industry growth and profitability in the short-term, according to Morgan Stanley Research. Deploying AI in these areas could lower costs and improve productivity for hospitals and would be easy to use, with little training necessary.
Though AI applications may make sense for some specialties, they won't be a cure-all. Specialties like corrective lenses, chronic care, or orthopedics may present more challenging environments for AI, and some fields may not offer sufficient profitability or cost savings. Other potential barriers include the plausibility of the technology and regulatory approval for use in medical settings, as well as anonymizing patient data to ensure individual privacy within large data pools.
Which players are best positioned to potentially benefit from AI in the MedTech space? Traditional medical-equipment providers have an advantage in the quest to enable MedTech AI, simply because they are already in hospitals everywhere.
But they still need to determine how to charge for AI integration. Options include bundling AI tech with existing offerings, selling licenses, charging per use, or offering subscription models.
The possibility of disruption from tech-industry giants also looms. In some specialties, traditional providers could face competition from tech companies that could use AI to deliver healthcare services using new or nontraditional methods, like monitoring equipment and smartphone apps.
Those who are looking for investing opportunities in health care technology may look to mutual funds or exchange-traded funds (ETFs) focused on MedTech or artificial intelligence.
ETFs and mutual funds are both collections, or “baskets,” of individual stocks, bonds, or other assets—in some cases hundreds of them—all pooled together. When you buy a share of the fund, you own a small piece of this basket of assets. ETFs and mutual funds are similar in that they give you a broad range of investment choices and inherently offer greater diversification than buying a single stock. That said, there are distinct differences in these investment choices. ETFs can be bought and sold throughout the trading day, tend to have lower fees, and are typically passively managed—mirroring the performance of an index. On the other hand, mutual funds trade once a day, typically have higher expense ratios, and are managed by professional fund managers who actively try to outperform a market or index. To learn more about the distinctions between mutual funds and ETFs, check out ETFs vs. mutual funds: Understand the difference.
Bottom line: With rapid growth in AI-driven healthcare applications expected, MedTech equipment providers, AI tech providers, and emerging startup disruptors could all present strong investment opportunities. Investors can get exposure to this market in a variety of ways, including ETFs, stocks, and mutual funds.
The source of this Morgan Stanley article, Could Artificial Intelligence Transform Healthcare?, was originally published on February 26, 2019.
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