The artificial intelligence (AI) market in health care is projected to grow at an annual rate of more than 50 percent between now and 2025 — bringing total spending in the sector from $2.1 billion in 2018 to $36.1 billion in 2025. The forecast from ReportLinker
, a technology company that supplies analysts and decision-makers with industry data, says hospitals and physician groups will account for most of the spending as they apply AI solutions across their organizations. Moreover, AI-based tools like voice recognition software and clinical decision-support systems will help streamline workflow processes in hospitals, lower costs, improve care delivery and enhance the patient experience, the report notes.
What’s Fueling the Growth?
The potential of AI to improve outcomes, streamline operations and cut costs have intrigued many with a stake in health care. And while data-privacy concerns and questions about just how much human oversight will be required to effectively implement AI have tamped down some short-term clinical expectations for the technology, many believe long-term prospects are bright. A Forbes report last summer highlighted five AI advances that appear to have the most potential, including AI-assisted robotic surgery, virtual nursing assistants, image analysis, workflow and administrative tasks, and aiding in clinical judgment or diagnosis. AI applications continue to expand. Duke University Hospital in December launched Sepsis Watch
, an AI-based system that identifies early sepsis cases and alerts nurses on the hospital’s rapid-response team. El Camino Hospital in California used AI technology to predict the likelihood of patient falls based on risk factors and merged the data with real-time tracking of patients. The result: a 39 percent drop in the rate of dangerous falls. If the potential costs of AI seem staggering, so too are the potential rewards. A report from Accenture
estimates that AI applications in health care could save up to $150 billion annually for the U.S. health care economy by 2026.
Of course, achieving this level of savings won’t be easy. As a recent Health Affairs report on implementing and scaling AI solutions
noted, health care leaders face an AI knowledge gap that may not be easy to bridge. “Many advances in AI solutions are being piloted and implemented by private-sector entrepreneurs and health organizations, rather than academic centers or researchers committed to publishing findings in widely available periodicals,” the report states. With this in mind, the report advises organizations to keep in mind these three AI considerations:
- Entry costs can be low. Pattern-recognition AI solutions, in particular, are affordable and are sometimes embedded and available in a modular fashion as part of larger software solutions. It has been estimated that $18 billion could be saved across health care by applying AI solutions to eliminate such administrative processes as automating chart notes, prescribing medications and ordering tests.
- Implementation may not translate easily across different AI solutions. Implementing more intricate AI applications in areas like clinical care support or population-health processes requires more elaborate and expensive solutions.
- Sustaining enterprisewide impact requires a long-term view. Scaling AI solutions and sustaining broad organizational impact across applications and use cases requires significant, sustained leadership focus and investment. And this requires investments in people, including data scientists, and technology.
Have an AI success story about your organization to share? Contact Lindsey Dunn Burgstahler email@example.com.