AI in Healthcare: Applications and Market Overview
The US Centers for Medicare & Medicaid Services reports that in 2021, healthcare spending accounted for 18.3 percent of the nation’s gross domestic product (GDP), reaching $4.3 trillion or $12,914 per person. Arcadia Solutions reveals that, even more impressively, approximately 30 percent of the world’s data volume is generated by the healthcare industry, a figure that should reach 36 percent by 2025. Alarmingly, Arcadia found that less than 60 percent of healthcare organizations’ data is being used to make intelligent business decisions. With healthcare as both a huge economic market and a huge data generator, the application of artificial intelligence to healthcare administration and practice is both essential and inevitable. To remain productive and competitive, leaders in the healthcare sector must proceed – with appropriate care and caution – to incorporate artificial intelligence and machine learning into their operations.
Introduction
The US Centers for Medicare & Medicaid Services reports that in 2021, healthcare spending accounted for 18.3 percent of the nation’s gross domestic product (GDP), reaching $4.3 trillion or $12,914 per person.
Even more impressively, perhaps, Arcadia Solutions reveals that “Approximately 30 percent of the world’s data volume is generated by the healthcare industry,” a figure which should “reach 36 percent by 2025.”
Alarmingly, Arcadia “found that less than 60 percent of healthcare organizations’ data is being used to make intelligent business decisions.”
Considering the importance of artificial intelligence to today’s enterprise, Arcadia discovered that:
- “Nearly 30 percent of healthcare leaders said they’ve already implemented AI”
- “Roughly 60 percent planning to implement such technology in the next 12-24 months or more”
Remarkably, “A small percentage (13 percent) don’t plan to implement AI at all.”1
With healthcare as both a huge economic market and a huge data generator, the application of artificial intelligence to healthcare administration and practice is both essential and inevitable.
To remain productive and competitive, leaders in the healthcare sector must proceed – with appropriate care and caution – to incorporate artificial intelligence and machine learning into their operations.
Market
“While AI may not replace clinical decision-making, it could improve decisions made by clinicians. In settings with limited resources, AI could be used to conduct screening and evaluation if insufficient medical expertise is available, a common challenge in many resource-poor settings. Yet, whether AI can advance beyond narrow tasks depends on numerous factors beyond the state of AI science and on the trust of providers, patients and health-care professionals in AI-based technologies.” – World Health Organization2
As forecast by MarketsandMarkets, AI in the healthcare market should expand from $14.6 billion in 2023 to $102.7 billion by 2028, reflecting a robust, but realistic, compound annual growth rate (CAGR) of 47.6 percent.3
Offering a similarly optimistic projection, Statista, which valued AI in healthcare at $11 billion in 2021, expects a mammoth rise to $187 billion by 2030.4
Elder Care
Among its many use cases, MarketsandMarkets believes that AI offers significant opportunities to enhance elder care. “With the growth of the geriatric population, the incidence of various age-related diseases is expected to increase worldwide. AI … provides enhanced services, such as real-time patient data collection and monitoring for emergency care, as well as [offering] preventive healthcare recommendations.”5
Public Acceptance
Among the AI in healthcare advocates, the biggest concern is public acceptance, as some patients will view AI as another vehicle for separating them from their primary care physician. First, it was HMOs, then nurse practitioners, then telemedicine, and now it’s AI. Tellingly, a new Pew Research Center survey shows “There is wide concern about AI’s potential impact on the personal connection between a patient and health care provider:
- “57 percent say the use of artificial intelligence to do things like diagnose disease and recommend treatments would make the patient-provider relationship worse.
- “Only 13 percent say it would be better.”
While more Americans than not believe that AI will help reduce healthcare mistakes, along with racial and ethnic bias, they are, nonetheless, concerned about the pace of AI adoption.
“Though Americans can identify a mix of pros and cons regarding the use of AI in health and medicine, caution remains a dominant theme in public views. Three-quarters of Americans say their greater concern is that health care providers will move too fast implementing AI in health and medicine before fully understanding the risks for patients; far fewer (23 percent) say they are more concerned that providers will move too slowly, missing opportunities to improve patients’ health.”6
Applications
As with other enterprise sectors, artificial intelligence is helping revolutionize healthcare delivery, lowering costs and improving patient outcomes. Prominent AI applications include:
Healthcare Administration
As analyst Shannon Flynn observes, “Administrative expenses are estimated to comprise 15 percent to 25 percent of total healthcare costs. Tools to improve and streamline administration are valuable for insurers, payers, and providers alike.”7
To illustrate, McKinsey & Company recently reported on a new generative AI tool, enabled by GPT-4, that greatly facilitates physician record-keeping.
“Here’s how it works: a clinician records a patient visit using the AI platform’s mobile app. The platform adds the patient’s information in real time, identifying any gaps and prompting the clinician to fill them in, effectively turning the dictation into a structured note with conversational language. Once the visit ends, the clinician reviews, on a computer, the AI-generated notes, which [can be edited] by voice or by typing, and submits them to the patient’s electronic health record (EHR). That near-instantaneous process makes the manual and time-consuming note-taking and administrative work that a clinician must complete for every patient interaction look archaic by comparison.”8
Patient Engagement
After a patient leaves a doctor’s office, clinic, or hospital, doctor-patient communication can end, which can lead to a sudden deterioration in a patient’s health. AI can help prevent or mitigate any adverse effects by maintaining the healthcare dialogue. As analyst Shannon Flynn reports:
“Hospitals use AI chatbots to check in with patients and help them get necessary information faster. When Northwell Health implemented patient chats, there was a 94 percent engagement rate among those utilizing oncology services. Clinicians who tried the tool agreed it extended the care they delivered. Chatbots also reduce challenges patients may encounter while seeking care. People can use them to find hospitals or clinics, book appointments and describe needs.
“Estimates suggest that as many as half of all patients don’t take medications as prescribed. However, AI can increase the chances of patients taking their medications as they should. Some platforms use smart algorithms to suggest when health professionals should engage with patients about compliance and through which channels. Medication reminder chatbots exist, too. In a recent example, researchers collaborated and used AI to assist with finding the best medications for people with Type 2 diabetes. The algorithms helped choose the right options for more than 83 percent of patients, even in cases where the people needed more than one medication simultaneously.”9
Disease Diagnostics
IBM reports that according to Harvard’s School of Public Health, using AI to make diagnoses may:
- Reduce treatment costs by up to 50 percent, and
- Improve health outcomes by 40 percent.10
Among early successes, AI has been instrumental in:
- Predicting breast cancer risks, and
- Detecting mental ailments, using “algorithms to identify depressed people by listening to their voices or scanning their social media feeds, for example.11
Robotic Surgery
Robotic Surgical System Performing a Stomach Operation
Source: Defense Visual Information Distribution Service
Dr. Joseph Nathan asserts that AI can “redefine” surgical care, adding that “two-thirds of the global population – roughly 5 billion people – don’t have proper access to surgical treatment.” Among the opportunities:
“AI can ensure that more physicians have access to learning opportunities from the best models in their field and thus support a larger number of medical professionals in performing surgeries. Regardless of where they are based in the world or what resources they have access to, surgeons can learn from and utilize AI-based surgical robotics to reach a wider patient population. Expanding their sub-specialties, surgeons who today only perform one type of procedure can potentially broaden their impact by having a new tool to address a wider variety of sub-specialties.
“Artificial intelligence goes hand in hand with robotic surgery. Integrating AI-based systems into medical technology is crucial to improve both the surgeons’ and patients’ experiences. By empowering physicians in every step of their career and elevating level of care, AI can reshape surgical robotics, launch the healthcare industry to new heights and ultimately serve as a gateway to automated care.”12
Medical Research
According to the New England Journal of Medicine, “Tools that utilize AI have come into increasing use in analyzing and interpreting large research databases containing information ranging from laboratory findings to clinical data. All these tools offer the potential for increased efficiency and may, perhaps, render insights that are difficult to attain with more traditional data-analysis methods.”
The Journal warns, however, that “new AI methods are not necessarily a panacea:
- “They can be brittle;
- “They may work only in a narrow domain: and
- “They can have built-in biases that [disproportionately] affect marginalized groups.”13
Governance
While controlling – in fact, regulating – artificial intelligence is a major public policy issue, especially as AI experts have commented on the risks, including the existential risks of general AI, the issue of AI governance is particularly pertinent as it applies to human health and safety. Understanding the urgency of acting now, before AI in Healthcare became even more entrenched in healthcare providers’ business models, in 2021, the World Health Organization (WHO) articulated six “key ethical principles for use of artificial intelligence for health.”
Protect Autonomy
“AI systems should be designed demonstrably and systematically to conform to the principles and human rights with which they cohere; more specifically, they should be designed to assist humans, whether they be medical providers or patients, in making informed decisions.”
Promote Human Well-Being, Human Safety and the Public Interest
“AI technologies should not harm people. They should satisfy regulatory requirements for safety, accuracy and efficacy before deployment, and measures should be in place to ensure quality control and quality improvement.”
Ensure Transparency, Explainability and Intelligibility
“AI should be intelligible or understandable to developers, users and regulators. Two broad approaches to ensuring intelligibility are improving the transparency and explainability of AI technology.”
Foster Responsibility and Accountability
“Responsibility can be assured by application of “human warranty,” which implies evaluation by patients and clinicians in the development and deployment of AI technologies. When something does go wrong in [the] application of an AI technology, there should be accountability. Appropriate mechanisms should be adopted to ensure questioning by and redress for individuals and groups adversely affected by algorithmically informed decisions.”
Ensure Inclusiveness and Equity
“Inclusiveness requires that AI used in health care is designed to encourage the widest possible … equitable use and access, irrespective of age, gender, income, ability or other characteristics.”
Promote Artificial Intelligence That Is Responsive and Sustainable
“Responsiveness requires that designers, developers and users continuously, systematically and transparently examine an AI technology to determine whether it is responding adequately, appropriately and according to communicated expectations and requirements in the context in which it is used. Responsiveness also requires that AI technologies be consistent with wider efforts to promote health systems and environmental and workplace sustainability. AI technologies should be introduced only if they can be fully integrated and sustained in the health-care system.”14
For their part, healthcare providers should develop their own ethical regimen, combining the WHO principles with coming:
Local, state, and federal AI laws, regulations, and guidelines.
Any relevant national or international standards [as developed, for example, by the International Organization for Standardization (ISO) or the US National Institute of Standards and Technology (NIST)].
Any sector-specific strictures [as developed, for example, by the American Medical Association (AMA), which has created a framework for development and use of AI].
Web Links
References
1. "Report: Only 57% of Healthcare Organizations’ Data Is Used to Make Decisions." Arcadia Solutions, LLC | Cision US Inc. August 9, 2023.
2. "Ethics and Governance of Artificial IntelligeHnce for ealth: WHO Guidance." World Health Organization. 2021:15.
3. "Artificial Intelligence in Healthcare Market by Offering (Hardware, Software, Services), Technology (Machine Learning, NLP, Context-aware Computing, Computer Vision), Application, End User and Region – Global Forecast to 2028." MarketsandMarkets.
4. "The Benefits of AI in Healthcare." IBM Education | IBM Corporation. July 11, 2023.
5. "Artificial Intelligence in Healthcare Market by Offering (Hardware, Software, Services), Technology (Machine Learning, NLP, Context-aware Computing, Computer Vision), Application, End User and Region – Global Forecast to 2028." MarketsandMarkets.
6. Alec Tyson, Giancarlo Pasquini, Alison Spencer, and Cary Funk. "60% of Americans Would Be Uncomfortable with Provider Relying on AI in Their Own Health Care." Pew Research Center. February 22, 2023.
7. Shannon Flynn. "10 Top Artificial Intelligence (AI) Applications in Healthcare." VentureBeat. September 30, 2022.
8. Shashank Bhasker, Damien Bruce, Jessica Lamb, and George Stein. "Tackling Healthcare’s Biggest Burdens with Generative AI." McKinsey & Company. July 10, 2023.
9. Shannon Flynn. "10 Top Artificial Intelligence (AI) Applications in Healthcare." VentureBeat. September 30, 2022.
10. "The Benefits of AI in Healthcare." IBM Education | IBM Corporation. July 11, 2023.
11. Shannon Flynn. "10 Top Artificial Intelligence (AI) Applications in Healthcare." VentureBeat. September 30, 2022.
12. Dr. Joseph Nathan. "Four Ways Artificial Intelligence Can Benefit Robotic Surgery." Forbes.com. February 15, 2023.
13. Andrew L. Beam, Ph.D., Jeffrey M. Drazen, M.D., Isaac S. Kohane, M.D., Ph.D., Tze-Yun Leong, Ph.D., Arjun K. Manrai, Ph.D., and Eric J. Rubin, M.D., Ph.D. "Artificial Intelligence in Medicine." The New England Journal of Medicine | Massachusetts Medical Society. 2023.
14. "Ethics and Governance of Artificial Intelligence for Health: WHO Guidance." World Health Organization.