Artificial Intelligence (AI) is a set of technologies that includes automated systems capable of performing tasks that normally require human intelligence, such as visual perception, speech recognition, and decision-making. Consumerization is transforming the healthcare space with digital technologies, causing a fundamental shift in consumer behavior, demands, and preferences. This transition has changed the way consumers (patients) interact with healthcare providers, with digital standardizing healthcare experiences and consumer engagement. AI in healthcare can apply these systems to perform administrative or clinical functions, then completely augment human activity. In the US, healthcare organizations have yet to unlock AI’s full potential, even though the majority are open to leveraging its extensive capabilities. The opportunity is clearly realized and has been greatly measured.
As the report Healthcare in the Digital Age explained, “the dynamics of the healthcare industry are changing—with innovative digital solutions bringing about a shift from the curative care model to a more preventive care model.” It’s interesting to see how the industry has changed to meet the demands and expectations of today’s patients. Digital health tools that facilitate innovative methods and modalities to improve care, enable lifestyle change, and create efficiencies are progressing quickly. As patients (consumers) continue to adopt digital interactions, healthcare organizations are rapidly leveraging these technologies to improve care and the patient experience.
As healthcare organizations seek more customized, data-driven patient care, adopting technologies to promote digital engagement, data management, and workflow optimization is vital. Cloud platforms, along with data analytics and AI, can help organizations achieve these goals while also focusing on patient care and security. Artificial Intelligence (AI) and cognitive computing can empower patients, transform the practice of medicine, and save the health care industry over $150 billion by 2025. According to one report from Frost and Sullivan, AI could improve health outcomes by up to 40 percent and reduce treatment costs up to 50 percent by improving diagnosis, increasing access to care, and enabling precision medicine.
In short, AI enables greater accessibility, relevancy, and actionability of healthcare information. Healthcare providers may not treat a physical patient; instead, they may analyze and treat data in the future. Recent innovations will create lasting improvements in healthcare accessibility. As research on AI and other digital health tools continues, documenting real-world outcomes, measured economically and clinically, is necessary.
Already playing a critical role in other industries, AI systems are poised to transform how we think about disease diagnosis and treatment. Augmenting the expertise of trained clinicians, AI systems will provide an added layer of decision support capable of helping mitigate oversights or errors in care administration.”
Harpreet Singh Buttar, Frost & Sullivan Transformational Health Industry Analyst
Solving Challenges in Healthcare
AI has a broad reach and can amplify the impact of care by integrating health data across platforms. The 2020 Accenture healthcare AI report found that essential clinical AI applications could create $150 billion in annual savings for the US healthcare economy by 2026. This potential for cost savings is one reason healthcare organizations will continue to invest in digital solutions to deliver new sources of value over the foreseeable future, whether to lower the cost of care, improve labor productivity, enable better patient/customer experiences, or achieve other desired outcomes.
AI is getting increasingly sophisticated at doing what humans do, but more efficiently, more quickly, and at a lower cost. Building off of the Accenture AI report, growth in the AI health market is expected to reach $6.6. billion by 2021, with the market growing more than 10x by 2025. Patients/consumers also want AI, which raises data security questions and concerns. Organizations within the digital health/AI ecosystem will need to work together ethically and securely to manage critical patient information.
Most healthcare organizations agree that AI and machine learning will affect the future of work; therefore, they have an opportunity to employ AI to make a systematic shift that affects every process, piece of data, healthcare professional, and patient. While investments and adoption are expected to grow exponentially, organizations must understand the full financial, systemic, and organizational value AI delivers.
AI can help prevent medical mistakes and flag those most at risk for problems. In the January 2020 issue of the scientific journal Nature, researchers found that using AI technology reduced false positives and false negatives in breast cancer diagnosis. Through reduced labor costs alone, AI represents a notable opportunity for organizations better to control their bottom line in new payment models while capitalizing on new growth potential.
Several surveys conducted in 2019 found that the ability to improve or assist in the accuracy of diagnoses and clinical outcomes is the greatest impact AI will have on patient care in the short term. This same survey also found that of those organizations that have yet to adopt AI, cost remains the most significant obstacle in implementation—followed by a lack of strategic direction” within their organization.
While many American healthcare professionals are not currently using AI, many would feel comfortable using it across a range of areas, suggesting a general openness to unlocking AI’s full potential in the future. As these and other AI applications gain more experience in the field, their ability to learn and act will continually improve precision, efficiency, and outcomes.
The Path Forward
With much of health and health care moving onto digital platforms, there has been remarkable growth in the amount of information generated. As the conversation on the potential wonders of AI becomes more mainstream, it is easy for misguided fears and optimism to hide its legitimate near-term possibilities. The purpose is to build competency in AI and data science to the point that health care AI presents an assistive benefit to humans rather than replacing them. And, of course, the need for privacy and the handling of large amounts of data remain challenges for AI in healthcare.
Mistaken fears and reporting aren’t the only limitations to AI adoption; low healthcare system literacy is a key barrier for any new technology or service model. This is notably true in the US, where reports find that over half of the American population ranks low in healthcare system literacy, causing an estimated $4.8 billion annual organizational cost burden for payers. Our next article will cover the role digital health technologies can play in improving healthcare system literacy, also known as the social determinants of health.
