Solutions based on artificial intelligence (AI) are becoming more prevalent as healthcare organizations begin to realize and explore the technology’s ability to transform the industry. From faster diagnoses, to helping doctors create tailored treatment plans, AI is quickly revolutionizing the provider, payer, and patient experience.
As AI continues to rise, there are two key trends enabling its growth. Unprecedented amounts of collected data—data being a critical enabler of AI—is paving the way for digital transformation while advances in computing technology have made it possible for enterprises to deploy these solutions.
Incorporating AI is a journey that any organization can take. As organizations look to capitalize on larger polystructured data sets to uncover new insights, AI is being used to greatly speed up or automate these processes. A common AI starting point is the application of machine-learning-based predictive models to clinical-, operational-, or financial-use cases. According to Forrester 86% of healthcare organizations are using or are planning to use predictive analytics within the next 12 months. Intel recently collaborated with Sharp HealthCare to build a model to predict which patients are at risk of sudden decline with 80% accuracy. The model can anticipate whether a Rapid Response Team (RRT) will be needed in the next hour, enabling Sharp to intelligently place medical emergency teams at key locations in the hospital to intervene before incidents become life threatening.
As AI technology advances, there will be more robust applications of AI, such as cognitive computing that combines predictive analytics with evidence-based guidelines to help inform next-best action for clinical decision support. At the core of these solutions is the growth of data being collected by healthcare organizations as they digitally transform. In the next 10 years, the potential for AI will only increase as more data becomes available and AI technologies continue to advance. Continuing collaborations among stakeholders in the healthcare ecosystem will tackle increasingly difficult challenges around cost, quality and access to care.
However, before any of the benefits of AI in the healthcare industry can be reaped, there are clear barriers to adoption. For example, many healthcare organizations use legacy systems that often can’t support newer technologies. Additionally, with AI’s dependence on data, it will be vital to bolster growing data collection and along the way, break down any organizational silos that hinder its flow. With the rise of big data will come the need for greater workforce transformation and the development of new skill sets to leverage analytical methods. While the existing workforce is well trained on traditional methods, such as regression, significant investments will be required to retrain existing staff on newer methods.
Other barriers that healthcare executives must overcome include the seamless integration of analytics into the clinical and operational workflow so that it naturally supports everyday activities. In order to do this, organizations will need to evolve their management capabilities to include strategies for driving organizational adoption of AI solutions.
Those organizations that have overcome barriers are seeing the benefits of AI and the potential for future applications. For example, Saffron, a pioneering AI company acquired by Intel, and West Virginia University Heart and Vascular Institute are using machine learning to discern between serious heart conditions with very similar symptoms, which have long vexed even experienced cardiologists. Using Saffron’s National Intelligence Platform, as well as associative memory classification, we reached a 90% accuracy rate in diagnosing constrictive pericarditis and cardiomyopathy. The insights gained from AI illustrate that, rather than functioning as a replacement for doctors, AI is a powerful tool that helps deliver more cost-effective care.
AI has unimaginable potential, and its benefits to all parties are enormous when implemented strategically. The technology is already disrupting multiple industries and powering innovations across everyday life. Healthcare leaders must take steps to not only prepare for potential disruption, but also use the technology to advance the industry. AI/technology companies and healthcare organizations will need to collaborate to develop solutions that meet their unique needs and help improve the standard of care. If we do, we’ll help to jumpstart enormous change that will shape the future of the healthcare industry for years to come.