March 15, 2021
Artificial intelligence has long been seen as the next step forward for organizations in a variety of industries. It’s already being used to deliver smarter consumer targeting, a better customer experience, and more efficient operations in a variety of businesses all across the globe.
This trend has not gone unnoticed in healthcare. Providers have already seen how AI can help improve administrative tasks, such as enabling smarter self-service options for patients, managing electronic health record alerts, and streamlining claims billing. COVID-19 has also helped accelerate interest in how AI can be used to support remote monitoring and triage. Startups, meanwhile, have created products that find personalized baselines in patient vital signs, detect and monitor cardiovascular disease, and monitor vital signs through smartphones and other consumer hardware.
As promising as all this is, however, it’s only the tip of the iceberg when it comes to harnessing the power of AI for innovation in healthcare.
To truly see the value of AI recognized, it’s crucial that real-world practitioners guide the implementation of AI from the ground up. A successful innovation strategy in healthcare has to be about creating value. In addition, many organizations place bets on technology-enabled innovation and throwing dollars at it without having the underlying culture to support successful initiatives.
With that in mind, these are the main areas in which AI has the potential to revolutionize healthcare — with the right strategic guidance:
When it comes to detecting a disease or recognizing a change in someone already diagnosed, time can play a key role in the success or failure of treatment. AI can help significantly shorten that timeline. Machine learning has already shown potential in the early detection of various diseases, including breast cancer, Alzheimer’s, and, most recently, COVID-19. Using a variety of publicly available data from social media, news, and government reports, AI can even help detect early signs of an epidemic.
Not only is chronic disease the foremost cause of death and infirmity in the U.S., but it also makes up the majority of the country’s $3.5 trillion in healthcare spending. Machine learning can make this process more efficient by helping to analyze data, guiding experts to smarter treatment decisions. Combine this with data crowdsourcing, and you have a much greater insight into how particular diseases tend to behave and respond to specific treatments in different types of patients.
It’s estimated that 14% of wasted spend is a result of inefficient administrative practices. While it might not sound as exciting as early detection and smarter treatment, the streamlining of administrative tasks — especially those that directly involve the patient — can make a huge difference in the quality and cost of care. Take something as seemingly mundane as handling faxes. Every year, healthcare providers receive approximately 120 million faxes. With the help of AI, they can use optical character recognition to read what the fax contains and then glean insights from the content.
Successful integration of AI into healthcare won’t happen overnight. It’ll take careful planning and an understanding of what you want to accomplish before you can put anything into action. With the right leadership, this technology has the potential to help the industry achieve the triple aim of improving the patient experience of care, improving the health of populations, and reducing the per-capita cost of healthcare.
Eric Schaefer is the Vice President of Healthcare Innovation at Coplex, a startup studio focused on developing new healthcare ventures with corporate partners. He’s responsible for developing partnerships with corporations and healthcare industry experts to identify healthcare startup ideas and works with the Coplex team to validate and pilot these concepts. Eric has years of experience working with healthcare providers in both strategic and business roles.
Arash Tadayon, former VP of Technology at Coplex.
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