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We surround ourselves with technology that is able to help us in our daily lives. The success of autonomous cars,...
advancements in clinical research and personal digital assistants has shown the incredible potential of technology and how far it has come in recent decades. Despite the progress that many other industries have made, healthcare is likely to be the one market where AI can truly have an impact that goes beyond convenience and positively affects human lives.
Today, more than ever, many technology vendors are making significant investments in AI to ensure they are able to offer products and services that can use the technology. Microsoft, Google, Apple, IBM and Amazon, to name a few, have all adopted and fully committed to AI and are already providing these services to consumers.
Anytime a new technology enters healthcare, there are a number of challenges it faces. Common setbacks of AI in healthcare include a lack of data exchange, regulatory compliance requirements and patient and provider adoption. AI has come across all of these issues, narrowing down the areas in which it can succeed.
One of the most popular uses of AI in healthcare is in IBM's smart cloud, where Watson lives. The Watson platform has been used in a number of disciplines within healthcare including with payers, oncology and patient risk assessment.
There are a number of other applications within healthcare where AI can deliver incredible value, but healthcare executives must evaluate and see if they can adopt some or all of them in order to begin their journey in the AI space. The following are six uses of AI in healthcare that are gaining steam.
1. Personal health virtual assistant
With most of today's U.S. adolescents, adults and seniors owning a smartphone, they are likely to have access to an intelligent personal virtual assistant on their device. The likes of Cortana, Siri and Google Assistant are backed by powerful systems with strong AI capabilities. These systems have the potential to provide tremendous value when combined with healthcare apps.
Healthcare apps can be used to deliver medication alerts, patient education material and human-like interactions to gauge a patient's current mental state. The application of AI in the form of a personal assistant can have an incredible impact on monitoring and assisting patients with some of their needs when clinical personnel are not available.
2. Advanced analytics and research
The uses of AI in healthcare do not stop at understanding human commands and knowing what type of response is needed. For example, AI has been used in many advanced use cases in oncology to help detect abnormalities in X-rays and MRIs, in genomics to perform complex processing and in precision medicine to provide assistance in creating highly customized treatments for individual patients.
In the example of IBM Watson, the AI has successfully applied its capabilities to process structured and unstructured patient data. In the field of oncology, IBM Watson can provide evidence-based treatment recommendations for cancer patients.
3. Personal life coach
Healthcare providers who treat patients with chronic diseases recognize the importance of maintaining contact with their patients outside of the exam room. Several hospitals have introduced life coaching services as part of their overall care, but the cost of such services compared to the current shrinking reimbursements makes it difficult to sustain such programs.
However, with today's powerful AI capabilities and mobile apps, patients can receive feedback on a number of data elements captured on their phone or wearable devices. Whether it relates to medication adherence or is simply a motivational voice that encourages fitness activities and healthy habits, AI as a personal life coach creates a customized experience for each individual patient and offers proactive alerts that can be sent back to physicians.
4. Healthcare bots
One of the new areas of AI that is beginning to gain adoption is in the field of customer service, and healthcare bots are likely to be available soon as part of what healthcare providers offer. A bot is an AI application patients can interact with through a chat window on a website or via telephone to receive help with their requests. Bots can be used in situations such as scheduling follow-up appointments with a patient's provider online. Other examples include when a bot helps a patient with their medication or medical billing needs. These uses of AI in healthcare improve customer service; offer 24/7 assistance for basic requests, such as scheduling, billing and other clinical requests; and reduce the overall administrative costs for hospitals.
5. Medical imaging analysis and diagnosis assistance
One of the most valuable uses of AI in healthcare is in radiology. It can assist in the diagnostic processes by analyzing many of the medical images such as MRIs, X-rays and CT scans and providing feedback on what it can detect that the human eye may miss.
6. Dictation assistance with NLP
In order to help reduce the time spent by health professionals capturing documentation, natural language processing extracts data from dictated notes and enters the information into the EHR. Another use of NLP that has been introduced recently is around the analysis of existing clinical documentation. Modern NLP systems are able to sort through the existing content of the charts and highlight the relevant data for the clinical team.
While healthcare is not ready to fully trust AI to independently diagnose patient diseases, advancements in machine learning and big data have contributed to healthcare by assisting in processing data and discovery insights much faster than humans can. Working alongside experienced clinicians, AI is likely to continue to be the current course for many healthcare organizations for some time. Until we can prove that AI has what it takes to accurately diagnose patients, the expansion of its current use in healthcare is likely to be a careful and well-planned process.
But by adopting new uses of AI in healthcare, hospitals can deliver on a number of key goals such as improving patient outcomes and increasing staff efficiency. Over time, more innovations in AI will drive its adoption further.
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