Healthcare pundits like to claim that an immutable law exists when it comes to optimizing any health care system — “Any healthcare system can only optimize two of the three elements – quality, access, and cost.” (“The Iron Triangle of Health Care: Access, Cost and Quality”, Journal of the American Medical Association).
It is believed that a system that favors the finest quality and best access cannot provide services at a reasonable cost. And an inexpensive one available to all cannot do so without sacrificing quality. But as we learn from other industries, the healthcare industry really isn’t that different when it comes to breaking such a triangle by disrupting the status quo.
Industries such as commercial aviation and computing went through disruptions which made services affordable, accessible, and better over time. The same is possible for the healthcare industry. This is especially true in a time when technological breakthroughs, better medical understanding, and deeper research interests are intersecting to create a ripe environment for the inevitable disruptions that will herald the next era in healthcare. This is where Artificial Intelligence (AI) in healthcare comes in. The familiar promise of AI technology as the savior is finally starting to show merit, with healthcare executives embracing it enthusiastically and others planning to do it very soon, according to the Accenture Executive Survey on AI in Healthcare.
Below are some areas where AI technology has already made its presence felt or can bring a difference in the future of healthcare:
- Medical diagnosis: Vision and deep learning can be leveraged to accurately diagnose and even predict diseases.
- An algorithm recently developed by Stanford researchers, CheXNet, diagnosed pneumonia, as well as up to 14 additional conditions, far better than its radiologist counterparts (scoring 0.435 on the F1 precision metric, higher than the Stanford radiologists’ average of 0.387), as reported in their paper published on the scientific preprint website arXiv. It was trained on 112,120 X-ray images labeled with up to 14 different pathologies.
- Post-operative care: Artificial intelligence in healthcare can help providers take extra precautions and save millions incurred due to needless hospital readmissions.
- Hospital systems like the Mercy Medical Center have managed to reduce readmissions by 20 percent% using AI and machine learning (ML).
- Assisted surgery: AI technology can help surgeons choose surgical methods better using correlations with other cases and help with accurately tracking vitals and other data during surgeries.
- Precision treatment: Natural language processing (NLP) and computer vision can assist doctors with diagnosis as well as running pharmacy correlations with other drugs, allergies, and foods, among other elements, to take a step further towards precision treatment.
- Virtual health: Chatbots or other smart services can solve patient queries like diagnosing symptoms or assisting them with routine tasks like appointments.
- The Microsoft Healthcare Bot empowers healthcare organizations to build AI-powered, conversational bots. Numerous other chatbots like Sensely, Babylon Health, and Florence offer a variety of virtual health services like diagnosing symptoms using a built-in, comprehensive medical database.
- Hospital management: This entails better planning and forecasting of hospital assets, emergency management, and operations processes.
- Glintt, an IT solutions integrator, recently worked with IBM to develop WiseWard, a solution that helps streamline hospital bed assignment decisions by predicting patient discharge trends. According to a Navigant survey, using AI analytics to make data-driven decisions about hospital operations could save hospitals almost $10 million per year.
- Telemedicine: Accurate remote health monitoring, predictive diagnosis can lead to cheaper remote and rural health management
- Local governments in Chinese provinces like Anhui and Jiangxi have been leveraging AI and cloud platforms to diagnose patients accurately and quickly in areas such as medical imaging (X-rays) and AI medical assistants (assisted surgery and diagnosis)
On the other end of the healthcare network, AI can also revolutionize the payer world by equipping insurance companies with the analytical and predictive power of AI to come up with better, cheaper, and optimized health plans which can better catch errors in payments, frauds, and workflow issues. In one such case, an AI-based system exposed a member of an insurance fraud ring in their customer database by cross-referencing external news data sources. AI in healthcare is predicted to become a $27.6 billion market by 2025, according to a report by Meticulous Research.
It needs to be kept in mind, however, that in the next few years, the real transformative power of AI lies in the back office – applications that lead to operational benefits and lowering costs i.e. the cost element of the triangle. For now, healthcare leaders are investing in making their systems safe from cyber-attacks and supporting mundane, repetitive tasks like responding to users’ tech queries and processing documents, using robotic process automation (RPA). Only a small group of the leaders surveyed are doing so for the AI applications focusing on greater care effectiveness/quality.
AI will surely make its way into the front office at some point in the future of healthcare, pushing an estimated 30 percent of the workload to smart machines or patients themselves. It is a promising sign that as many as 40 per cent of health executives are quite highly focused on increasing the use of AI-assisted applications, while another 53 percent are moderately focused on the matter. Patient-facing applications are expected to follow suit and show real, game-changing benefits in the future. Part of the reason why healthcare, unlike other industries, has not benefited from the productivity gains of IT is that much of the work in healthcare, both physical and cognitive, is non-routine work. AI and ML change that, with machines being able to do non-routine work.
HCL is pioneering ground-breaking innovations in front-office as well as back-office AI and healthcare services. The proprietary EXACTOTM framework, developed in collaboration with MIT CSAIL, harnesses the power of AI, ML, and computer vision, integrating seamlessly with RPA capabilities to create a truly unique solution. HCL has also developed an AI-enabled cognitive virtual assistant named Lucy, part of its DRYiCE Automation Framework. These offerings have yielded tremendous benefits for numerous healthcare payers and providers.
For an industry that has always sorely lacked in skill availability, AI can do wonders in times to come. What is needed is for the best and brightest minds of the industry to come together and ensure that the next generation is equipped with the right mindset to tackle the issues we face today. Otherwise, the looming fear of the iron triangle in healthcare will inevitably bring a self-fulfilling prophecy to fruition.