Digital Doc: Artificial intelligence in healthcare: 6 health IT executives on what to expect over the next 20 years
Artificial intelligence is gaining ground in healthcare. In 2012, there were fewer than 20 artificial intelligence startups focused on healthcare; last year there were almost 70, according to Becker's.
Additionally, the AI for healthcare sector is expected to drive overall AI market growth over the next six years. The overall AI market is expected to grow at a compound annual growth rate of 62.9 percent from 2016 to 2022, when it's projected to reach $16.6 billion.
Six health IT company executives summary of how AI will impact healthcare over the next 20 years:
Mudit Garg. Co-Founder and CEO of Qventus (Los Altos, Calif.): AI will not replace physicians, but AI is here and already helping. It's improving the flow of patients through the ED, reduce surgery delays and cancellations and eliminate patient falls. One hospital alone eliminated over a million minutes of patient wait time last year. As AI becomes widely adopted, hospitals and physicians will see a massive load lifted off their shoulders and burnout rates substantially reduced. Instead of having to look at every bit of data and anticipate every potential action and reaction, they will be able to focus solely on those issues that require their attention and spend the rest of their time dedicating themselves to their patients.
Charles Koontz. President and CEO of GE Healthcare IT and Chief Digital Officer of GE Healthcare (Chicago): "Digital health transformation is happening now. Machine learning and AI are already demonstrating its potential to drive efficiencies and improve the quality of care and will continue to be significant in the next 20 years. For example, GE Healthcare and the University of San Francisco are already putting digital health into action by developing a library of deep learning algorithms that will improve efficiency, speed and accuracy for clinicians to interpret scans and diagnose patients faster. One example is an algorithm that screens X-rays for pneumothorax (a collapsed lung), which can be a life-threatening condition. With this algorithm, the X-ray machine helps hospital workers quickly identify the presence of pneumothorax and alert the radiologist to prioritize the read in the worklist queue, potentially leading to faster and better outcomes, reduced costs and improved patient experience.
Greg Kuhnen. Senior Director of Research at Advisory Board (Washington, D.C.): Physicians are drowning in information and AI can help distill the ocean of raw data into high-quality predictions or highlight latent surprises. We expect AI agents to be deployed as integrated assistants suggesting diagnoses; tailoring order sets to a patient's unique circumstances; projecting risks and potential interventions; and taking over laborious patient monitoring and data interpretation tasks entirely.
Fatima Paruk, MD. CMO of Allscripts Analytics (Chicago): AI systems will play critical roles in healthcare within the next two to three years. The first application of intelligent systems will impact the care management of prevalent chronic diseases of populations. The next wave will leverage increasingly available patient-centered health data with external influences such as pollution exposure, weather factors and economic factors to generate precision medicine solutions customized to individual characteristics. Within reach will be the use of genetic information coupled within care management and precision medicine to uncover the best possible medical treatment plans.
Rajeev Ronanki. Principal in Life Sciences and Health Care of Deloitte Consulting (Los Angeles): There's a confluence of three powerful forces that is driving the machine intelligence trend: exponential data growth, faster distributed systems and smarter algorithms that interpret and process that data. CIOs can expect a number of ways to derive value from machine intelligence. Those opportunities include:
• Cognitive insights — machine intelligence that can augment human decision making;
• Cognitive engagement — machine intelligence based cognitive agents to engage with consumers via voice commands which will advance over time to perform more complex tasks such as admitting patients to hospitals; and
• Cognitive automation — machine intelligence baked into devices and processes that develops deep domain-specific expertise then automates related tasks, freeing up workers to focus on higher value activities.
Lisa Suennen. Managing Director at GE Ventures (Menlo Park, Calif.): AI offers the opportunity to free physicians and other clinicians from tedious work analyzing data, giving them time to apply their knowledge in a more focused, informed way. We think AI allows clinicians to work at the highest level of their ability by making them far more informed and effective patient advocates.
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