12 predictions on AI in healthcare: What the patient experience will look like in 20 years

Artificial intelligence is invading healthcare, with startups focusing on every aspect of healthcare delivery from personalized wellness to diagnosis to revenue cycle and supply chain management. Here, 12 health IT professionals give their predictions on how AI will affect healthcare over the next 20 years.

Note: Responses were lightly edited for length and clarity. The quotes are arranged in alphabetical order.

Jay Anders, MD. CMO of Medicomp Systems (Chantilly, Va.). "AI will be incredibly helpful in identifying patterns as long as it takes into account all of the data. Missing just one critical piece could lead to an error and possible patient injury or death. Thus AI will never replace trained, experienced physicians. Patients are unique and physicians treat individual patients — not populations. AI may be able to identify a particular chemo protocol for a particular cancer as giving the best outcome, but it won't be able to do that on an individual patient without having every single piece of clinical data."

Jehan Hamedi. Founder and CEO of Adhark (Boston). "One of the most exciting areas of potential we see in AI is in understanding people in context: who they are, what's unique about them and how to specifically influence their behavior. Similar to marketing technology that automatically learns what messages and imagery will engage a digital audience, AI deployed in a medical setting will be able to harness huge amounts of patient data in order to help healthcare professionals deliver more effective and personalized treatment plans at scale. In short, AI will enable physicians to reach the right conclusions faster. The healthcare system will benefit from more throughput and higher efficiency; the patient will benefit from accurate and timely recommendations and better health outcomes."

Ashish Koul. Senior Vice President and GM of Servion (San Jose, Calif.). "Artificial intelligence is expected to revolutionize healthcare in the near future. AI can have a positive effect on:

• Healthcare customer service: Customer service bots in the future will be able to comb through one's medical records, issue and renew prescriptions, schedule appointments and even help with billing and administrative needs. This will lead to reduced human resources costs (due to fewer call center agents needed), faster issue resolution for patients and a more fluid overall customer experience.

• Medical diagnosis: AI in the future will mine medical records, spot trends and even detect abnormalities faster. First steps are being taken in oncology and genomics today. AI will also be able to gather and analyze data from phones and smart devices. This can help improve the quality and speed of medical diagnosis.

• Reach and availability: Technologies like natural language processing will allow virtual bots to converse with any individual having a cell phone. This is especially important in areas with less established healthcare systems, potentially providing basic healthcare access and guidance to a large number of people."

Derek Gordon. COO of Lumiata (San Mateo, Calif.). "The healthcare industry can expect tremendous changes as AI advances and grows within hospitals and healthcare systems. Data gathered and presented by AI algorithms will enable healthcare providers and doctors to see patients' health risks and take more precise, early action to prevent, lessen the impact of or forestall disease progression. These interventions will curb healthcare costs and lead to improved patient health outcomes.

Additionally, we can expect routine and time-consuming tasks to become automated. According to Anthem, its care management nurses spend 40 percent to 60 percent of their time reading and aggregating information, including information on Anthem's policies, clinical research and treatment guidelines. With AI and automation, these highly-skilled personnel will be redeployed towards more urgent priorities in caregiving and the complex decision-making that require human cognition not well-suited to AI.

To prepare now, hospitals and healthcare systems must do a better job aggregating, normalizing, structuring and sharing patient data in a way that can lead to faster, more efficient predictive analytics, diagnoses and preventative care."

Cynthia Burghard. Research Director of IDC Health Insights (Framingham, Mass.). "AI and other cognitive technologies will continue and expand in the augmentation of clinician decision-making from reading radiology scans to improving outcomes through better treatment decisions. It will also be applied to consumer experiences in areas such as medication compliance and adverse event avoidance. The use of robots for routine tasks will continue in areas such as supply transporting within hospitals. The ability to continue to develop solutions to diagnoses and treatment using genomic information will become more precise."

Srinivas Kowta. Senior Director of the Health Analytics Vertical of Axtria (Berkeley Heights, N.J.). "I would summarize the following specific ways in which AI is revolutionizing healthcare and medicine, and will do so in the future:

1. Improve the accuracy of the Decision Making Systems in identifying treatment options in the regular and emergency setting.
2. Accelerate the time to diagnose hard-to-diagnose conditions such as cancers, Alzheimer's, multiple sclerosis and other rare disorders.
3. Increase the alternatives in treatment choices when the primary alternatives may not work in real time.
4. Customize healthcare to a segment of one: make the holy grail of individualized medicine a real possibility.
5. Exponentially increase the efficiency of physician-based repetitive tasks.
6. Accelerate new drug discovery.
7. Data mining patient treatment and health records across geographical boundaries to develop accurate treatment plan.
8. Significantly improve patient compliance and persistency with their treatments."

David Milward. CTO of Liguamatics (Cambridge, United Kingdom). "When you are inside a field such as AI, each step seems incremental. From the outside, there appear to be large jumps, as the field comes in and out of public attention. In 20 years from now, we will be routinely using AI to bring us relevant information when we need it, and to recommend decisions for us to take. We'll also be able to predict individual patient outcomes better by learning from the experiences of others.

How will this information be delivered to us? There has already been a move from keyboards to touch devices and to voice. In specialized areas we are likely to find people still want to see complex information displayed visually rather than summarized for them by voice, even if it is through head-mounted devices or even implants.

How will we share information with each other? This is still likely to be text, and with natural language processing making unstructured data accessible, we may see a reverse of the current trends for structuring and coding data during entry."

Eric Sullivan. Senior Vice President of Innovation and Data Strategies of Inovalon (Bowie, Md.). "Historically, the healthcare system in the United States has been plagued with the obstacle of rising healthcare costs and inefficiencies attributed to the fragmented nature of care delivery. As the frameworks for interoperability and interconnectedness evolve to bridge the chasms between healthcare silos, so too do the opportunities to more quickly aggregate data and leverage advanced parallel processing to employ cognitive computing and AI-like technologies. Using systems and platforms that integrate and aggregate disparate real-time data from historically fragmented sources and making those data available to the health care delivery system provides for the basis for AI to change how payers, providers and other healthcare organizations engage with patients and drive outcomes in a growing value-based, outcomes-based environment.

The future of AI is supported by scalable big data platforms and these integrated diverse data sets will impact clinical organizations through a shift in the role of the provider from one of diagnostician informed by training and evidence-based practices, to decision makers informed by both that training and practices as well as informed now with real-time patient specific analytics to guide the clinician at the point of care. These processes will help to change the healthcare system through improvements and efficiencies in areas such as having appropriate clinical and risk indicators at the point of care, reduction in medical errors, improved diagnosis within the mental health domain, detection of cancer and various others. You see this application starting to emerge across the healthcare ecosystem in areas such as telemedicine and specialty pharmacy delivery where clinicians may soon be armed with a longitudinal patient record during their virtual visit that is tailored to the specific genotypic, phenotypic, social economic circumstances of that patient, as of that moment in time."

Cindy Ehnes. Executive Vice President of COPE Health Solutions (Los Angeles). "AI will increasingly seamlessly integrate into the U.S. health system in the next decade. In a world of 3-D printers and self-driving vehicles, consumers and clinicians will readily incorporate technologies that don't simply collect and compute information, but add cognition. AI will continue to alter the way patients and providers interact, how health systems will view the care continuum and how clinicians will determine course of treatment. Increasingly, quality and affordable healthcare is defined as getting the right treatment to the right patient at the right time. AI advances in such precision medicine will drive a wholesale change of health organizations and procedures.

However, adoption of AI advances will be bimodal: wealthier systems will garner the newest 'whiz bang' technologies and health systems serving poor communities will struggle to access these cognitive capabilities.

Health consumers will increasingly link themselves to mobile devices that nudge them to make healthy lifestyle decisions. The consented collection of personal medical information for use by the patient and his or her treatment professional is a given. However, the concept of who is the 'treatment professional' has broadened and will continue to expand beyond the four walls of the doctor's office and into the patient's clinical and social community. For health systems serving underserved health communities, technologies are critically important that can engage those consumers and meet them in a variety of care settings. Adoption, though, may be slowed by affordability and insurance reimbursement. Further, the risk over time is that many of these applications may go the route of the dusty stationary bike stowing laundry in the basement."

Al Babbington. CEO of PrescribeWellness (Irvine, Calif.). "In 20 to 30 years, we really will be living in the Jetson era. By then, big data, the internet of everything , precision medicine and AI will have converged. A body scan will verify what we can already predict based on genetic mapping. Therapy, diet and treatment will all be personalized to the individual, and treatments like chemotherapy will seem as barbaric as leeching. Prevention centers will be hubs for in-home healthcare, and we'll have robotic caregivers. Some of the greatest advances will be in neuroscience. We'll have the ability to map the billions of neuron firings for personalization and unique mental health therapies."

Max Versace. Co-Founder and CEO of Neurala (Boston). "AI will democratize access to excellent healthcare for people who cannot normally afford it. There are two main entry points for AI in healthcare: diagnosis and treatment. AI systems can be trained to approximate the competencies and abilities of the best doctors available. So, in diagnosis, imagine having access to the best doctor trained on the largest corpus of medical data, right where you are, at the speed of light. In treatment, a combination of robotics and AI will also democratize access to the best-trained 'hands.' Using the same methodology, AI linked with a robotic effector will perform surgeries as well as the top 1 percent of surgeons, making access to premium treatment a reality for a large portion of the population, at a fraction of the cost. In essence, people will have the brainpower of the best doctors immediately available to them, resulting in faster, cheaper and more effective treatment. As a doctor friend of mine used to tell me, 'Somebody has to be last at medical school.' With AI, that will no longer be true. We will all always have access to the top doctors."

Nathan Spoden. CEO of Tremont Health (Cleveland). "Artificial intelligence will completely revamp the way revenue cycle management is run for healthcare providers. Everything from the front office staff becoming an AI kiosk that can ask you anything, to an AI program automatically reaching out to your insurance company to resolve the billing process. Costs will go down significantly, because instead of being treated by a typical doctor, a lower level provider, such as a PA or NP, will be able to help patients with an AI program that assists with medical decision-making.

Overall, providers will still need to manage the performance of their revenue cycle, but AI programs and business intelligence systems will have automated all of the reporting and monitoring Healthcare providers will need to ensure their revenue cycle is running successfully. In order to prepare for AI invading healthcare, physicians and hospitals will have to prioritize their management talents over more manual tasks, like reading radiology images and analyzing blood work results. Managing AI programs can only be done by humans…for now. "

More articles on AI in healthcare:
9 key thoughts on how machine learning and deep learning will affect healthcare
13 healthcare AI startups with $25+ funding
How to prepare for AI at your hospital: Key thoughts from 5 health IT executives

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