AI’s Healthcare Promise Will Serve Patients — and More

Tech Prognosis: Prevention, Diagnosis, and Back-Office Benefits

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Scanning today’s headlines about Artificial Intelligence reveals an atmosphere of optimism tempered by caution. Artificial intelligence presents a huge opportunity for everyone in the value chain: health providers and organizations, vendors, regulatory agencies, and, perhaps most importantly, patients. It’s driving stats like these: Sixty-two percent of respondents in a 2019 survey by OptumIQ report “having implemented an AI strategy—an increase of nearly 88% from 2018 (33%)—while 22% report being at late stages of implementation.”

But in these early days, the way forward can be unclear, muddied by too many choices, too many voices, and too much-sunk cost in legacy systems and thinking.

To gauge how industry leaders are using or planning to deploy AI, and to collect the best thinking on the most urgent opportunities for AI in healthcare in the near term, we asked experts and influencers to weigh in. The question: “As healthcare organizations invest in artificial intelligence technologies, in what areas can they reap the most immediate benefits?”

From the back office to the front lines, here’s what they told us.

Focus on Patients, Doctors 

Scott Nelson, Founder, CEO, CTO, Reuleaux Technology, agrees.Without question, the most immediate AND impactful application of AI in healthcare will be patient engagement/behavior during chronic care,” Nelson says. “Creating individual care plans which have been intelligently built and dynamically tailored including complex mixtures of prescription drugs is ideal for AI/ML.”

 “When it comes to AI and patient care, we tend to think only of radical advances in the ability to predict and treat deadly diseases. But there are dozens of less complex use cases today where AI is enabling incremental improvements in the patient care journey,” says Mary Edwards, President, Healthcare Provider Segment, at NTT DATA Services. “For example, one hospital is using machine learning to better manage patient flow in real-time, resulting in faster discharges, reduced wait times, and more efficient use of resources.”

“Speech and image recognition capabilities, combined with chatbots, can be used to engage with members or providers to improve the end-user experience,” notes Shashi Yadiki, President, Health Plan Segment, at NTT DATA Services. “Back office operations can be streamlined by using AI to predict which claims will be rejected and require human intervention.” 

The whole lifecycle of patient care has opportunities for machine learning analytics and pattern recognition technologies to make processes more efficient and more tailored to the individual patient,” says Pat Geary, Chief Evangelist at Blue Prism. “Healthcare is a complex business and where there is complexity there is a need for AI/ML technologies.”

In the clinic setting, AI’s impact will energize both sides of the caregiver-patient relationship. “AI will humanize doctors,” according to Peter Nichol, Director, Research and Development IT at Regeneron Pharmaceuticals. Sound contradictory? Nichol goes on:

“AI will take ownership of issues for which humans are now responsible, such as accountability for decisions, bias, inequalities and unfairness, data quality, consent, and information governance. This will free up doctors to focus on patients, not technology. We need a healthcare system where doctors focus on being doctors.”

Beyond the Clinic 

While patient care is rightfully at the center of AI considerations, applications like drug discovery will also benefit, says a pair of executives at Egnyte: Kris Lahiri, CISO, and Alok Tayi, VP of Life Sciences. 

Numerous health and life sciences companies are using AI to drive more intelligent design of molecules and selection of the right patients for clinical trials,” they say in a joint comment. “Algorithms can find hidden patterns in human biometrics to identify markers that portend events like heart attacks and strokes.”

Sarbjeet Johal, a leading cloud consultant, highlights some low-hanging fruit:

Hospital logistics, supply chain management, and insurance are all ripe for AI and ML applications. “Healthcare organizations don’t have to go for a big-bang approach in implementing ML and AI,” he says. He recommends small, incremental steps as well as departmental steps. 

Geary notes some back-office benefits await as well. “The administrative processes for healthcare provision have so many inputs and rules—this is all fertile ground for AI/ML,” Geary says. “Creating individual care plans that have been intelligently built and dynamically tailored including complex mixtures of prescription drugs—is ideal for AI/ML.” 

Data and Diagnosis

 AI’s ability to crunch data, reveal patterns, and learn from each iteration paints a bright picture for diagnosis and early detection.

Jason James, CIO of Net Health, points to one of several examples that have been in the news lately. “A study led by Dr. Yuichi Mori of Showa University of Japan showed that AI was able to detect colorectal cancer with an impressive 86% accuracy,” James says. “AI will become as common and standard in future patient diagnosis as the stethoscope and X-ray are today.”

Data is the key, says Dr Zafar Chaudry, Senior Vice President & CIO at Seattle Children's. “AI in healthcare should be focused on data and analytics; how clinical data can be used to predict and manage medical conditions,” he says. “Prevention is always better than cure (if possible) and AI has the potential to impact this area the most with huge patient outcome benefit.”

“AI tools–particularly deep learning–can improve the speed and accuracy of diagnoses, potentially freeing up more time for patient care,” says Erik Jost, Chief Technologist, Dynamic Workplace Services, at NTT DATA Services. “Routine nursing tasks can be automated, enabling more time at the bedside.”  

From early disease detection, improved patient safety, reduced or eliminated repeatable/mundane tasks and human errors, and more accurate medical billing, AI will play an expanding role in healthcare, says Brian E. Thomas, CIO of Swope Health Services. “Simply put, implementing a set of processes that combines both machines and humans will reap the most benefits.”

“The right infrastructure, coupled with AI technologies and human expertise, will take predictive medicine to new levels and enable electronic health records that truly go anywhere and everywhere,” says Andy Arends, Vice President, Healthcare Strategic Solutions & Innovation, at NTT DATA Services. “Can you imagine a future where healthcare works like we always thought it could? I can.”

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