How AI could shape the health tech landscape in the year to come

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October 2, 2019


The promise of AI in healthcare is finally starting to move beyond speculation.

In recent years companies have been funneling funds into advancements, especially those that cut costs and promote patient health. Spending on healthcare AI technology is expected to surpass $34 billion by 2025, compared to $2.1 billion in 2018, according to market intelligence firm Tractica.

Amazon, Siemens, IBM, Optum and GE Healthcare and health systems Mayo Clinic, Memorial Sloan Kettering and Intermountain are mining patient records for health data to train AI algorithms, allowing the machines to learn by recognizing patterns and make key predictions.

In some cases, such deep learning systems are already outperforming doctors. In others, they’re not.

Either way, experts predict that in 2019 AI in healthcare will continue to grow — especially in the areas of imaging, diagnostic, predictive analytics and administration.

Administration  scheduling, operations, billing  is the biggest area for AI growth in the coming months

The AI for healthcare information technology market is expected to exceed $1.7 billion by the end of 2019 alone. That tech can be used to detect the waste, fraud and abuse in healthcare spending — estimated between 3-10% of the more than $3 trillion spend in the county every year.

Frost and Sullivan’s SVP of Healthcare and Life Sciences Reenita Das predicts operationalizing AI platforms across healthcare workflows would result in a 10-15% productivity gain over the next couple of years.

In the current healthcare environment, with skyrocketing costs, an aging population and workplace shortages, it’s important to leverage use cases that aren’t clinical, Intel’s worldwide head of the health and life sciences group Jennifer Esposito told Healthcare Dive.

Repetitive, time-consuming tasks are where AI thrives — and there are a lot of those in America’s healthcare chassis. “We’re seeing a lot more of a conversation shift to AI being an augmenter or an enabler or an assistant,” Esposito said.

One example is scheduling and appointments. Cleveland’s MetroHealth System had a 10-35% no-show rate at its four hospitals before bringing AI into its operational decision-making in late 2017.

MetroHealth used AI to quantify that select patients that had a high likelihood of not showing and double book those patients in order to not waste providers’ time, MetroHealth’s chief strategy and innovations officer Karim Botros said at a 2018 U.S. News Healthcare of Tomorrow panel on AI.

The AI practice operates in the background, integrated into MetroHealth’s Epic system. So far, it has reduced the next available appointment time by roughly 30%, according to Botros.

Hospital operations is another place AI may help in 2019, experts say, by predicting where in the hospital workers are most needed.

Cleveland Clinic is currently tracking hospital bed use through an AI platform initially built for retailers. It keeps tabs on its surgical suite resources to get to full capacity and utilization. The program looks at patient movements through the OR to help identify potential bottlenecks in that process.

AI can also be leveraged to keep track of drugs and medical devices in health facilities, along with promoting financial responsibility in patients.

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