The use of artificial intelligence (AI) technology in health care is poised to soar throughout the globe in the coming years, including to support preventive care in people’s homes.
That’s according to a new report from market foresight advisory firm ABI Research. The report defines artificial intelligence (AI) as providing “a device or software program the ability to interpret complex data, including images, video, text, and speech or other sounds, and act on that interpretation to achieve a goal.”
The number of monitoring devices capturing patient data for AI purposes such as predictive analytics will increase exponentially, the report found. Specifically, there were 53,000 such devices in use as of 2017, and there will be 3.1 million as of 2021.
“This includes the use of AI for home-based preventive care solutions,” an ABI press release stated. “With more devices connected to AI-based predictive analytics models, hospitals will save US$52 billion in 2021, led by North America with US$21 billion in savings.”
This savings will be achieved in various ways, but home-based AI is one driver, report author and ABI Principal Analyst Pierce Owen told Home Health Care News.
For instance, AI holds promise for predicting a worsening heart condition, prompting a person to seek medical attention before a crisis.
“If you can go to the hospital and say, ‘I’m about to have a heart attack,’ and you have proof from an FDA-approved product, it is less costly to treat you,” Owen said.
While he did not break down the forecast for hospital versus home-based AI, Owen does believe that home-based artificial intelligence has a significant role to play in driving down health care costs.
One AI product he researched for the report is called EarlySense. It involves a sensor placed under a mattress, either in a hospital or a home, which captures metrics such as heart rate and temperature to generate a variety of predictions—everything from worsening asthma and heart conditions to women’s ovulation cycles.
Getting FDA approval was a “huge step” for EarlySense, Owen said, pointing out that there are few commercialized and scaled AI solutions on the market currently.
Many AI startups are targeting hospitals first, and they are encountering bureaucratic roadblocks, budgeting concerns, as well as a sense of distrust and fear over giving over the personal data needed to train artificial intelligence models.
Today, this sense of distrust might be the biggest inhibitor holding back AI, but that should change in the coming years, Owen said.
In the future, AI models will have less need for large amounts of raw data, once they have reached a critical mass and know how to interpret and act on particular pieces of information. Also, people are becoming gradually more comfortable sharing their personal data, thanks to social media as well as consumer health monitors such as Fitbit.
Many home health providers likely will not be surprised by the ABI Research findings, considering AI initiatives happening in the industry.
For example, Avamere Family of Companies is doing a pilot with IBM’s Watson—an AI platform famous for beating human Jeopardy! champions at that game. Wilsonville, Oregon-based Avamere operates skilled nursing facilities and senior living communities, as well as a home care brand called Signature and a rehab business called Infinity.
One goal of Avamere’s Watson project is to gather and analyze patients’ data to make sure they are in the most appropriate care setting, whether that’s a skilled nursing facility or at home.
Written by Tim Mullaney