7 AI Healthcare Startups Digitizing Hospital Operations
We once had to rush a buddy to a hospital while cruising the steep switchbacks on Bali after his scooter zigged left and he zagged right. Aside from prison, hospitals are usually the last place you want to be in a Third World country. In this case, there was no doctor on duty at one of the island’s biggest hospitals. Fortunately, our friend was a registered nurse who ended up reading his own X-rays. The hospital staff then plunked a catalog-sized book of prescription medicines down in front of him and asked, “What do you want?” So there was a silver lining. While U.S. hospitals are certainly a better alternative – and, until recently, also a reliable place to
score drugs receive medications, before the opioid crackdown – they could probably use some improvements. Can AI healthcare startups provide some much-needed innovation to improve service and cut costs?
As we noted in our recent article on value-based care solutions employing AI for better patient (and bottom-line) outcomes, there’s a lot of financial waste. A significant paper published last year in the Journal of the American Medical Association (JAMA), which reviewed previous estimates from 54 unique peer-reviewed publications on financial waste in the healthcare system, identified nearly $1 trillion that went out with the bedpan. Roughly 25% or more stems from a category that was called “administrative complexity.” While we can’t do a line-by-line analysis, no doubt tens of millions of dollars can be blamed on some of the byzantine systems and processes still in place at U.S. hospitals in order to manage patients, doctors, bed space, and all those bedpans. (A company called Health Catalyst is working on solving this problem, something we discussed in our recent piece on A Stock for Investing in Healthcare Data and Analytics)
Here are some more numbers to consider: The U.S. spends $3.65 trillion on healthcare, which works out to more than $11,000 per person, and nearly 60% of the spending going to hospitals, doctors, and clinical services. Despite spending more money than any nation – or 10 of them combined – the U.S. healthcare system ranks 27th based on quality of care and other metrics. Another recent paper in JAMA noted that for all that money Americans are living shorter lives for the first time in decades. Certainly, we won’t be able to reverse these trends by simply improving workflow at hospitals through intelligent automation, but every dollar not chewed up in the bureaucratic machinery is one that can be spent on value-based care outcomes. So let’s look at seven AI healthcare startups trying to digitize hospital operations.
Making Room in the OR
This story, like so many, begins in Silicon Valley, where venture capitalist vampires believe young blood transfusions will prolong their lives. But not every startup out of the U.S. tech capital is so sinister when it comes to disrupting healthcare. Founded in 2010, LeanTaaS has found a way to use machine learning to optimize hospital resources like operating rooms. Investors like the idea, with Goldman Sachs leading a $40 million Series C just last month, bringing total funding to a reported $101 million. Just like McDonald’s and other fast-food companies are using AI to speed customers through its restaurants, hospitals can employ LeanTaaS’ flagship product, iQueue, to maximize hospital assets like the OR and inpatient beds. Algorithms juggle hundreds of variables for what amount to schedule multi-tasking.
The company claims iQueue for the Operating Room is used by more than 100 hospitals for 900 ORs, each of which has experienced an average revenue increase of $500,000 per year. You can go here to read about specific case studies, such as how OhioHealth gained more than 200,000 minutes in OR time over just six months that would have gone to waste.
Don’t Overstay Your Welcome
Another Silicon Valley AI healthcare startup, Qventus, is also trying to keep things moving along with its machine learning platform by getting patients out of the hospital quicker. Founded in 2012, the company has raised more than $45 million in disclosed funding from some well-known investment firms, like Bessemer Venture Partners. Qventus’ machine learning-platform identifies potential issues or bottlenecks that keep patients in hospitals longer than they need to be. The company claims its technology is used in more than 70 hospitals nationwide where it has reduced patient length of stay by more than half a day in some locations.
While that might not sound like much, one in three hospital deaths are due to sepsis, or infection, so it’s best for everyone if a patient is discharged as soon a clinically advisable.
Going with the Patient Flow
Across the country in a Boston suburb, Hospital IQ is going with the patient flow with an AI platform it says uses structured and unstructured data to feed algorithms that can make crystal ball decisions on hospital management across operations. Founded in 2013, Hospital IQ has picked up about $23.2 million in funding. Its platform taps the usual databases, as well as unconventional sources such as weather forecasts, air quality readings, and seasonal health trends. It then churns out insights on block allocation, surgeon schedules and preferences, hospital policies, and staff.
Last year, Hospital IQ rolled out a new solution for managing OR assets. Starting to see a trend here?
Bridging Data Silos
Another AI healthcare startup digging deep into data is Shanghai-based Synyi, which was found in 2016 and has picked up $80 million in funding. It raised about $36.3 million in July in a Series C led by Chinese tech giant Tencent. Sequoia Capital’s China branch was an investor in both the Series A and Series B. Synyi reportedly started out focused on using natural language processing (NLP) to parse through scientific research data but has since moved on to create a platform capable of extracting information from medical records, and then managing and analyzing the data. The solution is intended to not only bridge the data silos within a company’s IT system but surface valuable insights along the way.
Robotic Process Automation in AI Healthcare
The recent layoffs at UiPath, at the time a $7-billion-dollar Robotic Process Automation (RPA) startup, hasn’t necessarily dimmed the glow of a technology hyped as software robots for doing office work. These algorithms, however, can recognize documents or understand the context of an email message. That brings us to Columbus, Ohio-based Olive, which is doing RPA for hospitals. And it has raised $72.8 million for its cause, with tech-savvy VC firm Khosla Ventures participating in multiple rounds. Here are a few of the human employee jobs that can go away soon:
The company says it takes Olive about 12 seconds to process one claim status check, against 85 seconds for a human employee between 90-second-long surfing sessions on Facebook. That means Olive does the work of about nine full-time employees per week – if they could work non-stop for 40 hours.
Update 03/31/20: Olive has raised $51 million in funding to accelerate its growth and to invest in R&D and engineering. This brings the company’s total funding to $123.8 million to date.
Update 09/17/20: Olive has raised $106 million in financing to continue to expand its healthcare AI workforce. This brings the company’s total funding to $230.8 million to date.
The Patient or Doctor is Always Right
It turns out that we still get a say in how the machines decide our fate. Austin-based NarrativeDx has raised $6.6 million in disclosed funding, including $3 million just more than a year ago. Its platform uses NLP and machine learning to understand feedback from healthcare providers and their patients by recognizing more than 5,400 root causes of patient and provider satisfaction. It then provides feedback on how to take actions that could lessen patient dread and caregiver burnout. The whole thing is based on research on more than 11 million tweets comments.
Reading Between the Lines
Another twist on AI-powered customer service comes from Silicon Valley-based HealthCrowd, which has raised nearly $10 million for a healthcare communications system. The platform funnels information from disparate sources – text, voice, email, etc. – and then uses various AI tactics like NLP to extract intelligence that it claims will improve member experience and the organization’s efficiency. This sounds a bit like another three-letter acronym related to RPA called customer relationship management (CRM), but just marketed to hospitals and the healthcare sector.
This list of AI healthcare startups digitizing hospital operations could appear as a list for quite a few other industries. In other words, it’s interesting to see the depth at which companies are adapting artificial intelligence for specialties like hospital operations. It speaks to just how widespread the technology – and, we suspect in some cases, the hype – is becoming in many business processes, whether it’s selling Coca Cola or treating cancer patients.
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