Harvard-based healthtech startup plans India entry with proprietary AI technology
basys.ai, a healthtech startup, spun out of Harvard, is looking to launch its services in India in a few months. It uses its proprietary AI technology to track, predict and provide interventions to improve treatment outcomes for better metabolic health.
, a healthtech startup that began its journey from Harvard, says its in-house technology will help improve doctors’ clinical decision-making in managing the metabolic health of their patients.
The startup has initiated discussions with healthcare providers in India as well as Singapore to launch its platform in these markets. It is banking on the Indian government’s Ayushman Bharat Digital Mission, which aims to interconnect the digital health solutions of hospitals across the country. This programme is likely to enable the consensual sharing of patient records with doctors in any hospital in India.
“We are interested in going to India because we believe this (the universal electronic health record framework) will be a reality in the next five years. Initially, it might not be profitable or we may not have the numbers we need but we are excited about the sheer scale we can achieve in the market,” Amber Nigam, Co-founder and CEO of basys.ai, tells YourStory.
In 2019, around 77 million individuals had type-2 diabetes in India. Given that one in three adults in the country currently suffers from metabolic syndrome—a cluster of conditions that increase one’s odds of developing cardiovascular disease or type-2 diabetes, there is a significant burden of these diseases in India.
Amber says basys.ai might launch the platform in India within the next few months based on the support it receives from prospective investors.
As the building of the universal health record system is underway in India, basys.ai plans to partner with hospitals to build its AI (artificial intelligence) capacity. Currently, the startup is only operational in the US.
The genesis of basys.ai
Amber met his co-founder Jie Sun while attending Harvard’s health data science programme. As they exchanged ideas at the cross-section of data science and healthcare, they decided to work on improving the metabolic health of people and narrowed it down to diabetes.
For Amber, the fight against diabetes-type-2 is also personal as his father suffered from the disease.
The co-founders launched their venture in 2020.
basys.ai has won several competitions. The co-founders were in the winning team of the MIT (Massachusetts Institute of Technology) 100K Accelerate event. They have also received grants from the likes of Harvard Innovation Lab and MIT.
The healthtech startup has also bagged its first customer, the world’s largest diabetes research centre. basys.ai says it will earn more than $1 million from the 5-year contract.
Under the deal, basys.ai would work with the diabetes centre to monitor, track and come up with interventions for other metabolic health issues such as kidney and cardiovascular diseases. It is currently working with the research centre on the entire spectrum of diabetes-related problems.
basys.ai’s proprietary AI technology
basys.ai relies on three main sources of data for tracking patients’ health: historical data of the patients, glucose levels received from glucose monitors in addition to other health metrics received from devices and inputs manually fed by the users. The platform assigns the least importance to the last source as users tend to be biased while feeding their own data.
The healthtech startup is awaiting approval for its patent application filed for its AI technology.
The startup combines the EHR (electronic health record) data with the health metrics collected via user devices to profile the risk of the users, summarise the information for the doctors, recommend tests, and predict/suggest disease management strategies.
“We extract patterns from the information that exists about the patients in the electronic health records (EHR). Once we have extracted this information, we do the pattern-finding exercise and classify the patients in different risk categories,” says Amber.
Once the risk profiling of the users is done, basys.ai defines different diagnostic tests that the patients have to take including the frequency at which those need to be taken.
For instance, if an individual is going to have a test for diabetic retinopathy (a complication that affects the eye), the platform would suggest if they should do it once in three months or every six months or if an annual test is enough.
Or, let’s take the case of someone with diabetic neuropathy (a type of nerve damage that can happen due to diabetes) or diabetic nephropathy (a condition that can lead to kidney damage and high blood pressure). The platform would be able to help determine if patients should go for additional tests such as an electrocardiogram (ECG) or a renal function test as diabetes can lead to the failure of internal organs.
How the platform works
There are two types of users for the startup’s platform: the providers/doctors and the patients. Currently, the startup is mainly focussed on doctors.
Amber says the platform provides the patient information, which includes their past and current health status and the recommended next steps, to the doctors via a dashboard.
Amber says doctors usually have around 15-20 minutes on average to scan a patient’s health records, diagnose their problems and suggest treatment plans for them.
“The doctors try to make sense of the data (from the EHRs) as humanly as possible in a short period of time. And, EHRs are like messy notebooks where the doctors need to click on multiple tabs to figure out the patient’s information. They may end up taking shortcuts in scanning the info, which is not good for the patients,” says Amber.
“The differentiation is that basys.ai uses AI to provide the patient’s health summary and a list of actionable points that the doctors can make use of,” adds the co-founder.
Currently, the use of the platform is optional for patients. Once they’ve signed up on the platform, they can sync their glucose monitor. All the information that has ever been collected would automatically get loaded onto the platform. Users can also choose to sync their smartwatches with the platform.
Besides the glucose levels, the platform also collects other information that gives a picture of an individual’s metabolic health such as blood pressure, heart rate, physical activity done in a day, calories burnt, resting heart levels and heart rate variability in case of those using devices to monitor these metrics.
The platform uses such information and figures out if the diabetic condition is improving or not.
Those who do not use any device to record their glucose levels have the option to manually enter the details.
“So far, we’ve been trying to make it provider-first such that the doctors recommend the platform to the patients. When doctors recommend it, either the patients or their family members download and use it,” says Amber. The startup is also trying to figure out if it can make a B2C (business to consumer) platform launch.
For the hospitals, Amber says basys.ai would help increase their revenues and decrease their costs. “Under the value-based healthcare delivery model, if hospitals improve patient treatment outcomes, they end up with increased payouts from the insurance companies," he says.
Under the fee-for-service model (where doctors and other healthcare providers are paid for each service provided), doctors would be able to treat more patients in a given time period.
The road ahead
Apart from working on a B2C platform for patients in the US, the startup is also looking at mental health.
“The next step for us is mental health. But we’re not there yet. It is a part of metabolic health but it’s a totally different game,” says Amber. The startup is also talking to a few hospitals in the US for similar partnerships.
Both Amber and Jie have put in their savings to build their startup in addition to the money they’ve earned from grants and competitions. basys.ai is now in talks with some investors to raise their seed capital. The healthtech startup is currently focussing on scaling its product and customer base to achieve “clinical validation” globally.
(The article has been updated for clarity and style)
Edited by Affirunisa Kankudti
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