Clover is focusing on its members with the most complex needs, providing more home care and genetic testing to prevent adverse medication reactions.
Healthcare is a collection of “structural inefficiencies” off of which entire business models have been built, according to Vivek Garipalli, CEO of Clover Health.
Speaking to Bloomberg’s Drew Armstrong at CB Insights’ Future of Fintech conference, Garipalli talked about how many of these inefficiencies are driven by opacity.
Using pharmacy benefit managers (PBMs) as an example, Garipalli said that “a distributor like a PBM can get 20-30% margins”, which is significantly higher than in other industries — “the more opaque the P&L is, the higher the EBIDTA.”
Essentially, the more healthcare companies can hide their business models, the more money they can make off of providing care.
Garipalli believes some of these inefficiencies could be resolved by transparency and flatter fee pricing, especially in more opaque markets like the employer healthcare market. The Amazon-Berkshire-JPMorgan coalition could be interesting for that reason.
Cost inefficiencies are also a major problem, especially when dealing with people with complex conditions and multiple chronic diseases: “The existing healthcare ecosystem is not set up to take care of these patients.”
Vivek says that Clover brought the ratio of caregivers to patients in their network down to ~1:200, which includes home aides, partnered physicians, and doctors.
By doing this, they were able to send more lower-cost caregivers to patients’ homes and spend more time with potentially costly patients.
Clover’s genetic testing initiative also tackles inefficiencies through a focus on data.
The company is trying to better understand how variants in the genetic code may affect medication reactions. By knowing the likelihood of how a patient might react to a medication, they can pay for a more expensive drug that is metabolized differently but avoids a more expensive hospital visit later.
The long-term play is understanding what other efficiencies can be gleaned from data.
“We can do this test and help our members more immediately through this pharmacogenomic use case for our members. We’re able to now collect this data, and we can do retrospective analyses on where else we might be able to have an impact.”
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