
Clover Health, an insurance startup trying to use data to keep customers healthy - daddy_drank
https://www.bloomberg.com/news/articles/2016-12-07/silicon-valley-is-trying-to-reinvent-health-care-starting-in-new-jersey
======
roymurdock
_Uncle Sam pays Clover a monthly fee for each Medicare Advantage customer the
startup enrolls. The amount varies depending on where the person lives, but it
averages $850 before adjusting for chronic conditions or healthy habits, the
Medicare Rights Center says. Clover uses the money to pay members’ bills and
generates almost all its revenue from whatever is left over after reimbursing
doctors, hospitals, labs, pharmacies and other points of care. The company
offers plans with no monthly premiums or ones that go as high as $225. Clover
says the amount it gets from those payments and copays isn’t significant._

So it sounds like the company's biz model is to send nurses out in the field
to get senior citizens to enroll in Medicare, check up on them and collect
data, and sell them healthy lifestyle products (gym memberships, cooking
classes, etc.). As a 23 year old I'm not sure if this is any different than
what big insurance co's do for their Medicare enrollees.

The actual tech part seems to be the web portal/CMS (Django) and the storage
and management of this tangential customer data that is generated with each
visit:

 _Clover uses Python for all of our backend coding so using a pipeline
orchestration tool that is itself written in Python is valuable for us.
Airflow meets that requirement and it’s the tool we’ve chosen to manage all of
our pipelines._

Here's the actual coverage sheet if you want to compare with your/your
parent's plans:
[https://cdn.cloverhealth.com/filer_public/c4/a8/c4a894d0-000...](https://cdn.cloverhealth.com/filer_public/c4/a8/c4a894d0-000e-47b8-873e-92bd323db9bb/benefitssummary_carepointplan_2017.pdf)

Deductibles (excluding prescription drugs) are $6,700 annually. Someone maxing
out prescription charges would spend an additional $5,000 per year. I'm not
sure how that compares to a traditional provider.

Tangentially: I think we've almost stretched the definition of the word
"startup" into oblivion at this point. It doesn't mean anything to me anymore.

~~~
ubernostrum
(I work at Clover)

 _As a 23 year old I 'm not sure if this is any different than what big
insurance co's do for their Medicare enrollees._

The difference is most insurers would say something like "OK, out of X
thousand Medicare-age people, Y of them will have this expensive health
problem over the next year, are we profitable when that happens?". We say "OK,
how can we identify the people most at risk of that and use preventive care to
head it off?" So while most insurers just take the statistics as a given and
budget for it, we're trying to change the statistics.

 _storage and management of this tangential customer data_

I think you vastly underestimate how much low-hanging fruit there is in this
field, and how difficult getting and maintaining good data (so you can find
the things you can do) really is :)

~~~
Justin_K
Every health plan has been doing this for years. They too have treasure troves
of data... they have care coordinators, patient centered medical homes, etc.
So, how are you actually trying to change the statistics?

~~~
ubernostrum
This isn't my first insurance company. The typical experience in insurance is
that those tools mostly only come out once someone already _has_ the expensive
problem, and are used to manage the cost of it after the fact, rather than
prevent it from happening in the first place.

Also most insurance companies aren't really set up to _do_ preventive work to
the extent we do (which involves home visits from nurses and other clinical
staff, staying in touch and proactively reaching out when there seem to be
problems, etc. etc.), largely because they consist of essentially competing
divisions which each own a subset of the data and responsibilities and
jealously guard against every other division. I worked in a company like that,
once upon a time -- everyone had very clearly-defined limits to their
responsibilities (well beyond what privacy rules required) and even just
contacting someone in a different department to make them aware of a problem
or pass along a suggestion would trigger turf-war consequences.

I'm very happy to now be working with the opposite of that.

Finally, it's worth noting that although there are a lot of dismissive
comments about tech in this thread (and some of it I can understand -- most of
what we do is internal-facing and harder to promote as a result), the
perspective inside is pretty different. It's true there's not a ton we're
doing that's cutting edge and "sexy" tech (though we have open-sourced some
neat tools for temporalizing SQLAlchemy's ORM), but that's because health care
hasn't yet caught up to just the boring everyday things we take for granted.

There's an example that really drove it home for me, from about six months
ago. Claims are obviously a big part of what we're about, and so we have an
internal team that reviews processed claims for accuracy. They have to check
against a pretty complex set of Medicare claim-processing rules, part of which
involves rules about combinations of medical procedures (i.e., Procedure A
might be allowed but only if alongside Procedure B, or A might only be allowed
_without_ B, or A and B might just be independent and can both appear or not
appear). The canonical source for that data is... gigantic Excel spreadsheets
of all the procedure codes and rules. And so the claims-review team would open
up Excel, type in a code, wait five minutes while it churned to find the code,
then repeat for the next code, etc.

An engineer saw this and spun up a two-day project to ingest those
spreadsheets (on an ongoing basis, since they change over time) into a
database and wrap a search interface around them which allowed punching in all
the codes and getting back a list of rules and an indicator of whether they'd
been violated.

To tech people that's so mundane it almost puts you to sleep, and makes you
say "wait, that's _it_?". But to healthcare people, it was a gigantic step
forward. So many people from health backgrounds came from places that never
let them work side-by-side with tech staff and figure out what was possible
(or where all tech was outsourced to vendors with opaque planning and feature-
request processes), which is why so much of healthcare tech feels decades out
of date.

So just having tech and medical/insurance people in the same room, working and
talking together every day, acts as a pretty impressive multiplier compared to
traditional insurance companies.

~~~
coldcode
Also worked at a Healthcare (claims processing) company owned by multiple
giant insurance companies. I never thought of it as healthcare but just health
plumbing, all we did is push HIPAA data from point A to point B. And we also
had horrible turf wars and insanely stupid projects that did no one any good.

What you are doing is far more interesting. It was pretty obvious that there
is a lot one can do with data, assuming you can deal with the HIPAA
limitations. One ill person is hard to get much from, but 10000 is different
story.

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gmarx
Poor article. The first example they give (trying to reduce the risk of
developing diabetes in an 83 yo by switching her to brown rice) is stupid,
wishful thinking. Then several paragraphs which could be shortened to "they
use data to improve patient outcomes". Finally towards the middle they mention
some good examples of data driven interventions. Looks like a promising
company if you skip most of the article :)

------
dr_
Interesting but they are not the only ones doing this. United and aetna are
collecting data as well, and also employ nurses that follow patients into
their homes or other settings. The data operation is what is emphasized in
this article, but it really remains to be seen how much the data can have an
impact on people's overall health - preventing hospitalizations, making sure
patients take their medications etc. maybe it can guide clover and let them
determine where to allocate manpower - but in the end it's still the manpower
that matters.

from my experience, a lot of it depends on having the right family, and
perhaps community, support structure in place.

------
bkudria
Our Tech blog has some more in-depth dives into what we do and how:
[https://technology.cloverhealth.com/](https://technology.cloverhealth.com/)

~~~
mtw
I skimmed through the posts but apart from the website that uses Django and
marketing that needs analytics, it's not clear how you use tech?

I was hoping there would be insights or code on the "inputs/outcomes" seen on
the title

I'm doing [http://outcomereference.com/](http://outcomereference.com/) so i'm
esp. interested in this

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john_gaucho
I'm very interested / concerned about what is going to happen to the insurance
industry as companies get more and more data about their clients.

I'm a fairly healthy person (at least right now), and I'm not sure how I feel
about it.

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tcbawo
I hope that we see technology and analysis used to improve outcomes rather
than to screen or filter the customer pool. I worry that this will happen
without protections in place.

~~~
bkudria
One of the nice benefits of being a Medicare Advantage provider is that there
is a set comprehensive of member-oriented regulations and protections in place
that force us to benefits the member. In this case, the government pays us on
a risk-adjusted basis (based on CMS-set risk-adjustment factors.) We are
therefore incentivized to comprehensively collect and document every member's
risk, so that we are able to manage their medical expenses. (Also worth
noting: we are required by law to spend 85% of our payments directly on member
care.)

------
yourapostasy
This orientation towards data is admirable, but likely is an impossibly uphill
climb without a corresponding emphasis upon _expanding_ collected types of
data. Which is expensive. And is why US insurance companies---who pay for this
kind of data out of tests---won't be leading the charge towards a data-centric
or Big-Data-centric health outcomes evolution in the medical field. The
mainstream medical field has not yet recognized the possibilities, either.

Let's take the Type 2 diabetes example given in the article.

No mention is made of putting a Continuous Glucose Monitor on the 83-year old
patient, to graphically show in real time the impact white rice has upon her
blood sugar.

No mention is made of five additional antibodies tests to identify Latent
Autoimmune Diabetes in Adults (LADA), which looks _a lot_ like Type 2 in its
early stages, but likely needs to be treated as Type 1 as early as feasible
according to some very recent research.

No mention is made of regular tracking of her HbA1c, fructosamine (gives a
14-day instead of ~115 day window into long-term blood sugar management), and
1,5-anhydroglucitol (indicates time spent with hyperglycemia).

Not to speak of doing those three areas on a regular, monthly/quarterly basis.
It is very rare in the US to do all of that even on an annual basis; at best,
the common practice is HbA1c once a year. While metabolic syndrome leading to
diabetes is a huge drain on US insurers, aggressive data-led syndrome
reversion is _de facto_ not recognized by either the mainstream medical field
nor insurance industry.

There is lots more data they could gather than what I mentioned here, but all
they did instead was suggest "try to eat brown instead of white rice". She
should try not eat rice (and other carb-heavy food) _at all_ for a month, and
see if that improves her blood sugar numbers. While the fitness community has
already empirically identified that diet is 90% of success unless you are a
genetic anomaly, the food, medical and insurance industries still push the
idea upon patients they need to go out and exercise more, and only tinker
around the edges of their diets (unless you are fasting/caloric-restricting,
going very low-carb, going vegetarian, going raw food, _etc._ , most Americans
idea of a diet change by adding a couple salads a week, picking "low fat"
packaged food and so on is just tinkering).

This doesn't even get into monitoring controlled changes in habits, measuring
the impact upon the data, and using those results to guide further changes.
Nor have we even touched upon the lack of incentives in the US for companies
seeking to "disrupt" medicine through holistic, integrated process changes
instead of "product" like pharma or medical devices: if company X can provably
intake Y number of customers with say, metabolic syndrome or even Type 2
diabetes, and achieve a reversion rate of Z% with negligible (<5%) backsliding
5+ years out from date of reversion, monetizing that proprietary process is
limited to either being a provider (in which case you're squeezed by the
insurance companies with take-it-or-leave-it negotiations) or an insurer (in
which case you're too spread out covering other ailments to really capitalize
upon the proprietary knowledge). I suspect the lack of incentive structures is
similar in nations with national health plans.

~~~
leftpad
Clover collects tons of data about its patients, probably more than most
health plans. They may only have 19,000 patients, but they also like to talk
about how their data is very wide. Most health plans I've worked with do a
terrible job of even collecting the simplest types of data and outsource a
vast majority of their data collection processes. These health plans have
aging technology and a reluctance to use new and open source tools. A great
example of this is how many health plans manage to somehow overpay claims to
the tune of 10-100s of millions of dollars per year, and have no idea why.
There's an entire cottage industry devoted to solving this problem for
insurers.

Most of the tests you mention above are wasteful for your typical Medicare
Advantage enrollee. There's a ton of low hanging fruit for a start-up like
Clover to make a meaningful impact. Trying to change human behavior through
diet or exercise is incredibly difficult, especially for those from
disadvantaged communities or of lower socioeconomic status. Kudos to Clover to
trying to make a marginal impact on that front; most insurance plans wouldn't
do anything.

~~~
yourapostasy
> Most of the tests you mention above are wasteful for your typical Medicare
> Advantage enrollee.

A good point to discuss. Perhaps I'm overly optimistic about people in
general, but how do we _know_ , _a priori_ to a data-centric healthcare model
applied to a patient, about their participation? These tests are only wasteful
in the context of the current care model, which stipulates that once you have
Type 2, there is a lockstep progression of increasingly invasive and expensive
medication and interventions, graduation to insulin injection, and culminating
in early death from complications? In the face of that kind of prognosis, it
is not at all surprising that any additional tests are considered futile by
both medical practitioners and patients alike. But if the patient was offered
via data-centric care a clearer window to their condition, amplified proactive
participation in care management with negative feedback loops tamping down
undesirable fluctuations, and in the case of Type 2 or metabolic syndrome the
clear goal of reversion (though not a cure) and drastically improved eventual
outcomes, why do we assume that even elderly patients on Medicare Advantage
would not statistically respond well as a whole population? I dunno, this
isn't my domain expertise, so I'm honestly asking these questions; if there is
the equivalent of behavioral economics studying patient behavior, then perhaps
that field has the answers I'm seeking.

> There's an entire cottage industry devoted to solving this problem for
> insurers.

I'd like nothing more than to see these efforts succeed, look forward to
following the progress.

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foolinaround
What we need to see is the ability for the patients to be able to own and
transfer that data ( like a Google takeout ).

~~~
demolish
not sure that would work really - could lead to falsified medical records to
claim from state/drug abuse/(falsely) claiming mental illness in an attempt to
absolve people of crimes in court etc

