Derek Halpern

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Derek Halpern

Derek Halpern

@derekhalpern

Co-founder of Truvani. Also had a popular YouTube channel about business. All tweets are my own opinion.

Miami Beach, FL Katılım Temmuz 2008
1.1K Takip Edilen58.5K Takipçiler
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Derek Halpern
Derek Halpern@derekhalpern·
When I cofounded Truvani, I had zero experience in creating my own consumer packaged goods and selling them. This inexperience turned into one of our biggest strengths. Here’s why…
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Derek Halpern
Derek Halpern@derekhalpern·
This is written as satire, but rings too true.
Peter Girnus 🦅@gothburz

I am the VP of Claims Optimization at one of the five largest health insurers in the United States. I do not practice medicine. I have never practiced medicine. I have an MBA from Wharton and a background in supply chain logistics. Before healthcare, I optimized fulfillment times for an e-commerce company. The transition was seamless. In e-commerce, the product is a package. In healthcare, the product is a claim. Both are routed, processed, and occasionally denied. The denial rate for packages was 0.3%. The denial rate for claims is 34%. The margins are better in healthcare. The algorithm is called nH Predict. We did not name it. The vendor named it. The vendor is a subsidiary of our parent company, which means we named it, but through a subsidiary, which means the liability sits in a different filing cabinet. nH Predict processes a claim in 1.2 seconds. A board-certified physician reviewing the same claim takes forty-five minutes. We replaced the forty-five minutes. The replacement was described in the board presentation as "clinical decision support." It supports the decision to deny. My team processes 1.4 million claims per quarter. The algorithm reviews each one against a predictive model trained on historical outcomes. The model predicts how long a patient will need post-acute care — rehabilitation, skilled nursing, home health. Then it recommends a coverage duration. The recommendation is almost always shorter than the treating physician's recommendation. The physician sees the patient. The algorithm sees the data. We trust the data. The data is cheaper. Here is what I am not supposed to tell you. We know the reversal rate. We have always known the reversal rate. When a patient appeals a denial, 90% of denials are reversed. Ninety percent. This means nine out of ten times, the algorithm was wrong. Not arguably wrong. Not borderline wrong. Reversed-on-appeal wrong. The appeal is reviewed by a human physician. The human physician looks at the same information the algorithm looked at and reaches the opposite conclusion. This has been happening for three years. We have not recalibrated the algorithm. Recalibration would increase the approval rate. An increased approval rate would decrease the margin. The margin is reported to shareholders as "medical cost ratio improvement." Nobody asks what the words mean. The business model is the gap between denial and appeal. Sixty-three percent of patients do not appeal. They receive the denial letter — which is eleven pages, single-spaced, with the appeal instructions on page nine in 9-point font — and they give up. They pay out of pocket. They skip the rehabilitation. They go home early. Some of them fall. Some of them are readmitted. The readmission is a new claim. The new claim is processed by nH Predict. The 37% who appeal wait an average of 43 days for a decision. Forty-three days of uncertainty about whether their insurance will cover the care their doctor prescribed. During those 43 days, many of them have already been discharged. The appeal is retroactive. The care is not. I have a dashboard. The dashboard shows denials per day, appeals per day, reversals per day, and a fourth number that is the most important number: the non-appeal rate. The non-appeal rate is 63%. I report this number weekly. It has never been described as a problem. It has been described as "patient engagement efficiency." When the non-appeal rate rises, I am congratulated. When it falls, I am asked what happened. The class action lawsuit uses the phrase "bad faith." The plaintiffs allege we substituted algorithmic predictions for independent medical judgment. This is accurate. The substitution saves $2.1 billion annually. The lawsuit seeks $1.3 billion. Even if we lose, the math works. Three years of $2.1 billion is $6.3 billion. Minus $1.3 billion is $5 billion. The settlement will include the phrase "without admitting wrongdoing." The settlement always includes that phrase. I am the Vice President of Claims Optimization. My job is to optimize the distance between what your doctor recommends and what your insurer pays. The distance is the product. I have been optimizing it for three years. The algorithm gets faster. The appeals process gets longer. The font on page nine gets smaller. The margin gets wider. My annual performance review cites "exceptional contributions to medical cost ratio improvement." The review does not mention the 90% reversal rate. The review does not mention the 63% non-appeal rate. The review does not mention the patients. The algorithm does not practice medicine. I want to be clear about that. It predicts. It denies. It profits. The prediction, the denial, and the profit are three separate functions. The separation is important. For legal purposes.

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Cherene
Cherene@ChereneAubert·
@TaylorHoliday @derekhalpern Lots of new ai-first saas coming out a fraction of the cost of SaaS that launched 2 years ago. Everything is a pendulum
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Derek Halpern
Derek Halpern@derekhalpern·
I'm looking for a video editor to work on Reels. Shorts. Tiktoks. etc. Fast paced editing, creating stories from b-roll (and text on screen), and a strong eye for viral content. It's for Truvani and even tho the content will be used as advertisements, I'm more interested in people who know how to create viral memes instead of ads. Reply with your social media link if interested.
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Derek Halpern
Derek Halpern@derekhalpern·
@nikitabier @robertoblake You guys are on top of this! While we are at it, should start banning people for 90 days who don’t disclose when they are doing a sponsored post or not as well.
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Nikita Bier
Nikita Bier@nikitabier·
Today we are revising our Creator Revenue Sharing policies to maintain authenticity of content on Timeline and prevent manipulation of the program. During times of war, it is critical that people have access to authentic information on the ground. With today’s AI technologies, it is trivial to create content that can mislead people. Starting now, users who post AI-generated videos of an armed conflict—without adding a disclosure that it was made with AI—will be suspended from Creator Revenue Sharing for 90 days. Subsequent violations will result in a permanent suspension from the program. This will be flagged to us by any post with a Community Note or if the content contains meta data (or other signals) from generative AI tools. We will continue to refine our policies and product to ensure X can be trusted during these critical moments.
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Derek Halpern
Derek Halpern@derekhalpern·
If you thought there was too much noise 10 years ago… It’s only getting worse. The people who can find signal - truth, information, real content and experience - will continue to win. This is why I like Xs new topic feature.
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Derek Halpern
Derek Halpern@derekhalpern·
“It’s real, it’s not ai” just wasnt something you heard in the English language until recently,
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Derek Halpern
Derek Halpern@derekhalpern·
@OisinO Other than your Twitter, how come I almost never see recharge marketing anything whether it’s features, new product offerings or even base product.
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Oisin
Oisin@OisinO·
My company (Recharge) is the 3rd largest Shopify App: - We do well >$100M in ARR, profitably. - I've raised over $250M in capital. - 440+ people are helping me build this. Ask me anything about building a business and I will answer.
Oisin tweet mediaOisin tweet media
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Derek Halpern
Derek Halpern@derekhalpern·
If there’s one thing I’m proud about the team at Truvani is we do things fast, at scale. When we wanted to do influencer gifting for example… We started with 50 gifts. Then 250. And next thing you know we are sending 5000 per month to around 65,000 people in total. When we wanted to do events, we did 1 and then 10 and now we do up to 200 per month. Now we wanted to scale DTC ads and in less than 3 months we have 6xed our spend without raising cac too badly. In business ideas matter, but speed of execution matters more. We haven’t always been the best but we are getting better.
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Jason Fried
Jason Fried@jasonfried·
@sampittko @dhh That would be a fun podcast to do, but someone appropriate would have to invite us on to do it.
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Samuel Pitonak
Samuel Pitonak@sampittko·
I wanna understand the duo @jasonfried & @dhh more. How do they complement each other etc. what are the dynamics of their relationship. Is this even possible? Any interesting podcast/video to listen to/watch? Loving the podcast so far: youtu.be/BdDCtMA1gSw
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Drew Fallon
Drew Fallon@drewfallon12·
what’s a good way to track your funnel / ongoing campaign effectiveness?
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Mehtab | Karta Ventures
Mehtab | Karta Ventures@MehtabKarta·
Anyone here do a ton of events for their brand? We are doing 200+ this year and I’d like to trade notes. 📝
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Derek Halpern
Derek Halpern@derekhalpern·
“Yeah — good catch. The circled image I returned is not a markup of your original photo. I used an image tool that generated a new image, and it inserted a tiger instead of simply circling something already there. That’s my mistake. Looking at your original picture closely, I don’t actually see a tiger in this still frame (it may be in the video at another moment, or it’s so obscured that it’s not visible in this particular screenshot).” Yes, it’s a pointless find the tiger experiment. But I feel so cheated. What if they do this with actual information or statistics? What if ai distorts reality just to provide positive responses as if it knows the answers? I’ve been weary of ai responses and this is why.
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Derek Halpern
Derek Halpern@derekhalpern·
At this point I think I’m crazy. I compare the two images and it seems like ChatGPT just put a tiger in there that didn’t exist. I say, “Did you just add the tiger there? It’s not in the original pic. And the response is downright scary:
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Derek Halpern
Derek Halpern@derekhalpern·
This is why I can’t trust ChatGPT. It seemingly lies. Intentionally. Look at this example. I ask ChatGPT to find the tiger hiding in this picture. I use the prompt “Where is the tiger hiding in this picture”
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