Where We Are Now
Since our last non-spring-break-related update, we’ve had a tumultuous few weeks: dead week (which was also the week of our first demo day), finals week, and spring break (during which 3/4 of the team travelled to Japan, to attend a Bitcoin- and blockchain-focused conference). A lot has happened during that time, so we hope this post will serve to bring everyone up to speed on Torque’s current status and our plans for Spring quarter.
To understand where we are now, it helps to revisit how we started out: at the beginning of last quarter, we thought we were building an anti-counterfeiting supply chain management solution for pharmaceuticals. After talking to a lot of people, however, we decided it made more sense for us to disrupt some of the functionalities of Pharmacy Benefit Managers (PBMs) — specifically, the creation and negotiation of insurer formularies. As we see it, we can automate the aggregation of insurer purchasing power (like a PBM, but better), without siphoning off savings for profit.
Unfortunately, our system relies on a network effect — the more insurers we onboard, the greater the formulary overlaps we’ll be able to discover, and the greater the savings we’ll be able to generate. So we need to start on boarding, and fast — but for now, our system has virtually no appeal. So how will we convince insurers to work with us?
The answer, we think, lies in narrowing the focus of both our target users and the service we will offer. During spring quarter, we’ll focus specifically on self-insured employers — that is, employers who assume the financial risk associated with providing health insurance to their employees. Even more specifically, we’ll focus on self-insured employers (SEIs) who rely on a large insurance provider for third-party administration (TPA) services. Big providers offering TPA services to SEIs make claims data (in a variety of formats) available to those employers, but this data usually isn’t analyzed — so oftentimes, SEIs don’t understand where there insurance spend is coming from, which is abnormal for such a large expense.
We’ll start out by performing data analysis on anonymized claims data for SEIs — for free. If the SEI fits the typical profile, the largest portion of their spend will be coming from a relatively small segment of their employees health needs: specialty drugs and treatments. PBMs tend to massively markup the prices of these treatments (and, even at their average wholesale price [AWP], these drugs are much more expensive than almost anything else). Because employees facing these sorts of health issues are unlikely to leave their jobs, these costs are typically the greatest contributors to an employer’s spend — and they often don’t know this. We’ll expose them to this helpful information free of charge — of course, in a beautiful and presentable format, as different from those messy CSV files as possible.
At this point, you’re likely wondering how Torque will survive financially. That comes next. Once we’ve identified these disproportionate expenditures on highly marked up specialty drugs, we can (with a much smaller markup) direct these employer to specialty pharmacies (which often do mail-order, and are capable of handling the sort of volume we would generate in the start), significantly reducing their overall spend. At this point, we’ve created a relationship with this employer as a client — and once we have enough of these relationships, we can begin the transition to more general formulary creation and price negotiation for non-specialty drugs.
For now, our priority is creating these relationships with SEIs at small- to mid-size employers. We’ll start by advertising on social media to targeted audiences, and by having conversations with founders in the Stanford alumni network who would be willing to work with us while we are still unproven.
Keep checking in — we anticipate lots of interesting updates over the next ten weeks.
