- The cost of healthcare in US will go up for everyone, as employers will pass the buck to employees and the uninsured will have to pay.
- Even standard procedures have high price volatility. If you ask how much your hospital will charge for an above $5,000 procedure, by explicitly asking how much they charged for the last 5 patients, they have no answer, as if they don't keep financial records. Would you buy a car if the car dealer has no idea how much they will charge you, until two months after the purchase? And then you hear your neighbor got exactly the same car from a different dealer for half the price? Any other type of businesses would quickly go bankrupt if using such business practices.
- Despite hiring the brightest people (surgeons, doctors) hospitals lack basic analytic talent for budgeting, pricing, forecasting. They can't create a statistical financial model that includes revenues (insurance payments etc.) and expenses (clients not paying, labor, drug costs, equipment, lawsuits, etc.)
- Patients not analytically savvy, don't know that they are financially abused, want to get plenty of useless tests and expensive procedures for minor issues, and ready to sue for no reason. But things are changing. Yet no patient (except myself?) ever mentioned that his budget is say $2,000 for XYZ procedure, and that he won't pay more and will cancel or find another provider if his budget is too low.
- Volatility is expected in prices, but must be controlled. If I provide consulting services to a client, the client (like any patient) has a finite budget, and myself (like hospitals) have constraints and issues (I need to purchase good quality software, the data might be much more messy than expected, etc.)
An Internet start-up offering prices for 20 top medical procedures, across 5,000 hospitals and 20 patient segments. Prices would come from patients filling a web form or sharing their invoice details, and partners such as cost-efficient hospitals willing to attract new patients. Statistical inference would be made to estimate all these 20 x 20 x 500 = 200,000 prices (and their volatility) every month based on maybe as little as 8,000 data points. The statistical engine would be similar to Zillow (estimating the value of all houses based on a limited volume of sales data), but it would also have a patient review component (like Yelp), together with fake review detection.
Revenue would be coming from hospitals partners, from selling data to agencies, from advertising to pharmaceutical companies, and from membership fees (premium members having access to more granular data).
Interested in creating this start-up? I could help you get started. Feel free to contact me at [email protected] or post a comment below if you are serious about this project.