How to save millions of dollars in health care costs as an employer
We have built analytics and AI to help you optimize your benefits and save millions.
As a CFO, your top line-item for the year might be salary. The second-biggest cost might be health care.
As a CEO, Director of Human Resources, Benefits Manager, Health Fund Analytics team, you might also be aware that you can reduce this cost and improve health outcomes for your employees.
Did you know you can save millions of dollars from how much your organization pays for health care?
What we can do for your organization
We help reduce how much your organization spends on health care using a simple process:
- We standardize your claim feed that contains the billing codes for employees' visits to doctors and hospitals alongside medications.
- We benchmark the most expensive billing codes in the claim feed to our data from hospitals and insurers.
- We help you restructure your benefits (by designing employee incentives and copays, through an RFP, negotiation, or a member portal).
It's that simple. Why isn't your organization doing this? We'd love to help and work with a team of analytics experts, AI researchers, and bioinformatics & health care analysts.
Organizations we have worked with have already reduced their health care costs by millions of dollars.
For example, we have worked with the Lehigh County controller who reduced health care costs by $6M out of a $23M spend for the 2,500 employees he monitors accounts receivable for.
Some organizations we work with are even able to give wage increases to their employees (like 32BJ).
How to work with us
Reach out to us today to work with us: send us an email at firstname.lastname@example.org.
Contracts start at $20,000 to complete steps 1 & 2. This will give you an estimate of how much you can save in a dashboard such as this visualization of 106,000+ line items at a major hospital in NYC: https://payless.health/hospital/mount-sinai.
We have worked with claims data representing tens of millions of patients, published academic research on health equity, designed AI systems to find patterns in health data.
We do this work as a non-profit to ensure trust and transparency and that reducing cost improves rather than harms health outcomes throughout the system.