Cardiogram Differentiates in Analytics Field by Enticing its Clients to Become Data Providers

 

Most smartwatches today are equipped with heart rate monitors and continuously track user heart rates over the entire day. While developers are certainly working on additional biosensors, heart rate tracking is mature enough to be producing reliable heart rate data. As such, developers can begin to expand the use case of smartwatches by taking advantage of existing data for applications like chronic disease diagnosis and management. Cardiogram is looking into precisely this opportunity and is offering a solution for employers to reduce medical spending by helping with the diagnosis of undiscovered chronic diseases.

USE CASE AND BUSINESS IMPACT

Cardiogram analyzes heart rate data collected from wearables and flags employers who have potential undiagnosed chronic conditions. After an FDA-cleared diagnostic test, Cardiogram will cover the cost for negative diagnosis and only file for medical claims if the result is a true positive. Employers do not need to pay a subscription fee for employees, meaning fees are only incurred if Cardiogram successfully helps diagnose a previously undiagnosed condition. The company is likely lowering the barrier of entry for potential employers in exchange for heart rate data, which contributes to the continual improvement of the algorithm. While the algorithm is not FDA-certified, it is co-developed with University of California San Francisco's cardiology department; to date, the company has conducted clinical studies with its algorithm for predicting cardiovascular risk, screening for atrial fibrillation, sleep apnea, and hypertension.

LUX TAKE

Much like how Facebook's early operations were preparation work for its targeted advertisements today, Cardiogram is enticing employers to participate in the program in exchange for data with an attractive business model. Lowering the barrier to entry is crucial for analytics companies, as securing verifiable data sources helps not only with the technology development but also with building a strong client base for scaling the business. In an era when advanced analytics buzzwords are being used loosely, clients should understand that data integrity and verification are crucial to the development process of any analytics platforms. Having a business model where clients are enticed to provide data will serve as a strong differentiator.

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