JMIR Publications

ABSTRACT

Background:

Direct-to-consumer (DTC) digital health companies, offering services such as on-demand prescriptions, mental health apps, fertility tracking, and at-home diagnostics, have become more common in the United States. These companies represent a shift in healthcare delivery by engaging consumers directly and operating largely outside of traditional health systems. While questions remain about the quality of services provided and their implications for healthcare costs, addressing those issues requires establishing who these companies are, the populations they serve, the health domains they target, and the technologies they use.

Objective:

To characterize the growth of DTC digital health companies in the U.S. from 2011 to 2023, with a focus on target populations, health domains, and technology differentiation.

Methods:

We analyzed data from the Rock Health Venture Funding Database, a continuously maintained dataset that systematically tracks digital health funding activity in the U.S. This database was selected because of its scope, consistency, and detailed coding of company characteristics. We identified U.S. DTC digital health companies that received at least $2 million in publicly disclosed funding between 2011 and 2023. We extracted and validated data on company characteristics, including founding year, operational status, funding levels, target populations, health domains, and technologies used. Descriptive analyses were conducted to examine trends and distribution across key dimensions.

Results:

Between 2011 and 2023, there has been a steady growth in number of DTC digital health companies. We identified 478 DTC digital health companies, finding that women were the most targeted population (14.6 percent), mental health was the most common health focus (16.7 percent), and telemedicine was the most adopted technology (11.6 percent).

Conclusions:

As DTC digital health companies continue to shape how care is accessed and delivered, understanding their scope and characteristics is essential to evaluate their broader impact. Our findings provide a foundation for assessing whether these models are effectively addressing health needs, reaching diverse populations, and lowering healthcare costs.