Evidence map›Paper›PMID 41313172›Full record

ArticleJMIR formative research2025

Populations and Health Domains Served by Direct-to-Consumer Digital Health Companies in the United States, 2011-2023: Cross-Sectional Study.

Ashwini Nagappan, Xi Zhu, Corrina Moucheraud, Olivia S Jung

Abstract read
In one paragraph

Article in JMIR formative research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ashwini NagappanDepartment of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles, 650 Charles Young Dr. S, Los Angeles, CA, 90095, United States, 1 310 825 2594.ORCID 0000-0001-5518-102X
Xi ZhuDepartment of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles, 650 Charles Young Dr. S, Los Angeles, CA, 90095, United States, 1 310 825 2594.ORCID 0000-0003-2194-7327
Corrina MoucheraudDepartment of Public Health Policy and Management, School of Global Public Health, New York University, New York, NY, United States.ORCID 0000-0001-7862-7928
Olivia S JungDepartment of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles, 650 Charles Young Dr. S, Los Angeles, CA, 90095, United States, 1 310 825 2594.ORCID 0000-0001-9998-6022

Funding

NRSA Training CoreTL1TR001883 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ALEX BUI, Nina Thawata Harawa · 2016 to 2026
$8.6M
NCATS NIH HHS TL1 TR001883
6 · The paper itself

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 health care delivery by engaging consumers directly and operating largely outside of traditional health care systems. Despite their increasing presence, little is known about the populations that these companies serve, the health domains they address, and the technologies they use. Understanding these characteristics is critical for evaluating the quality of services provided, implications for health care costs, and impact on health equity. Objective: This study aimed to describe the growth and focus of DTC digital health companies in the United States from 2011 to 2023, examining their target populations, health domains, and differentiating technologies. Methods: We conducted a cross-sectional descriptive analysis using the Rock Health Digital Health Venture Funding Database, which systematically tracks US digital health companies that have received at least US $2 million in publicly disclosed funding. This database was selected because of its scope, consistency, and detailed coding of company characteristics. Of the 2652 digital health companies identified between 2011 and 2023, 478 (18.0%) were classified as exclusively pursuing a DTC model. We extracted and validated data on company characteristics, including founding year, operational status, funding levels, target populations, health domains, and technologies used. Descriptive analyses of frequencies, medians, and IQRs were conducted. Results: Between 2011 and 2023, the number of DTC digital health companies grew steadily, with the highest number founded in 2020 (59/478, 12.3%). As of 2023, 445 (93.1%) of the 478 companies remained active, and 6.9% (n=33) had ceased operations. Across all 478 companies, total venture funding ranged from US $2 million to US $570 million (median US $9.6 million, IQR US $4.0-$25.0 million). Companies focusing on rural or Medicaid populations (n=10, 2.1%) were rare and had lower median funding (median US $5.0 million, IQR US $3.5-$13.4 million). Women were the most targeted population (n=70, 14.6%), followed by children and adolescents (n=36, 7.5%), and older adults (n=25, 5.2%). Mental health was the most common health domain (n=80, 16.7%), followed by reproductive and maternal health (n=71, 14.9%). Telemedicine (n=108, 22.6%), wearables and biosensors (n=93, 19.5%), and artificial intelligence or machine learning (n=63, 13.2%) were the most frequently adopted technologies, with their use varying by population and health domain. Conclusions: As DTC digital health companies increasingly influence where and how care is delivered, systematic monitoring of their scope and characteristics is essential to evaluate whether they contribute to equitable access to care. Our findings provide a foundation for assessing whether these models are effectively addressing health needs, reaching diverse populations, and lowering health care costs.

Indexed as

Delivery of Health CareDigital HealthCross-Sectional StudiesDirect-to-Consumer AdvertisingHumansUnited Statesaccessdigital healthdirect-to-consumerhealth equityhealth services research

Identifiers

PMID41313172
PMCPMC12661595

What OpenQuestion holds

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.