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Longevity Briefs: Digital Health Innovations Have Huge Potential, But Where’s The Evidence?

Posted on 21 July 2022

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Longevity briefs provides a short summary of novel research in biology, medicine, or biotechnology that caught the attention of our researchers in Oxford, due to its potential to improve our health, wellbeing, and longevity.

Why is this research important: Thousands of digital health startups are seeking ways to apply new technologies and theories to old healthcare practices. This includes everything from mental health apps that provide online therapy sessions to applying automation and machine learning to disease prevention and treatment. Excitement for these innovations has attracted hundreds of millions of dollars in investments, but how many of these companies have actually shown that their technologies can have a meaningful impact?

What did the researchers do: In this study, researchers gathered data on 224 health tech startups. Each one was given a “clinical robustness” score, which was simply equal to the number of clinical trials they had completed, plus the number of regulatory filings they had made with the FDA (Food and Drug Administration).

Key takeaway(s) from this research: The numbers turned out to be quite disappointing: almost 100 of the 224 companies had a score of 0, and the average score of all companies was 2.5. Companies made an average of 1.3 public claims about their product’s impact, suggesting that many of them either wanted to keep their data private or had insufficient supporting data to begin with.

While the scarcity of completed clinical trials is disheartening, this is a fairly crude measure of a technology’s potential impact. Quality of evidence, both from clinical trials and elsewhere, is also important, and was not taken into account here. The low scores don’t necessarily mean that digital health startups are failing, but perhaps that they aren’t being sufficiently pressed for evidence. Investors don’t typically feel the need to see convincing clinical data when deciding whether or not to back a new company.

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    Assessing the Clinical Robustness of Digital Health Startups: Cross-sectional Observational Analysis:

    Researchers tried to calculate the impact of health tech companies. It sent startups into a tizzy:

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