The Hol Picture

The HM Treasury in the United Kingdom recently announced an exciting and truly forward-looking initiative for healthcare: a package of government funding, called the Life Sci for Growth package, to fuel research and bring treatments to patients faster. There are many impressive projects being funded, from clinical trial improvements to preparation efforts for future public health emergencies. 

Consider an emergency room doctor who is caring for a patient who has been hospitalized after a suicide attempt. When she consults his chart, she can see that he has been diagnosed with depression, but the structured data that is immediately available does not provide much additional context. 

Huge amounts of data are collected throughout a person’s journey through the behavioral healthcare system. From demographic data captured during intake to in-depth conversations between patients and clinicians about symptoms, daily activities, and goals, most of the information captured about a patient becomes part of their electronic health record (EHR). 

As a mental health clinician and researcher, I have seen firsthand how our understanding of the role that biological and socioenvironmental factors play in mental health has evolved over time. For many years, the debate over nature vs. nurture dominated discussions in the field, but more recent models have focused on the interaction between genes and the environment, such as the diathesis stress model.

I recently led a team of researchers in a large-scale observational study, which was accepted and published by The Lancet Psychiatry. To our knowledge, our study was the first to study the impact of early clinical trajectory across multiple psychiatric diagnoses.

I recently had the pleasure of joining Real-World Wednesday, a conversation hosted weekly on Clubhouse covering various topics about real-world data. First off, I’d like to thank the hosts of the RWD-RWE Club, Matt Veatch and Aaron Kamauu, for the invitation and the engaging discussion.

Today, Digital Health New York (DHNY) released its Q1 Healthcare Innovation Report, of which we were honored to be a part.

At Holmusk, our vision is to provide fit-for-purpose real-world data that fuel research and innovation in behavioral health. With tons of data captured each day as patients move through healthcare systems—much of it in unstructured data fields—a lot goes on behind the scenes, as we ensure that this information is available and usable for research. Below, you’ll find a quick overview on the types of data that are included in the NeuroBlu Database—as well as the process data go through to ensure they are fit-for-purpose.

Earlier this month,  the Substance Abuse and Mental Health Services Administration (SAMHSA) released its annual National Survey on Drug Use and Health (NSDUH), which examined substance use and mental health data from 2021. Although the survey has been administered since 1971, SAMHSA called this year’s “the most comprehensive report on substance use and mental health indicators” that the organization has released to date.

Over seven years ago, I founded Holmusk with the vision that advances in technology and data science could be harnessed to improve health care. Over the company’s lifespan, the vision has crystallized, and we decided to focus first on an area of dire need—behavioral health. We have made great advancements in this space, many of which would not have been realized without the creation and nurturing of fruitful and supportive partnerships.