Videra Health Named to MountainWest Capital Network’s 2025 Utah 100 Emerging Elite

Videra Health Logo

Orem, UT, October 17, 2025 – Videra Health, a leading AI platform for behavioral health providers, today announced it was named to the 2025 Utah 100 Emerging Elite category, MountainWest Capital Network (MWCN)’s annual list of the fastest-growing companies in Utah.
Videra Health was honored at the 31st annual Utah 100 Awards program, held at the Grand America Hotel in Salt Lake City.

“We’re honored to be recognized among Utah’s Emerging Elite,” said Loren Larsen, CEO of Videra Health. “Utah’s innovation community has helped to fuel our growth and mission to make behavioral healthcare more proactive, accessible, and effective through AI. This
recognition affirms our commitment to improving patient outcomes and advancing care both locally and nationwide.”

“We congratulate all of this year’s Utah 100 companies for building outstanding businesses and making strong contributions to Utah’s economy,” said Chris Badger, Chairman of the MWCN Utah 100 committee. “These companies further advance Utah’s standing as an excellent place to do business.”

Recipients of the Utah 100 Emerging Elite were chosen as a Utah business with great prospects for future growth and success.

Videra Health’s rapid growth reflects its unique approach to behavioral healthcare, combining AI-driven insights with real-world clinical applications. The company has expanded its platform to serve a growing network of providers, helping them identify at-risk patients, optimize care workflows, and improve outcomes. By generating actionable patient data and insights at scale, Videra Health also creates opportunities for healthcare and pharmaceutical partners to better understand treatment patterns, support clinical decision-making, and enhance patient engagement. These measurable achievements align with the Utah 100 Emerging Elite’s focus on recognizing companies with strong growth potential and market impact.

Videra Health team at t he Utah 100 2025 Awards Event
From left to right, members of the Videra Health team: Brad Grimm, Madeline Cheney, Byron Clark, William Burk, Brett Talbot, Mike Henneman, Mel Walker, and Sterling Mason.

About MountainWest Capital Network

MountainWest Capital Network (MWCN) is the largest business networking organization in Utah, consisting of entrepreneurs, venture capitalists, consultants, legal professionals, bankers, and educators. MWCN seeks to promote and recognize business growth and capital development in the state through a variety of award programs and activities.

About Videra Health™

Videra Health is a leading AI platform for behavioral health providers and proactively identifies, triages and monitors at-risk patients using linguistic, audio and video analysis. The FDA-registered digital platform transforms how doctors and healthcare systems interact and track a patient’s journey, illuminating the hidden depths of patient behavior and outcomes. Videra Health connects providers and patients anytime, anywhere, between visits and post-discharge via written and video assessments that translate into actionable quantitative and qualitative patient data. The platform streamlines diagnoses, enhances care accessibility, optimizes workflows and drives down costs for providers and healthcare systems.

Videra Health Launches “Check on Mom,” the First Free AI-Powered Postpartum Depression Screener

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New initiative empowers moms with a confidential, stigma-free video screener for postpartum depression, powered by conversational AI

Orem, UT, September 23, 2025 – Videra Health, a leading AI platform for behavioral health providers, today announced the launch of Check on Mom, the first free, confidential AI-powered postpartum depression screener. The self-assessment tool empowers mothers to complete a private, video-based check-in using conversational AI that captures both verbal and non-verbal signs of postpartum depression (PPD) and generates results they can share with a provider.

Unlike traditional written screeners, Check on Mom uses video and AI language models trained specifically for healthcare to analyze both spoken words and non-verbal cues. This dual-layer approach provides deeper insights into maternal mental health, making it easier to distinguish between common “baby blues” and postpartum depression.

“Check on Mom is not just a digital tool, it is a public health resource,” said Loren Larsen, co-founder and CEO of Videra Health. “By showing what is possible with AI-powered video screeners, we are opening new opportunities for earlier detection and better outcomes, not just in maternal health but across conditions where timely screening can make a real difference for patients and providers.”

How Check on Mom Works:

  • Free and confidential: No insurance, no cost.
  • Fast and convenient: Completed on almost any device, at any time, in less than three minutes.
  • Video-based and shame-free: Instead of static surveys, moms can speak openly and naturally about how they feel, and results are theirs to share
  • Clinically validated insights: Downloadable results can be shared with OBs, midwives, or primary care providers to guide next steps.

One in eight mothers experience postpartum depression, yet most go undiagnosed or untreated because screenings are inconsistent, stigma persists, and support often arrives too late. With Check on Mom, any mother can complete a short, video-based screener in just a few minutes and access secure results immediately without waiting for a six-week appointment or navigating health system barriers.

Check on Mom is more than a consumer resource. It is a proof point for how AI can transform condition-specific screening at scale. By applying conversational AI and video analysis, Videra Health is creating earlier pathways to care for conditions that are too often overlooked.

In addition to proprietary AI models already used to screen for depression, anxiety, trauma, and other conditions, the company most recently released TDScreen, the first AI-powered screener for tardive dyskinesia. These tools show how AI screeners can:

  • Expand access to early detection in underserved populations.
  • Deliver patient-centered insights that improve diagnosis and treatment.
  • Provide adaptable, condition-specific screening models that can be applied across therapeutic areas.

Across healthcare from patients and providers to pharma leaders, Check on Mom demonstrates how technology can expand access to postpartum depression screening, improve early detection, and support better patient outcomes. Videra is working to normalize maternal mental health conversations and demonstrate a new model for patient-first innovation.

Check on Mom is available free of charge for any mom wanting to screen for postpartum depression. Visit www.checkonmom.ai to learn more.

About Videra Health™

Videra Health is a leading AI platform for behavioral health providers and proactively identifies, triages and monitors at-risk patients using linguistic, audio and video analysis. The FDA-registered digital platform transforms how doctors and healthcare systems interact and track a patient’s journey, illuminating the hidden depths of patient behavior and outcomes. Videra Health connects providers and patients anytime, anywhere, between visits and post-discharge via written and video assessments that translate into actionable quantitative and qualitative patient data. The platform streamlines diagnoses, enhances care accessibility, optimizes workflows and drives down costs for providers and healthcare systems.

Protecting Innovation, Security, and Patient Trust in AI Healthcare

Healthcare AI security dashboard showing patient data protection features and compliance indicators

As CEO of Videra, I’ve watched the artificial intelligence landscape evolve at an unprecedented pace, particularly in healthcare AI security. While this evolution brings extraordinary opportunities for healthcare advancement, it also presents significant challenges that we must address head-on – especially regarding the proliferation of low-cost AI solutions from non-allied nations that may compromise our healthcare AI security standards.

The healthcare sector, especially in mental and behavioral health, requires the highest standards of security, reliability, and ethical consideration. When we develop AI tools for healthcare applications, we’re not just creating technology – we’re creating solutions that impact human lives, influence medical decisions, and handle incredibly sensitive patient data.

This year has seen a surge in AI products marketed to healthcare providers at significantly reduced prices, often at the expense of healthcare AI security. While competitive pricing is generally beneficial for market innovation, we must carefully consider the hidden costs and risks associated with AI solutions from nations with different data privacy standards, regulatory frameworks, and strategic interests than our own.

For pharmaceutical companies and drug developers, these risks are particularly acute. Drug development involves highly sensitive intellectual property and research data that, if compromised, could have far-reaching consequences for both innovation and national security. When AI systems process this data, they need to do so with absolute security and transparency about data handling practices.

In behavioral and mental health, healthcare AI security is paramount. These fields deal with some of our most vulnerable populations, and the AI systems supporting these services must maintain the highest standards of privacy and ethical operation. Providers need to know exactly how patient data is being processed, where it’s being stored, and who has access to it.

Key Healthcare AI Security Considerations for Providers:

1. Healthcare AI Security: Data Sovereignty and Protection

Your patient data should remain within U.S. jurisdiction, protected by our robust privacy laws and HIPAA regulations. Be wary of solutions that may route or store data through servers in countries with different privacy standards or data access laws.

2. Regulatory Compliance

Ensure any AI solution fully complies with U.S. healthcare regulations. This includes not just HIPAA, but also FDA requirements for medical devices and software as a medical device (SaMD).

3. Algorithmic Transparency

Understanding how AI makes decisions is crucial in healthcare. Providers should have clear insight into the training data and methodologies used to develop the AI systems they employ.

4. Supply Chain Security in Healthcare AI

Consider the entire technology supply chain, including where the AI models were trained and how they’re maintained. This is particularly crucial for solutions handling sensitive healthcare data.

5. Long-term Stability

Healthcare providers need partners they can rely on for the long term, with clear accountability and consistent support. This becomes particularly important when dealing with foreign entities operating under different legal frameworks.

At Videra, we believe that true innovation in healthcare AI must be built on a foundation of trust, security, and ethical operation. While cost is certainly a factor in technology decisions, it cannot be the primary driver when patient care and privacy are at stake.

The U.S. healthcare system has always been at the forefront of innovation, and maintaining this leadership requires careful consideration of the tools and technologies we employ. As we continue to advance in the AI era, let’s ensure we’re making choices that protect our patients, our intellectual property, and our healthcare infrastructure.

Our commitment to developing secure, ethical AI solutions that prioritize healthcare AI security remains unwavering. We understand that the future of healthcare technology must balance innovation with responsibility, and we’re dedicated to maintaining the highest standards in both areas.

Check our blog for the latest discussions on AI in healthcare, behavioral health, life sciences and clinical trials.

Protecting Innovation, Security, and Patient Trust in AI Healthcare

Model cards for AI vendors showing performance metrics across populations

As CEO of Videra, I’ve watched the artificial intelligence landscape evolve at an unprecedented pace. While this evolution brings extraordinary opportunities for healthcare advancement, it also presents significant challenges that we must address head-on – particularly regarding the proliferation of low-cost AI solutions from non-allied nations.

The healthcare sector, especially in mental and behavioral health, requires the highest standards of security, reliability, and ethical consideration. When we develop AI tools for healthcare applications, we’re not just creating technology – we’re creating solutions that impact human lives, influence medical decisions, and handle incredibly sensitive patient data.

This year has seen a surge in AI products marketed to healthcare providers at significantly reduced prices. While competitive pricing is generally beneficial for market innovation, we must carefully consider the hidden costs and risks associated with AI solutions from nations with different data privacy standards, regulatory frameworks, and strategic interests than our own.

For pharmaceutical companies and drug developers, these risks are particularly acute. Drug development involves highly sensitive intellectual property and research data that, if compromised, could have far-reaching consequences for both innovation and national security. When AI systems process this data, they need to do so with absolute security and transparency about data handling practices.

In behavioral and mental health, the stakes are equally high. These fields deal with some of our most vulnerable populations, and the AI systems supporting these services must maintain the highest standards of privacy and ethical operation. Providers need to know exactly how patient data is being processed, where it’s being stored, and who has access to it.

Key considerations for healthcare providers when evaluating AI solutions:

1. Data Security and Sovereignty

Your patient data should remain within U.S. jurisdiction, protected by our robust privacy laws and HIPAA regulations. Be wary of solutions that may route or store data through servers in countries with different privacy standards or data access laws.

2. Regulatory Compliance

Ensure any AI solution fully complies with U.S. healthcare regulations. This includes not just HIPAA, but also FDA requirements for medical devices and software as a medical device (SaMD).

3. Algorithmic Transparency

Understanding how AI makes decisions is crucial in healthcare. Providers should have clear insight into the training data and methodologies used to develop the AI systems they employ.

4. Supply Chain Security

Consider the entire technology supply chain, including where the AI models were trained and how they’re maintained. This is particularly crucial for solutions handling sensitive healthcare data.

5. Long-term Stability

Healthcare providers need partners they can rely on for the long term, with clear accountability and consistent support. This becomes particularly important when dealing with foreign entities operating under different legal frameworks.

At Videra, we believe that true innovation in healthcare AI must be built on a foundation of trust, security, and ethical operation. While cost is certainly a factor in technology decisions, it cannot be the primary driver when patient care and privacy are at stake.

The U.S. healthcare system has always been at the forefront of innovation, and maintaining this leadership requires careful consideration of the tools and technologies we employ. As we continue to advance in the AI era, let’s ensure we’re making choices that protect our patients, our intellectual property, and our healthcare infrastructure.

Our commitment to developing secure, ethical AI solutions remains unwavering. We understand that the future of healthcare technology must balance innovation with responsibility, and we’re dedicated to maintaining the highest standards in both areas.

Check our blog for the latest discussions on AI in healthcare, behavioral health, life sciences and clinical trials.

Why We Made TDScreen Free: A CEO’s Perspective on Democratizing Mental Health Screening

TDScreen AI-powered TD screening tool interface showing patient assessment dashboard

Last week we announced the launch of TDScreen – our AI-powered Tardive Dyskinesia (TD) screening tool. The response has been immediate and overwhelming, validating everything we believed about the urgent need for accessible TD screening.

This is exactly why we built TDScreen.

The Hidden Crisis in Plain Sight

Let me share some numbers that keep me up at night:

  • At least 500,000 Americans suffer with Tardive Dyskinesia
  • Only 20% of those  have been diagnosed
  • That’s a 80% diagnosis gap

But here’s what those statistics don’t capture: Each untreated case represents someone whose involuntary movements might be dismissed as nervousness, aging, or “just a quirk.” Someone who might stop taking life-changing medications because they’re embarrassed by movements that could be managed. Someone whose quality of life is quietly deteriorating while effective treatments exist.

Why Traditional Screening Fails

The standard AIMS assessment takes 15-20 minutes of specialized clinical time. For a psychiatrist seeing 20-30 patients daily, screening everyone quarterly (as guidelines recommend) is mathematically impossible. It’s not about clinician dedication – it’s about the brutal reality of time constraints in modern healthcare.

This is where AI changes everything. TDScreen compresses expert-level assessment into a 5-minute patient self-assessment, with accuracy that actually exceeds human raters (0.89 AUC, validated in our Journal of Clinical Psychiatry study).

The Business Decision to Make TDScreen Free

We’re not in the business of gatekeeping essential healthcare tools. We’re in the business of transforming behavioral health outcomes.

Making TDScreen free isn’t charity – it’s strategy. Every provider who adopts TDScreen becomes part of our mission to modernize behavioral healthcare. Every patient who gets screened is a potential life improved. And every success story builds the foundation for our broader platform vision.

What Our TD Screening Tool Actually Does

For providers wondering about the specifics – here’s exactly what you get:

Immediate Clinical Value

  • Patient completes video assessment (smartphone, tablet, or computer)
  • AI analyzes movement patterns based on AIMS criteria
  • You receive an objective risk score with visual highlights
  • Track changes over time with quantitative data

Zero Hidden Costs

  • No subscription fees
  • No per-patient charges
  • No training requirements
  • No IT integration needed
  • Start screening in under 15 minutes

The Evidence Behind TDScreen

Our research, published yesterday in the Journal of Clinical Psychiatry, demonstrates that TDScreen achieves:

  • Superior consistency compared to human raters (Cohen’s Kappa of 0.61)
  • Validated across 350+ patients in multi-site clinical trials

This isn’t theoretical – it’s proven technology ready for clinical use today. Our partners in the study – Dr. Anthony A. Sterns, Ph.D., lead researcher on the project and CEO at iRxReminder, Dr. Owen Muir, CMO of iRxReminder, CMO and co-founder of Radial Health, and co-author of the publication, and the National Institutes of Health – provided the data and analysis that helped to create TDScreen.

The Bigger Vision

Why This TD Screening Tool Changes Everything

TDScreen is just the beginning. At Videra Health, we’re building a comprehensive AI platform that transforms how behavioral health providers deliver care. But we started with TD screening for a reason: it’s a massive, solvable problem where AI demonstrably outperforms traditional methods.

By making TDScreen free, we’re proving that AI in healthcare doesn’t have to be expensive, complex, or intimidating. It can be as simple as sending your patient a link.

Your Patients Are Waiting

If you prescribe antipsychotics, you have patients at risk for TD. Statistically, several already have symptoms. The question isn’t whether to screen – it’s whether you’ll do it the old way or the better way.

TDScreen is live, validated, and free at tdscreen.ai.

No sales calls. No demos required. No contracts to sign.

Just better care, starting today.

Join the Movement

In healthcare innovation, the best time to adopt new technology is when it’s proven but not yet universal. TDScreen has the validation (peer-reviewed research), the accessibility (completely free), and the simplicity (5-minute assessments) to transform TD screening.

The providers who adopt TDScreen today aren’t just using a tool – they’re setting a new standard of care for their patients.

Will you join us?

Start screening at tdscreen.ai

Register for TDScreen now

Videra Health Launches TDScreen, a First-of-Its-Kind Video-based, AI-powered Tool to Assess Tardive Dyskinesia Symptoms

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New study published in the Journal of Clinical Psychiatry reveals AI enables efficient, accurate and scalable detection of TD, representing a significant advancement in meeting the standard of care for TD screening

Orem, UT, June 3, 2025 – Videra Health, a leading AI platform for behavioral health providers, has announced the launch of TDScreen, the first-ever automated, video-based AI solution on the market to screen for Tardive Dyskinesia (TD) symptoms. TD is a chronic, involuntary movement disorder that can develop as a side effect of long-term use of certain medications, particularly antipsychotic drugs. While TDScreen isn’t intended as a standalone diagnostic tool, it represents a significant advancement in meeting the standard of care for TD screening.

TD presents unique screening challenges even for experienced clinicians and remains underdiagnosed. TD affects up to 2.6 million Americans, and up to 7 million Americans taking antipsychotic medications could develop TD symptoms. With its involuntary movements often mistaken for nervousness, aging, or other conditions, the gap in recognition represents not just a clinical challenge, but a deeply human one that affects quality of life and treatment outcomes. A paper published Wednesday in The Journal of Clinical Psychiatry, led by Principal Investigator Dr. Anthony Sterns and members of the iRxReminder and Videra Health teams, reveals that video-based AI enables efficient, accurate, and scalable detection of TD. This application has the potential to significantly improve early diagnosis and patient outcomes, especially in remote care settings where resources are scarcest. Videra Health’s TDScreen algorithm was built using the data from multiple studies, which was supported in part by the National Institute of Mental Health, and represents a significant leap forward in integrating artificial intelligence into psychiatric care, particularly in the era of telemedicine.

“Videra Health is thrilled to be able to launch a first-of-its-kind innovative solution to screen for TD symptoms, effectively,” said Loren Larsen, CEO of Videra Health. “TDScreen and our broader AI platform aren’t about replacing clinician judgment—they’re about enhancing it. By automating routine screenings, we free healthcare providers to focus on what matters most: the human connections and complex decision-making that drive quality care.” Larsen added, “We are grateful for the multiple academic and research partners who have contributed their time and expertise to these studies.”

“Early detection of TD is critical to mitigating its debilitating effects,” said Dr. Anthony A. Sterns, Ph.D., lead researcher on the project and CEO at iRxReminder. “Our AI-driven approach not only matches but exceeds human expert performance, offering a scalable solution to a major unmet clinical need,” added Dr. Joel W. Hughes, Ph.D., collaborator from Kent State University.

“As a physician who both treats –and lives with– tardive dyskinesia, this research marks a turning point for millions of patients who have been forced to wonder if the movement disorder they suffer from could be treatable,” says Owen S, Muir, M.D., CMO of iRxReminder, CMO and co-founder of Radial Health, and co-author of the publication.  “Now, physicians have a simple, evidence-based AI-guided tool to support their clinical decision making.”

TDScreen was validated across three clinical studies involving more than 350 participants on antipsychotic medications. The innovative AI tool developed by Videra Health utilizes advanced video analysis and a vision transformer machine learning architecture to detect TD with unprecedented accuracy. TDScreen demonstrates a Cohen’s Kappa of 0.61—a number indicating the algorithm is outperforming even calibrated human raters. The algorithm achieved an area under the receiver-operating-characteristic curve (AUC) of 0.89, surpassing the sensitivity and specificity of trained human raters using the standard Abnormal Involuntary Movement Scale (AIMS).

These numbers represent more than just statistical achievements—they translate to real-world benefits:

  • Consistency: Unlike human raters whose assessments may vary, AI provides the same evaluation standards every time
  • Accessibility: Patients can complete assessments from home on their own devices
  • Efficiency: Providers save valuable clinical time while increasing screening frequency
  • Earlier detection: Subtle symptoms can be identified before they become pronounced

Continuous monitoring: Regular assessments track symptom progression or improvement

With TDScreen, patients on antipsychotics can easily complete video-based screenings in-office or remotely, and enable providers to monitor or modify their treatment plans. The TDScreen tool is based on the Abnormal Involuntary Movement Scale (AIMS), a comprehensive clinician-rated scale designed to specifically evaluate involuntary movements. Employing advanced AI video technology, TDScreen efficiently assesses and quantifies the risk of TD in less than 5 minutes. The resulting score generated by this assessment can aid in clinical decision-making and management strategies.

TDscreen is available free of charge for any provider or patient wanting to screen for TD. Visit tdscreen.ai to learn more.

About Videra Health™

Videra Health is a leading AI platform for behavioral health providers and proactively identifies, triages and monitors at-risk patients using linguistic, audio and video analysis. The FDA-registered digital platform transforms how doctors and healthcare systems interact and track a patient’s journey, illuminating the hidden depths of patient behavior and outcomes. Videra Health connects providers and patients anytime, anywhere, between visits and post-discharge via written and video assessments that translate into actionable quantitative and qualitative patient data. The platform streamlines diagnoses, enhances care accessibility, optimizes workflows and drives down costs for providers and healthcare systems. 

For more information, visit www.viderahealth.com.

About iRxReminder
iRxReminder specializes in digital health solutions aimed at enhancing medication adherence and mental health management through cutting-edge technology applications and innovative behavioral science solutions.

For more information, visit www.irxreminder.com.

The Critical Role of Model Cards When Selecting an AI Vendor for Behavioral Health and Pharma

Model cards for AI vendors showing performance metrics across populations

In today’s healthcare landscape, model cards for AI vendors have become essential documentation when selecting technology partners for behavioral health and pharmaceutical applications. These comprehensive documents provide transparent details about AI models’ performance, training data, and limitations—critical information for healthcare organizations making high-stakes technology decisions that impact patient care.

What Are Model Cards and Why Do They Matter?

Model cards serve as transparent documentation for machine learning models, detailing their performance characteristics, training data, intended use cases, and limitations. First proposed by researchers at Google in 2019, model cards have quickly become a best practice in responsible AI development.

For behavioral health and pharmaceutical applications, where decisions directly impact patient care, model cards aren’t just nice-to-have documentation—they’re essential safeguards that provide critical information about the algorithms making or supporting clinical decisions.

Key Elements of Strong Model Cards in Healthcare AI

When evaluating AI vendors for behavioral health or pharmaceutical applications, look for model cards that include:

  • Intended Use and Clinical Context: Clear explanation of what the model is designed to do, and importantly, what it’s not designed to do.
  • Training Data Demographics: Details about the populations represented in the training data—particularly important for ensuring models work across diverse patient populations.
  • Performance Metrics: Specificity and sensitivity measurements, both overall and for specific demographic groups.
  • Validation Methodology: How the model was validated, including any peer-reviewed research or clinical studies.
  • Limitations and Constraints: Transparent acknowledgment of the model’s limitations and potential failure modes.
  • Bias Evaluation: Assessment of potential biases in the model and steps taken to mitigate them.
  • Regulatory Status: Information about FDA registration or other regulatory frameworks the model complies with.

Real-World Example: Behavioral Health Assessment Models

Consider a vendor offering AI models that analyze video responses to detect signs of depression. A comprehensive model card would specify:

  • The model predicts PHQ-9 equivalent scores based on facial expressions, voice tone, and natural language analysis
  • Training included data from 10,000+ individuals across diverse demographic groups
  • Overall accuracy metrics (e.g., AUC: 0.89) with breakdowns for different populations
  • Independent validation through IRB-approved studies
  • Lower accuracy rates for certain populations with smaller representation in training data
  • Not intended for standalone diagnosis, but as a screening aid for clinicians

This level of transparency enables healthcare organizations to make informed decisions about whether a particular AI solution aligns with their clinical needs, patient populations, and ethical standards.

The Coalition for Health AI (CHAI) produced a great example of what a model card can contain to ensure transparency, safety, security & privacy, fairness & bias, and usefulness. Individual model cards will look different, but the frameworks CHAI developed are a baseline.

The Regulatory Landscape and Model Documentation

As regulatory bodies like the FDA develop frameworks for AI as medical devices, comprehensive documentation is becoming increasingly important. The FDA’s proposed regulatory framework for AI/ML-based Software as a Medical Device (SaMD) emphasizes the importance of transparency in model development and performance.

For pharmaceutical companies, model documentation is particularly crucial for clinical trials, where regulators require clear evidence of model validity and reliability. Strong model cards can help satisfy these requirements and build trust with regulatory agencies.

Questions to Ask AI Vendors About Their Models

When evaluating AI vendors for behavioral health or pharmaceutical applications, consider asking:

  • “Can you provide detailed model cards for each of your algorithms?”
  • “How was your model validated across different demographic groups?”
  • “What peer-reviewed research supports the effectiveness of your model?”
  • “What are the known limitations or potential biases in your model?”
  • “How often is your model updated, and what is your validation process for new versions?”

Model Cards as a Competitive Advantage

As the AI healthcare market becomes increasingly competitive, comprehensive model cards aren’t just good practice—they’re becoming a competitive advantage. Organizations that prioritize vendors with thorough, transparent documentation are better positioned to implement AI solutions that are effective, ethical, and aligned with regulatory requirements.

When selecting an AI vendor for behavioral health or pharmaceutical applications, remember that the quality of their model cards often reflects the quality of their approach to AI development. In a field where decisions impact patient lives, this level of transparency isn’t optional—it’s essential.

By demanding comprehensive model cards from AI vendors, healthcare organizations can make more informed decisions, reduce implementation risks, and ultimately deliver better care to the patients who need it most.

Check our blog for the latest discussions on AI in healthcare, behavioral health, life sciences and clinical trials.

Improving Intake Processes Without Overloading Staff: Technology’s Role in Patient Flow

As healthcare providers, we all share a common challenge: efficiently managing the automated healthcare intake process while maintaining quality care and not overwhelming our already stretched staff. Whether you’re running a behavioral health clinic or coordinating clinical trials, intake processes often create bottlenecks that impact everything downstream.

The Automated Healthcare Intake Revolution

The statistics tell a sobering story. Traditional intake assessments typically require 30-60 minutes of clinical time per patient, with staff spending additional hours on documentation and coordination. For many behavioral health organizations, this translates to:

  • Extended wait times averaging 3+ months for new patient appointments
  • High no-show rates (often exceeding 30%) due to delayed access
  • Significant administrative burden leading to clinician burnout
  • Lost revenue from unfilled appointments and incomplete assessments

Clinical trial administrators face similar challenges, with participant screening and enrollment often consuming 30% of total study costs and extending timelines by months.

How Our Automated Healthcare Intake Process Works

At Videra Health, we’ve focused on developing solutions that specifically address these intake challenges while preserving what matters most – the human connection between providers and patients.

Our Videra Intake Manager transforms the traditional intake process by combining AI-driven automation with thoughtful human design. This system allows patients to complete comprehensive assessments on their own time while automatically generating the documentation your team needs.

Key capabilities include:

  • Automated pre-screening that identifies appropriate level of care before the first appointment
  • Self-directed video assessments that capture rich clinical information without provider time
  • AI-assisted documentation that generates structured intake reports
  • Seamless EHR integration that eliminates duplicate data entry
  • Multi-language support that expands access to diverse populations

Real Results from Real Implementations

Behavioral health organizations implementing our intake solutions have reported impressive outcomes:

  • 50% reduction in administrative time spent on new patient processing
  • 35% increase in completed intake appointments
  • 28% decrease in time-to-treatment for new patients
  • 42% improvement in staff satisfaction with intake processes

For clinical trial administrators, our system has demonstrated:

  • 40% faster participant screening and enrollment
  • 65% reduction in administrative processing time
  • 30% improvement in protocol adherence during screening
  • Significant enhancement in participant diversity through expanded access

A Practical Implementation Approach

The most successful implementations we’ve seen take a phased approach. Rather than completely overhauling existing processes, many organizations begin by implementing Videra Assess for pre-appointment screening, then gradually integrate more automation as staff and patients become comfortable with the technology.

This measured approach ensures that technology enhances rather than disrupts your care delivery model, with each phase building on previous successes.

Looking Forward: The Integrated Intake Ecosystem

The future of intake management lies in seamless integration between automated assessment tools, documentation systems, and advanced operational tools.

Together, these create an ecosystem that not only improves efficiency but actually enhances the quality of clinical information gathered during the intake process.

To learn more about how Videra Health can transform your intake processes, schedule a personalized demonstration with our team.

Your patients deserve prompt access to care, and your staff deserves technology that makes their jobs easier rather than more complicated. Let’s work together to make that a reality.

Check our blog for the latest discussions on AI in healthcare, behavioral health, life sciences and clinical trials.

5 Ways AI Can Help Mental Health Clinicians Manage a Growing Caseload

As mental health providers face mounting caseloads and rising demand, AI offers a path forward by enhancing efficiency without sacrificing personalized care. This article highlights how AI-powered screening platforms, rooted in measurement-based care, are helping clinicians prioritize high-risk patients, automate routine tasks, and extend their reach beyond the office. The result is more time for meaningful client interactions and stronger therapeutic relationships—hallmarks of quality care. With the right implementation, AI serves not as a replacement, but as a trusted partner in the delivery of smarter, more responsive mental health services.
Read the full article here.

How AI is Empowering Providers with Early Detection of Mental Illness

AI is transforming mental health care by enabling earlier, more precise detection of symptoms that might otherwise go unnoticed until crisis points. This thoughtful piece explores how technology can continuously monitor subtle behavioral shifts—augmenting clinical expertise and allowing providers to intervene sooner. By analyzing data across multiple modalities and comparing patients to their own baselines, AI supports a shift from reactive treatment to proactive care. The result is better outcomes, lower costs, and a future where clinicians are empowered—not replaced—by intelligent tools.
Read the full article here.

2025 Trends in Behavioral Health Technology – Part 2

Two hands - one human, one robotic - pointing to 2025

As discussed in part one of this series, the behavioral health technology landscape is undergoing a profound metamorphosis, with artificial intelligence (AI) and digital technologies reshaping how behavioral health professionals train, deliver care, and interact with patients. Here’s the last four trends I think will impact the behavioral healthcare space in 2025.

Intelligent Training and Skill Development

Continuous improvement has always been the hallmark of exceptional clinical practice. Now, AI is revolutionizing how behavioral health professionals refine their craft. Imagine a world where every therapy session becomes a learning opportunity—not through traditional supervision alone, but through intelligent, nuanced feedback systems that can analyze communication patterns, emotional resonance, and therapeutic techniques with unprecedented depth.

Advanced AI tools can now listen to therapy sessions, providing granular insights into communication effectiveness. These systems don’t just provide mechanical feedback; they offer sophisticated analysis of therapeutic alliance, helping clinicians understand subtle interpersonal dynamics that might otherwise go unnoticed. Simulated training environments allow practitioners to practice with AI patients, creating safe spaces to experiment with diverse therapeutic approaches and develop skills for treating populations they might find challenging.

This isn’t about replacing human supervision but augmenting it. By reducing time and cost barriers associated with traditional training methods, these technologies democratize professional development, allowing more practitioners to access high-quality skill enhancement.

The Emerging Landscape of Digital Therapeutics

The regulatory landscape for digital behavioral health tools is rapidly evolving. The FDA’s increasing approval of digital therapeutics and CMS’s recent Medicare billing codes represent a watershed moment. What was once considered experimental is now becoming mainstream healthcare.

Digital therapeutics are no longer peripheral technologies but integrated healthcare solutions. Much like traditional prescriptions, clinicians can now “prescribe” FDA-approved digital applications. This represents a fundamental shift in how we conceptualize behavioral health treatment—expanding therapeutic interventions beyond traditional in-person or telehealth models.

However, this emerging ecosystem is not without risks. The proliferation of behavioral health apps has created a complex marketplace where marketing claims often outpace clinical evidence. Consumers and practitioners must develop sophisticated digital literacy, distinguishing between rigorously tested interventions and unsubstantiated digital offerings.

Navigating the Ethics of AI in Therapy

The potential for AI to automate risk assessment and even conduct preliminary therapeutic interactions is tantalizing. Yet, this technological frontier demands careful navigation. While AI tools can provide initial screenings and support, they cannot—and should not—replace the profound human elements of therapeutic relationships.

We are witnessing the early stages of what might become a regulatory “Wild West” in digital behavioral health. Expect increased scrutiny, with regulatory bodies working to establish clear guidelines that protect patient safety while allowing technological innovation.

A Holistic View of Technological Integration

These trends are not isolated developments but interconnected elements of a broader transformation. They represent a holistic reimagining of behavioral healthcare—where technology serves as an empowering tool, not a replacement for human connection.

The most successful organizations will be those that view these technologies not as standalone solutions but as integrated components of a comprehensive care strategy. Success will depend on maintaining a delicate balance: leveraging technological capabilities while preserving the irreplaceable human elements of empathy, nuance, and genuine therapeutic connection.

Embracing Responsible Innovation

As we move deeper into 2025, the behavioral health landscape stands at a critical juncture. The technologies emerging today have the potential to democratize behavioral healthcare, reduce systemic barriers, and create more personalized, effective treatment modalities.

Yet, with this potential comes profound responsibility. Our challenge is not merely to adopt new technologies but to do so thoughtfully, ethically, and with an unwavering commitment to patient well-being.

The future of behavioral health is not about technology replacing human care—it’s about technology expanding and enhancing our capacity for compassion, understanding, and healing.

Deep Dive Into the Trends

Curious about how these technologies impact care, how the regulatory landscape is changing to meet the new paradigm, or how AI can help super-charge efforts to bring new medications to market? Join our webinar on January 31, 2025 at 3PM ET / 12PM PT to discuss 2025 trends and what it means for healthcare.

Check our blog for the latest discussions on AI in healthcare, behavioral health, life sciences and clinical trials.

2025 Trends in Behavioral Health Technology, Part 1

Two hands - one human, one robotic - pointing to 2025

The First Three Trends

As we enter 2025, the behavioral health technology landscape is on the cusp of a revolution, with artificial intelligence (AI), digital tools, and innovative approaches poised to dramatically reshape how mental health services are delivered, accessed, and personalized. I expect these first three key emerging trends will fundamentally alter the healthcare ecosystem.

Expanding Access and Democratizing Behavioral Health Care with Technology

Digital health technologies are emerging as powerful democratizing forces in healthcare delivery. For populations historically marginalized—rural communities, economically constrained individuals, and underserved demographic groups—AI and digital platforms represent more than technological solutions. They are bridges to care, pathways to understanding, and tools of empowerment.

These technologies are not about replacing human connection but extending its reach. By breaking down geographical, economic, and systemic barriers, they create opportunities for more inclusive, accessible behavioral health support. Intelligent systems can now provide initial screenings, offer preliminary support, and guide individuals towards appropriate resources with unprecedented sensitivity and efficiency.

The Precision Medicine of Behavioral Health

 The era of one-size-fits-all treatment is rapidly dissolving. Artificial intelligence is ushering in a new paradigm of precision behavioral healthcare, where treatment plans are as unique as the individuals receiving them. By analyzing complex, multi-dimensional datasets, AI can now recommend care pathways with a level of personalization that was once the domain of highly specialized, resource-intensive approaches.

This isn’t about algorithmic replacement of clinical judgment but about providing clinicians with powerful, nuanced tools for understanding and supporting patient well-being. Each recommendation is a collaborative insight, bridging technological sophistication with human empathy.

Navigating the Ethical Considerations in the Human-Technology Interface

As we embrace these transformative technologies, we must remain vigilant about maintaining the core ethical principles of healthcare. Artificial intelligence and digital tools are powerful assistants, not autonomous decision-makers. They augment human capability, illuminate hidden insights, and create opportunities for more profound, more personalized care.

The most successful approaches will be those that view behavioral health technology not as a replacement for human interaction but as a sophisticated tool for enhancing our collective capacity for understanding, compassion, and healing.

Read part two of my Top Trends for 2025 here.

Check our blog for the latest discussions on AI in healthcare, behavioral health, life sciences and clinical trials.

Meet The Disruptors: Loren Larsen Of Videra Health On The Five Things You Need To Shake Up Your Industry

Loren Larsen, CEO of Videra Health, shares his perspective on what it takes to truly disrupt an industry in this thoughtful Authority Magazine interview. Drawing on decades of experience in healthcare technology and AI, Larsen reflects on the challenges of innovating in a highly regulated, human-centered field like mental health. He discusses how Videra Health is leveraging video-based AI to enhance early detection and support clinicians without replacing the essential human connection. Throughout the piece, he emphasizes the importance of trust, empathy, and deep domain expertise in building solutions that actually move the needle.

Read the full article here.

Trust and Transformation Take Center Stage at DataRobot’s 2021 AI Experience Worldwide, May 11-12, 2021

Videra Health Logo

Tech visionary Alexis Ohanian and newly appointed CEO of DataRobot, Dan Wright, join customers, execs, partners, and AI visionaries on “The Hunt for Transformational Growth” during virtual event

BOSTON–(BUSINESS WIRE)–DataRobot, the leader in enterprise AI, is on “The Hunt For Transformational Growth” with its second annual virtual event on May 11-12. Alexis Ohanian, Founder of Seven Seven Six and Co-Founder of Reddit, and America’s “Science Guy,” Bill Nye, join a dynamic speaker line-up, including DataRobot executives and customers, business leaders, data scientists, educators, and leading AI ethicists. The two-day event is open to the public and free to attend, with sessions available on-demand immediately following.

Competition is fierce these days and organizations must scale fast, smart, and efficient. Offering over 20 sessions from unique voices in business and AI, AI Experience Worldwide attendees will gain actionable insight on building an agile, AI-driven enterprise and access to cutting-edge strategy that is critical when it comes to improving forecasts and optimizing performance with AI.

Day 1 of the conference includes a forward-leaning conversation featuring DataRobot’s CEO, Dan Wright, on his call for a new era of democratized AI, as well as a sneak peek at some of DataRobot’s enterprise AI platform innovations from Nenshad Bardoliwalla, SVP of Product. Executives from Yelp, Overstock.com, Pendo, and Airin share unscripted insight on their path to transformational growth.

Day 2 explores why trust in AI is no longer a feature, it’s a requirement. DataRobot’s Global AI Ethicist, Haniyeh Mahmoudian, PhD, will address the skepticism surrounding AI solutions, and discuss why it’s critical to approach issues of bias and fairness by implementing trustworthy AI.

Additional highlights include:

  • Opening Keynote from tech visionary Alexis Ohanian, Founder of Seven Seven Six and Co-Founder of Reddit. This session will explore Alexis’s views on the future of tech and how he intends to enable a better world for the next generation.
  • Ricky Ray Butler, CEO of BEN Group, Linda Klug, Founder & CEO of Airin, and Loren Larsen, CEO/Co-Founder of Videra Health, join DataRobot Chief AI Evangelist, Ben Taylor, for a transparent conversation around their initial doubts—and ultimate takeaways—when implementing AI to transform their business.
  • Sally Embrey, DataRobot’s VP of Public Health and Medical Technologies, speaks to the pivotal role of data and AI as we seek to democratize health, empower patients, and allow individuals to thrive.
  • Closing remarks from “Science Guy” Bill Nye and Chris Mattmann, Chief Technology and Innovation Officer at NASA Jet Propulsion Laboratory, on the importance of research and discovery, fighting anti-science sentiment, space exploration, where humanity is headed, and how we can all play a role.

“Every company is now an AI company, and the decision to implement AI is no longer optional,” said Wright. “Knowing this, we’re excited to welcome technologists, corporate leaders, data scientists, researchers, and users at every level to witness the transformational potential of AI on businesses’ bottom line. Our goal is to create a space for transparent discussions around the complexities surrounding AI. We’ll have CEOs share their own hesitations when embracing AI and AI ethicists and educators explore the need for AI we can trust, with actionable roadmaps to help us plan for and handle institutional bias as we look to the future.”

To register for DataRobot’s virtual conference or to learn more about the event, visit the AI Experience Worldwide website and follow along on Twitter #AIExperience.

About DataRobot

DataRobot is the leader in enterprise AI, delivering trusted AI technology and enablement services to global enterprises competing in today’s Intelligence Revolution. DataRobot’s enterprise AI platform democratizes data science with end-to-end automation for building, deploying, and managing machine learning models. This platform maximizes business value by delivering AI at scale and continuously optimizing performance over time. The company’s proven combination of cutting-edge software and world-class AI implementation, training, and support services, empowers any organization – regardless of size, industry, or resources – to drive better business outcomes with AI.

DataRobot has offices across the globe and funding from some of the world’s best investing firms including Alliance Bernstein, Altimeter, B Capital Group, Cisco, Citi Ventures, ClearBridge, DFJ Growth, Geodesic Capital, Glynn Capital, Intel Capital, Meritech, NEA, Salesforce Ventures, Sands Capital, Sapphire Ventures, Silver Lake Waterman, Snowflake Ventures, Tiger Global, T. Rowe Price, and World Innovation Lab. DataRobot was named to the Forbes 2020 Cloud 100 list and the Forbes 2019, 2020, and 2021 Most Promising AI Companies lists, and was named a Leader in the IDC MarketScape: Worldwide Advanced Machine Learning Software Platforms Vendor Assessment. For more information visit http://www.datarobot.com/, and join the conversation on the DataRobot Community, More Intelligent Tomorrow podcast, Twitter, and LinkedIn.