The most up-to-date, comprehensive, and accurate source of data. Your organization can access profiles of every active provider in the U.S.—over 6 million.
See how we’ve helped leading healthcare organizations achieve significant cost savings, improve data accuracy, and enhance patient care. Here, you will find our results, research, reports, and everything else our scientists are testing in the Veda Lab – no lab coat required.
At Veda we understand that every data point is an opportunity to improve the healthcare experience. And we can see the potential when data is no longer a barrier.
Healthcare organizations today face an immense challenge: ensuring data accuracy and accessibility in a complex, often fragmented industry. Meghan Gaffney, CEO of Veda Data Solutions, is tackling these healthcare data challenges head-on.
In a recent episode of the Healthcare Strategy Podcast, Gaffney, whose unique journey spans nearly 15 years in healthcare policy to tech entrepreneurship, discussed how AI-driven healthcare solutions can bridge critical gaps.
Meghan covers the impact Veda’s technology has had on healthcare organizations. Please read about our automation, which saves money and improves the member experience.
Dr. Bob Lindner is the Chief Science and Technology Officer at Veda, a company addressing provider directory data challenges.
It’s no surprise to anyone who works with data—it’s messy. In every industry and every business, there are data anomalies and issues that can impact the story data tells. If we have any hope of improving data practices and making collected data truly actionable, we first have to acknowledge its limitations and then explore modern solutions for improving it.
Bad Data Is The Norm
With the new federal administration exploring cost-cutting measures and releasing data nearly daily, a specific example caught my eye—it was a Social Security disbursements by age graph, with the data suggesting 210 year olds are receiving Social Security entitlements. As a data scientist who has been working with healthcare data for over 10 years, this graph wasn’t shocking to me.
I recently saw one dermatologist who was practicing at 20 different variations of one address; imagine the extra legwork required by a patient to find out where you are booking an appointment. Or how about two providers with the exact same name but one is a veterinarian on the West Coast and the other is a physician in New York? There is state licensing info for both of them, but the only one with a federal National Provider Identifier (NPI) is the veterinarian. These are complex data problems occurring every day.
Data engineers know that a lot of data in every industry is collected manually, and this often introduces errors that are quickly propagated and magnified throughout downstream processes. In fact, most data systems in the modern economy, all around the globe, have shockingly out-of-date practices. With a spotlight on data issues right now, it’s important to dig deeper and examine data processes to have any hope of modernizing databases and making data functional.
Simple, Clear Provider Data For Fast Decision-Making
Reliable provider data enables confident goal attainment in your healthcare business, streamlining operations and facilitating the pursuit of new strategic ventures.
Reliable Provider Data for Digital Health Organizations
In this scenario, your digital health organization aims to connect patients to behavioral health specialists within 24 hours of contact. How can you accomplish this goal? By finding and partnering with plenty of providers who perform online appointments and having reliable data to refer patients quickly.
Watch this example of how Vectyr Profile Search identifies specific providers who conduct telehealth appointments:
Then, you can compare your search findings with your current provider database to easily contract with those you’re not currently working with. The best part? Peace of mind that the information is up to date and accurate—no more making several dead-end calls when one will do.
Pro Tip: Provider profiles are detail rich. Look for providers that are accepting many different types of insurance if that is a plus for your organization.
Reliable Provider Data for Health Plans
Let’s say you want to recruit more pediatric cardiologists for your health plan in Illinois to carve out a competitive advantage and meet your members’ needs.
Use Vectyr Profile Search to curate an exportable list of providers to contact:
The best part? Addresses are practice locations and not just P.O. boxes, so you can be sure your network reflects where providers are actually practicing.
Pro Tip: Check provider profiles for languages, cultural competencies, licenses, and more. By aligning patients with the right providers, you’ll enhance care quality and drive better retention.
Reliable Provider Data for Provider Organizations
What about when you’re onboarding new providers and want to enroll and credential them faster? You can streamline the onboarding process with the initial data entry of provider information, ensuring accuracy from the start.
Watch as the Vectyr Profile Search serves up-to-date and complete information—no more costly and time-consuming manual searches and verification of credentials:
Pro Tip: With Vectyr’s detail-rich profiles, you can spot or bulk-check credentials to ensure enrollment is completed correctly the first time without relying on self-reported data.
Try Our Provider Data
Veda’s Vectyr Profile Search features a comprehensive and constantly growing dataset that drives value for many healthcare businesses. Our data offering is always expanding to ensure that no matter how deep the use case, we have the data to support it.
Meghan Gaffney: 5 Reasons Why Women Build Great Companies
Read CEO and Co-Founder of Veda Meghan Gaffney’s Medium.com Interview
Medium Authority Magazine — Women-led businesses are on the rise, and the data shows they often outperform their peers. From fostering strong company cultures to driving innovation and long-term success, women bring unique strengths to entrepreneurship and leadership. What are the key reasons behind their success? Read Meghan Gaffney‘s interview with Authority Magazine below.
Thank you so much for doing this with us! Before we dig in, our readers would like to get to know you a bit more. Can you tell us a bit about your “backstory”? What led you to this particular career path?
I worked on Capitol Hill during the development of the Affordable Care Act and had the unique opportunity to hear perspectives on the future of healthcare from hospital executives, insurers, and patient advocates. Data was at the center of many challenges patients faced when accessing care, but it wasn’t the focus of any proposed solutions. I learned most patients simply want the basics: the ability to find a provider who they can easily and quickly book an appointment with. Quite simply, I knew there had to be a better way for people to access a provider.
Can you share the most interesting story that happened to you since you began your career
What I’ve found over and over again is how bipartisan healthcare is. From working on Capitol Hill to CEO of a healthcare technology company, healthcare’s impact is universal. It’s a rare piece of common ground for both sides of the aisle.
Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lesson you learned from that?
One of the mistakes I made in the early fundraising days was trying to contort our business into something that it wasn’t to appeal to a broader audience. We were offering technology that was fundamentally different from what everyone else was doing in Silicon Valley and initially, instead of leaning into that, I tried to appeal to everyone. Even down to my slide deck framework, I made it look like what the market was used to seeing.
I learned broad visions that address all areas of a market can muddy the water on what your next steps are. It’s difficult to find out where your product will fit if it fits everywhere. I quickly realized an authentic voice and viewpoint was far more valuable than doing what everyone else was doing.
Digital Health Transformers podcast host Gregory Cave is joined by Meghan Gaffney, CEO and Co-Founder of Veda. She discusses the importance of accurate provider data, the challenges patients face in accessing specialized care, and how AI is transforming healthcare operations. Meghan explains how Veda automates the transfer of provider data to health plans, helping patients find in-network providers quickly and efficiently.
Meghan covers the impact Veda’s technology has had on healthcare organizations-read about our automation that saves money and improves member experience.
Deepfakes Can Damage Businesses—Here’s How To Fight Back
Deepfakes—AI-generated synthetic media in which visuals or audio are manipulated to create deceptively realistic content—are often discussed in terms of their impact on the public’s perception of current events, but they pose a growing threat to businesses as well. Created and leveraged by unscrupulous actors, deepfakes can enable fraud, perpetuate misinformation and cause lasting brand damage.
Whether they take the form of a fabricated video, cloned voice or contrived image, deepfakes can erode trust and disrupt operations in ways many companies aren’t prepared for. Members of Forbes Technology Council discuss some of the specific ways deepfakes could be used to hurt a company and what leaders can do to defend their organizations (or respond when a deepfake succeeds).
Regularly Review Employee LinkedIn Profiles
“We’ve noticed LinkedIn profiles for people who claim to work at our company but who don’t or never have. Such deepfake profiles damage our company because our people, our reputation and our brand are being abused. Leaders can respond to this specific use of deepfakes by periodically reviewing all “employees” of your company. Look for surprises and flag the frauds for review by LinkedIn.” – Robert Lindner, Veda
Veda Announces Tenth AI and Machine Learning Patent
Proprietary Technology Leads the Health Data Industry
MADISON, February 6, 2025 – Veda Data Solutions, Inc. (Veda), a healthcare technology company solving complex provider data challenges, announced its tenth patent has been granted by the United States Patent and Trademark Office, with four patents secured in the last four months.
“Our provider data solution is the only one of its kind,” said Veda Chief Science & Technology Officer and patent author Dr. Bob Lindner. “The 10 patents work in tandem to deliver automation, speed, and provider data accuracy that others can’t match. Our IP portfolio spans the entire operational pipeline from web-scale data collection, entity resolution, automatic semantic recognition and transformation, accuracy modeling, and human-in-the-loop interactivity.”
Why did Veda patent its AI technology?
Veda is committed to building responsible and transparent AI. The patent process is rigorous and ensures inventors are both creating technology with unique value while also openly sharing their research to fuel an innovation ecosystem.
What does Veda’s patented AI technology do?
Veda’s patented technology definitively solves provider data problems plaguing the healthcare industry.
Veda offers the optimal solution for automatic mass-scale demographic information management along with automatic roster ingestion, directory accuracy, network construction, and network adequacy optimization.
Veda’s best-in-class product leaves behind flawed, biased, and outdated notions of “sources of truth” and attestation, instead leaning on artificial intelligence and sound scientific design to produce reliable and reproducible results.
Is Veda’s AI secure?
Veda’s AI systems are HITRUST-certified and built entirely in-house. Veda’s implementation of its patented technology is bias and hallucination-free with all customer data and services fire-walled within the United States for maximum security.
At Veda, provider data is treated with the same reverence for security and privacy that is required for patient data.
What is next for Veda’s proprietary innovations?
With 14 more pending patents, Veda continues innovating to remain the optimal solution for provider data roster automation and data accuracy scoring.
“Veda’s technology isn’t only patented, it’s powerful. Innovated precisely for healthcare organizations and their unique data problems, our patents are essential to the delivery of fast and accurate data to Veda’s customers,” said Veda CEO Meghan Gaffney. “Veda was the first to tackle the provider roster data problem successfully and continues to develop innovative solutions in healthcare data today. With our patented approach, organizations can dramatically reduce operating costs by automating complex business rules for data extraction, transformation, and loading.”
About Veda Veda blends science and imagination to solve healthcare’s most complex data issues. Using AI, machine learning, and human-in-the-loop automation, our solutions dramatically increase productivity, enable compliance, and empower healthcare businesses to focus on delivering care. Veda’s platforms are simple to use and require no technical skills or drastic system changes because we envision a future for healthcare where data isn’t a barrier—it’s an opportunity. To learn more about Veda, visit vedadata.com and follow us on LinkedIn.
New in 2025: CMS Standards for Initial Appointment Wait Times
How to achieve compliance with Centers for Medicare & Medicaid Services (CMS) wait time standards
The healthcare landscape just got more demanding. Starting January 1, 2025, Qualified Health Plan (QHP) issuers on the federal exchanges must meet strict new standards for initial appointment wait times. This means proving that 90% of the time, new patients can schedule primary care and behavioral health appointments within 15 and 10 days, respectively. Fail to comply? You’ll need to expand your network.
Decoding the New Appointment Wait Time Standards
CMS is tackling the growing problem of long wait times head-on. The new standards, which must be assessed by a third party unaffiliated with the health plan (more on that below), require QHPs to demonstrate timely access to care. Here’s a breakdown of the standards:
Primary Care: Appointments within 15 days
Behavioral Health: Appointments within 10 days
90% Compliance Target: Health plans must meet this target with a confidence level of +/- 5% or face mandatory network expansion.
Specialists will be surveyed in future years and that standard will be 30 days.
The Stakes Are High: Why CMS is Prioritizing Wait Times
Long wait times create barriers to care, frustrate patients, and can have serious consequences for health outcomes. As the media has reported, in some cases, patients are not able to schedule an appointment for 6-12 months from the first time they reach out for care.
The completed surveys must be submitted to CMS with compliance rates, percentage of non-responsive providers, and contracts with third-party entities. Submissions are due in mid-June.
Veda: Your Partner in Achieving and Exceeding CMS Compliance
Veda’s proprietary provider data technology can help QHPs meet and exceed the wait time standards issued by CMS.
Meeting these new standards requires accurate, real-time data on provider availability. This is where Veda shines.
The first step in ensuring you can deliver on wait time requirements is auditing your directories for accurate provider-at-location data and keeping those records current.
Then, Veda can help you identify and strategically fill gaps in your network for known provider needs (from an adequacy perspective), particularly PCPs and Telehealth. This will ensure adequate access to care across all specialties and service areas.
Veda’s Dashboard: Your CMS Audit Command Center
Veda’s intuitive dashboard provides a clear, real-time view of your provider data accuracy. View your performance through a simulated CMS audit score, identify areas for improvement, and take proactive steps to ensure compliance.
Offering profiles on providers and roster automation, Veda offers true directory accuracy for providers, facilities, and groups. Veda’s solutions can help you not only meet the new CMS wait time standards but exceed them, all while enhancing your member satisfaction and solidifying your position in the market.
In this episode, #MillenniumLive is joined by Dr. Bob Lindner, Chief Science & Technology Officer and Co-Founder at Veda, for a deep dive into the fascinating world of artificial intelligence (AI). Bob shares his insights on what excites him most about AI development, exploring the balance between innovation and responsibility. Tune in as Bob discusses the differences between supervised and unsupervised learning, the critical role of data science in AI modeling, and why modeling is essential to delivering impactful results.
We’ll look at the future of healthcare data and the challenges it faces, and how Veda is positioned to lead the charge in transforming the industry. Whether you’re an AI enthusiast or just curious about the technology shaping our future, this episode is packed with knowledge, thought-provoking discussions, and practical advice for businesses exploring AI solutions.
Q&A with Bob Lindner on why sustainably-fed AI models are the path forward
As an AI company powered by our proprietary data training AI models, the article, “When A.I.’s Output Is a Threat to A.I. Itself,” in the New York Times caught our eye. Illustrating exactly what happens when you make a copy of a copy, the article lays out the problems that arise when AI-created inputs generate AI-created outputs and repeat…and repeat.
Veda focuses on having the right sources and the right training data to solve provider data challenges. A data processing system is only as good as the data it’s trained on; if the training data becomes stale—or, is a copy of a copy—inaccurate outputs will likely result.
We asked Veda’s Chief Science & Technology Officer, Bob Lindner, PhD, for his thoughts on AI-model training, AI inputs, and what happens if you rely too heavily on one source.
Veda doesn’t use payers’ directories as inputs in its AI and data training models. Why not?
At Veda, we use what we call “sustainably-fed models.” This means we use hundreds of thousands of input sources to feed our provider directory models. However, there is one kind of source we don’t use: payer-provided directories.
Provider directories are made by health plans that are spending millions of dollars of effort to make them. By lifting that data directly into Veda’s AI learning model, we would permanently depend on ongoing spending from the payers.
We aim to build accurate provider directories that allow the payers to stop expensive administrative efforts. A system that depends on payer-collected data isn’t useful in the long term as that data will go away.
The models will begin ingesting data that was generated by models and you will experience quality decay just like the New York Times article describes. We use sustainably sourced inputs that won’t be contaminated or affected by the model outputs.
Veda does the work and collects first party sources that stand independently without requiring the payer directories as inputs.
Beyond the data integrity problems, if you are using payers’ directories to power directory cleaning for other payers, you are effectively lifting the hard work from payer 1 and using it to help payer 2, potentially running into data sharing agreement problems. This is another risk of cavalier machine learning applications—unauthorized use of the data powering them.
Can you give us an analogy to describe how problematic this really is?
Imagine we make chocolate and we are telling Hershey that they should just sell our chocolate because it’s way better than their own. We tell them, “You could save a lot of money by not making it yourselves anymore.”
However, we make our chocolate by buying a ton of Hershey’s chocolate, remelting it with some new ingredients, and casting it into a different shape.
In the beginning, everything is fine. Hershey loves the new bar and they’re saving money because we’re doing the manufacturing. Eventually, they turn off their own production. Now, with the production turned off, we can’t make our chocolate either. The model falls apart and in the end, no one has any chocolate. A real recipe for disaster.
Veda’s provider data solutions help healthcare organizations reduce manual work, meet compliance requirements, and improve member experience through accurate provider directories. Select your path to accurate data.
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Standardize and verify unstructured data with unprecedented speed and accuracy.
