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.
Spring 2025 Highlights on Federal and State Regulations
As the first quarter of 2025 draws to a close, the federal government and various states have wasted no time in implementing enhanced provider directory reforms aimed at ending ghost networks and increasing healthcare access.
These new regulations mandate that the initial appointment for behavioral health care must occur within 10 business days of the request or 7 calendar days following hospital discharge. Health plans that are unable to meet these time frames must offer out-of-network mental health or substance abuse coverage at in-network rates.
Health plans must also verify the accuracy of their behavioral health directory at least annually and include a host of additional information, including telehealth, languages spoken, facility affiliation, and restrictions on the scope of care (e.g., age or mental health conditions treated).
Maryland Provider Directory Legislation
Effective October 1, 2025, health plans in Maryland must confirm that their online directories are accurate as of the date of posting, and commit to updating their online information within 2 days of receiving notice of a change from a provider (15 days for dental carriers). Every 90 days, the accuracy of the provider directory must be verified.
The information that must be included in provider directories has also expanded to include name, address, contact info, specialty, accepting new patients, gender of provider, languages, facility information, and a statement that advises members to confirm the provider is in-network and participating in the enrollee’s health plan.
Finally, Maryland now requires that health plans periodically review a “reasonable sample size” of their provider directories for accuracy and retain that documentation for submission to the Maryland Insurance Commissioner upon request.
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.
If we can speed up end-point to end-point connections of the healthcare lifecycle and remove additional steps in the clerical process, it will result in improved patient experiences.
However, simplifying workflows isn’t enough unless the data driving the information is accurate and timely.
In the fast-paced world of healthcare, sluggish provider data is a liability, not a luxury. Backlogged rosters pile up, decisions stall, and resources drain away. But what if provider data moved faster?
How Veda’s Speed Redefines Provider Data Management
Imagine what is possible when automation delivers provider rosters at unprecedented speeds. That’s the power of Veda. We’re not just automating data; we’re redefining it. In the future of provider data, speed isn’t just a goal – it’s how we connect health systems and payers to solve complex healthcare data challenges.
Manual provider data approaches are specifically troublesome when handling large provider rosters, some containing hundreds of rows. Handling the volume of data created in healthcare every day is unfeasible without AI.
Where AI Comes In
One of the main benefits of AI is the ability to quickly wrap up tasks—especially when compared to manual methods and reduced processing times free up resources for other meaningful tasks.
Large, unruly provider rosters or atypical formats? Not a problem with robust and reliable (and patented) AI. When data quality is maintained by automation, it also means rosters don’t need addressing or fixing again later.
AI also delivers on what we call “synthetic attestation.” This is an attestation that occurs with no provider intervention or effort. While this is important in all specialties, it’s especially impactful for behavioral health when providers do not have precious moments available to pick up the phone and self-attest. Synthetic attestation uses the data providers are already creating in their day-to-day workflows.
Faster Data, Faster Care
With accurate data that quickly gets to where it needs to be, providers are displayed correctly, decision-making is improved, and patients have faster access to care.
Meghan: When we founded Veda, we set out to create lasting infrastructure in the healthcare industry that allows accurate data to flow automatically between payers and providers. That meant inventing new ways of processing data that were both secure and accurate, and then publishing our work through the patent process. Ten years later, we are staying true to those objectives— we’ve built AI tools to modernize healthcare and we’ve shared our discoveries through the patent process so our solutions can fuel further innovation.
Bob: We needed to bring a fresh perspective to the problems surrounding provider data that have remained stagnant for over four decades. By creating wholly new approaches to the trillion-dollar data administration problem in healthcare, we knew that our solutions were innovative and unique. So we began early in our company’s history with the patenting of Veda’s technology—protecting our inventions in the short term, while also benefitting all of us in the long run.
Veda’s patents protect our entity resolution engine, AI modeling engine, ML training data process & platform, and web-scale data collection.
How else has Veda committed to AI development?
Bob: I’m an astrophysicist and I built AI tools in radio astronomy before founding Veda. Scientists have been building innovative AI tools for decades and have a cultural rigor that drives them to test and publish their findings.
We’ve recruited a team of PhD scientists—from physics to molecular genetics and astronomy—who help build and test Veda’s in-house LLM technology, train our machine learning models, and develop the infrastructure that is the foundation for Veda’s patented systems.
What makes your AI systems different from others in the industry?
Bob: Our AI is trained on Veda’s proprietary training data, which is ethically sourced and high quality. Our training data is used to fine-tune Veda’s models and help solve critical healthcare-specific tasks with the highest possible performance.
Plus, Veda’s AI models are entirely owned by Veda with no external dependencies. Our application of AI differentiates us from others in the industry because it leverages LLMs and contextual understanding but does not produce hallucinations. We allow the model to select correct answers, not to invent free-form text.
Meghan: Our company is founded on scientific rigor and was built specifically for healthcare from Day 1. We have over 80 combined years of AI expertise, and our commitment to science and data integrity compels us to approach problems differently. It hasn’t always been easy. We did the hard work upfront. We threw out the rule book and asked ourselves, “How do I ensure I can access care?”
Putting ourselves in the patients’ shoes is how we began to turn these challenges on their heads and look at them differently—we’ve calibrated our success to the patient’s ability to use the data to access care. What does that mean technologically? It means our AI systems must provide hallucination-free, predictable, and measurable results because that is what our customers expect and it is what patients deserve.
Bob: It was essential we build the system in a new way. The blend of patents is what makes our AI systems so unique. The patented technology works together, in parallel, to accomplish complex data curation challenges with speed and accuracy that was previously thought impossible.
Which provider data problem is Veda’s AI solving?
Bob: All of them. But the one I’m particularly excited about, and that our most recently granted patent underscores, is our ability to automate intake at scale.
Meghan: Veda’s technology isn’t just a single model. It offers many capabilities working in tandem towards one comprehensible function. There are several foundational data challenges that our technology solves. One of the unique benefits of our patented technology is that it can be assembled in different ways to address many kinds of healthcare industry problems.
Bob: For example, our patented entity resolution system efficiently matches the identity of healthcare providers. The special challenge in this problem is that healthcare providers change lots of their information over the course of their careers, so the system needs to connect their identities while allowing for a normal amount of drift in some fields over time.
Why do you need AI to solve provider data problems?
Meghan: Veda’s AI can cut through data barriers and ensure that people can access care when they need it the most. That’s why we founded Veda—because everyone deserves access to accurate, up-to-date information that empowers them to get the care they need.
What are the risks of using AI in healthcare and how can they be mitigated?
Meghan: While everyone is looking to AI and automation for solutions, in healthcare the AI isn’t living up to the hype. In a race to reduce costs, many have lost sight of the problem they are trying to solve and have left out foundational components of professional services, actual results, and rigorous testing. In fact, I think the irresponsible development of some AI tools could negatively impact the companies that are taking a transparent and tested path.
For instance, imagine a business trying a new product for the first time, and it doesn’t go well. It breaks, it’s costly, and leaves a negative impression. After that bad experience, you might be reluctant to try another product in that category. This can happen with AI too—if one company delivers poor results, people might dismiss AI solutions altogether and revert to outdated methods, which ultimately hurts innovation.
Bob: We succeed with AI when it is effective, robust, and focused on responsibly making an impact. While there is a risk posed by poorly designed and underperforming tools, I see an opportunity for Veda to prove our integrity to the industry. We’re proud to showcase our patented AI and machine learning solutions, which were developed and tested with an unwavering commitment to scientific rigor and ethical, security-forward principles.
Ready for Veda’s provider data solutions? Contact us.
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.
HealthX Ventures Blog: How Veda Is Aiming to Fix Healthcare’s Broken Provider Directories
Q&A with Veda CEO Meghan Gaffney and HealthX Ventures on how Veda leverages automated data science and machine learning solutions to provide healthcare payers and networks with the most accurate and comprehensive data available.
When you or someone you love needs care, it would make sense to seek help from a directory of providers who are in-network and available to help. Unfortunately, this is one of the most painful parts of America’s broken healthcare system. One of the most shocking and significant barriers for patients seeking care in today’s healthcare landscape is the vast amount of inaccurate provider directory data. This inaccurate data creates frustration, delays, and inefficiencies that negatively impact both the patient experience in finding care, and also contributes to negative overall patient outcomes. Now, imagine loved ones dealing with memory loss, a behavioral health crisis, or long Covid—and finding the right provider becomes an even greater challenge.
Veda, co-founded by Meghan Gaffney, addresses this critical issue by leveraging automated data science and machine learning solutions to provide healthcare payers and networks with the most accurate and comprehensive data available. By curating data from over 300,000 unique sources, Veda offers real-time, precise profiles of more than 3.5 million healthcare providers, facilitating better decision-making and improved patient experiences.
Imagine this: you use your health insurance company’s online directory to find a doctor at your preferred location and needed specialty, only to be met with incorrect phone numbers, wrong addresses, or no information at all. You’re stuck making phone calls that lead to nowhere, and wasting precious hours navigating bad information while experiencing delays in actually getting the care you need most. After years of diving deep to the complexities around this problem, Veda is at the forefront of clean data and better access to care. Veda’s tools correct inaccurate data and make it possible for members to get what they truly need: the ability to easily and quickly make an appointment with a healthcare provider.
One of Veda’s earliest supporters was HealthX Ventures. With a mission to improve access to care, HealthX found Veda working at the forefront of health equity and contributing to better outcomes for all.
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.
CMS 2025 Final Rule: New Behavioral Health Requirements for MA Plans
Mental Health Awareness Month and Summary of New CMS Final Rule
Fitting for Mental Health Awareness Month, the Centers for Medicare & Medicaid Services (CMS) recently released its 2025 Final Rule that, among other things, aims to improve access to behavioral health providers for Medicare Advantage members.
Ready to learn about the CMS 2025 Final Rule and Veda’s strategic approach to its behavioral health network requirements?
The CMS 2025 Final Rule significantly expands the behavioral health network requirements for Medicare Advantage (MA) health plans. As reported by Fierce Healthcare, all Medicare Advantage plans will likely see increased administrative burdens due to the behavioral health network expansion requirements.
Not only is Veda a proven and trusted partner for achieving compliance with CMS requirements, Veda’s solutions are unrivaled in their ability to help health plans verify, expand, improve, and map their behavioral health networks.
Here are the behavioral health requirements covered in the Contract Year 2025 Medicare Advantage and Part D Final Rule and Veda’s approach:
New “Outpatient Behavioral Health” Category Added to Network Adequacy Evaluations
Veda’s curated dataset includes accurate information for even the hardest-to-validate specialties, credentials, and facility types— requiring no additional burden on health plans and health systems.
Wide Range of Specialists Included in “Outpatient Behavioral Health” Category
More specialties and outpatient care classifications were added to solve behavioral health provider shortages. The specialists in the new “Outpatient Behavioral Health” category include MHCs, MFTs, Opioid Treatment Program providers, Community Mental Health Centers, addiction medicine physicians, nurse practitioners (NPs), physician assistants (PAs), and clinical nurse specialists (CNSs).
What Can Veda Do?
Veda offers current and complete outpatient behavioral health provider profiles, on each of the specialties above, containing the necessary details to contract with providers and meet adequacy requirements.
Skill Sets of Certain Behavioral Providers Must Be Verified
To address concerns that NPs, PAs, and CNSs have the requisite skills and training to address the behavioral health needs of plan members, MA plans must independently verify that the providers they are adding to their network have furnished (or will furnish) behavioral health services to at least 20 patients within a 12-month period using information such as (i) MA plan’s claims data, (ii) prescription drug claims data, (iii) EHRs, or (iv) similarly reliable data.
What Can Veda Do?
Veda partners with customers to develop effective ways to complete the requisite independent verifications, utilizing the best data available in the industry. Our proprietary Vectyr database is updated 24/7 to include the most up-to-date, complete, and accurate provider data in the behavioral health space. This data can help MA plans verify behavioral health providers and comply with CMS’s requirements.
“Outpatient Behavioral Health” Facility Added to Time & Distance Standards and Telehealth Specialty Requirements
CMS now includes the “Outpatient Behavioral Health” facility specialty in the list of specialty types that will receive a 10% credit toward meeting time and distance standards. Additionally, MA plan’s networks must include at least one telehealth provider within the Outpatient Behavioral Health specialty.
What Can Veda Do?
Veda’s nationwide database can identify telehealth providers, flag whether a provider accepts patients at their practice location, and help source providers to meet the new behavioral health requirements. We can also help MA plans ensure compliance with CMS’s time and distance standards.
Veda is Equipped to Meet The Needs Introduced By The 2025 CMS Rule Changes
Veda excels at helping health plans and systems connect members with behavioral health services, treatment facilities, and telehealth providers. The 2025 MA rule changes are an opportunity for health plans and health systems to explore how Veda can help them expand, improve, and map their behavioral health networks and verify the claims data for behavioral health providers.
Veda’s solutions can help connect members to quality behavioral health services more quickly, efficiently, and at less cost than the traditional methods relied on in the past. Armed with the most accurate provider data available, Veda’s solutions contribute to positive member experiences while helping people find the right care for their behavioral health needs.
Provider Data Accuracy Verified By Third-Party Audit
Independent Audit Says Veda’s AI Precision Exceeds 90%, Solving Ghost Networks and Payer Network Attestation Challenges
Veda is paving the way for improved data quality, transparency, and accountability in healthcare through continuous validation and testing of our AI-powered solutions. Our scientific rigor commits us to continuously testing our methodology and we believe all AI-powered data solutions should undergo an unbiased independent validation of their data. Learn about our approach to healthcare data challenges and the third-party study performed by Erdős Institute proving our data accuracy.
Provider data management is inherently flawed. The information found in provider directories is often manually updated, the scope of required information keeps expanding and information changes often; practices move, physicians change practices, and contracts between practices and health plans expire. Multiple industry reports state between 20% and 30% of directory information changes annually.
With provider data accuracy rates of 90+%, the study highlights the potential of automation and machine learning in achieving high levels of data accuracy
Reinforcing Commitment to Accountable AI-Powered Solutions in Healthcare
To prove our products and approach to provider directory accuracy are best-in-class, the Erdős Institute conducted a blind third-party audit of Veda’s Vectyr product.
Vectyr is Veda’s curated dataset that powers all our provider data products. With Vectyr’s continuously monitored and validated data, Veda customers can quickly find correct provider information with the confidence of Veda’s optimal accuracy. Many back-office workflows—like directory management, credentialing, and claims—need access to accurate, up-to-date provider information. Our Vectyr product curates data from over 300,000 sources including NPPES, DEA, and state licensing organizations.
Why validate with impartial analysis?
As a leader in the industry, armed with proprietary solutions, we understand the key to solving complex healthcare problems lies in innovative technology. We’re taking the lead again, this time via rigorous third-party validation. By subjecting our technology to impartial analysis we’re taking a step forward in the evolution towards greater transparency.
Employing rigorous methodologies and independent sampling techniques, ensuring an unbiased assessment of provider directory accuracy? Sounds like our scientific approach to everything we do. Additionally, having an independent institute like Erdős conduct the validation study safeguards against potential conflicts of interest and ensures the credibility and integrity of the findings.
Erdõs’ Method for Proving Accuracy
To gauge provider data accuracy, Erdős and Veda simulated a Centers for Medicare & Medicaid Services “secret shopper” audit. Callers attempted to make an appointment on behalf of a patient and collect information that would be necessary to do so: the phone number and location of the provider (which are typically major areas of inaccuracies). The audit provided a measure for the main appointment information and manual research was used to measure more detailed provider information.
To reduce bias in the CMS simulation, Erdős created a sample of NPIs for the measurement. The selection of the sample was aimed to be representative with respect to geographic categories of rural and urban and focused on stratified sampling by specialty. In the total sample, 184 NPIs were called. Of these 184 NPIs, 92 phone numbers and 118 locations could be assessed.
The call-based outcomes found phone and address accuracy are consistent at 90%. Moreover, Erdős found that additional Vectyr fields were also highly accurate. For example, the Vectyr database demonstrated accuracy levels of 99% for fields such as languages spoken. With provider data accuracy rates of 90+%, the study highlights the potential of automation and machine learning in achieving high levels of data accuracy.
Reinforcing Commitment to Accountable AI-Powered Solutions in Healthcare
With a commitment to accountable AI-powered solutions and five approved patents in the industry, we believe all healthcare data vendors need to think more rigorously about what “correct” data means. Attestation does not create quality data. Patients don’t need attested data, they need correct data. Therefore, data vendors must measure performance the same way patients do: making an appointment on the first try, with the correct information. We promise accuracy, and we deliver.
ViVE 2024 brought together health tech innovators, vendors, investors, and media. What did Veda bring? Engaging discussions around Medicare Advantage, AI in healthcare, ghost networks, and rural health. Not to mention some heavy media coverage announcing our Humana partnership. Plus, a little fun with a certain famous car to showcase Veda’s ghost network-busting abilities. (We were in Hollywood after all.)
Rural Healthcare and Data
“The way for rural healthcare to succeed is to make it easy to find a doctor, to be a doctor and to pay a doctor,” said Dr. Bob Lindner, Chief Science & Technology officer at Veda during a panel on the challenging rural healthcare landscape. “All of these three things have challenges that can be traced back to the data.”
Bob presented data as a tool that rural health systems can utilize to access accurate information on traveling doctors, a unique offering in rural areas. As rural health faces more hits and challenges, data has the answers.
Veda will use its patented automation technology to analyze, verify, and standardize Humana’s data to ensure the information is accurate and comprehensive, along with real-time scoring of data quality.
Whether you were building a mini-fig or entering to win an ECTO-1 replica, plenty of fun was found at the Veda booth. With a page taken from a beloved movie franchise, Veda showed off its ‘ghost-busting’ abilities and talked ghost networks.
Ghost networks are provider networks that appear robust and full of available providers but actually contain bad data and thus, much more limited availability and unreachable providers. These “ghosts” are no longer practicing, not accepting new patients, are not in-network, or have errors in their contact information.
Veda’s accurate data eliminates ghost networks, improves member satisfaction, and stays ahead of emerging regulations.
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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