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Is Your Data Partner Ready for New AI Regulations?

How to Find the Right Provider Data Vendor Partnership

It seems that almost every week we see new vendor offerings within the provider data management ecosphere—each claiming to offer a revolutionary way of visualizing your data and making impactful improvements for healthcare. The provider data accuracy challenges that health plans and provider organizations face are vast, so it’s not surprising that new health tech companies are quick to capitalize. Caution: all health tech companies may not be keeping new and developing AI regulations in mind when developing their technology.

All health tech companies may not be keeping new and developing AI regulations in mind when developing their technology.

Looking at the Bigger Provider Data Picture

Quality provider data can help the healthcare industry tackle some of the biggest challenges health plans and provider networks face, like onboarding, credentialing, roster creation, and referrals. 

A commitment to improving your provider data can have great ROI potential and long-term impacts on your business and patient populations. But, with all the buzzwords and capability promises from the masses, how do you find the best vendor fit for your business needs?

Necessary Topics to Cover When Vetting Provider Data Vendors

To set you up for partnership success, here are discussion ideas for data vendor conversations:

  1. Find out the vendor’s practices for responsible data collection, storage, and validation. For example, does the vendor keep their data in the U.S.?
    Veda’s Take: You want to ensure any vendor interacting with critical data is not utilizing offshore, 3rd party data processing centers that can unnecessarily expose data and therefore, providers’ information. Consider this: If patient data is protected from offshore processing vendors via HIPAA and other regulations, shouldn’t the same protections be afforded to provider data? Veda offers comprehensive security and data protection and is HITRUST-certified.
  2. Understand the vendor’s business policies regarding AI. For example, how does an AI vendor utilize Language Learning Models? 
    Veda’s Take: Avoid risk by future-proofing your AI policies. Machine Learning can be a powerful tool, but should be approached thoughtfully and aligned with current and future U.S. legislative requirements such as President Biden’s executive order for the Development and Use of Artificial Intelligence. Warning: fewer companies comply with the proposed regulatory requirements than you may think.
  3. Ask about their reporting and measurement. How does the vendor define accurate data and measure it during and after delivery?
    Veda’s Take: Data can be compliant but inaccurate and unusable for health plan members who depend on the data to get care. Be prepared to discuss your business goals and thresholds for accuracy—consider going beyond meeting regulatory guidelines. We think healthcare data should truly be considered “accurate” if it meets a member’s needs when accessing care. 
  4. Discuss what is necessary for your business success. Can the vendor offer the necessary tools to reach your goals and eliminate what is unproven?
    Veda’s Take: Don’t be distracted by tools that may not deliver results or provide value for your goals. For example, APIs are often necessary to save time on automation. Therefore, many businesses focus on the ability to have an API connection and the API integration above even the results the product delivers. Or, in another example, the UX and the interface of a product can become a focal point above the actual functionality of the product. If you can’t trust the data and know how to interpret and use it, then connectivity and appearances don’t matter.
  5. Determine what happens first. Can a vendor partner prioritize your specific business requirements?
    Veda’s Take: All businesses have different objectives and these goals greatly impact priorities. Your vendor should clearly articulate what needs to happen first, upon implementation of the product, to realize immediate value and reach success. There is no one-size-fits-all solution when working with a provider data vendor. Before integration and during the initial conversations is the perfect time to establish an approach to prioritization within business rules. 
  6. Get familiar with the training process. What does the implementation, training, and delivery process look like for your AI data vendor?
    Veda’s Take: How a provider data vendor plans to work with you, and how they plan to train others in your organization, is key to partnership success. Beyond day-to-day use of the tools, how does the vendor recommend using the data and applying the findings? Who should be trained on what tasks? Clear and concise preparation will ready everyone in your organization.

Ensure any vendor interacting with critical data is not utilizing offshore, 3rd party data processing centers that can unnecessarily expose data and therefore, providers’ information.

Once you have a solid understanding of how a potential partner tackles the above objectives, only then can you capitalize on a business case for building a collaborative partnership with a provider data vendor.

Need more ideas on what to ask a potential provider data vendor? See Veda’s Six Questions to Ask Your Provider Data Vendor

Healthcare Business Today: Why AI Is Critical to Accelerating Value-Based Care and Reimbursement

By Meghan Gaffney

Here’s something you’ve heard before—patients are now becoming “consumers” of medical care in the same way that they make informed choices in retail and other aspects of their lives. From the patients’ point of view, the healthcare system is broken, with significant issues arising around cost, access, and quality of care.

Link to Healthcare Business Today article

The patients aren’t wrong. Over one trillion dollars is spent each year on healthcare administration alone. Those providing and subsidizing healthcare are equally frustrated by the inefficiencies and challenges that exist on the administrative front.

Value-based care (VBC) and reimbursement models have long been hailed as the solution to these problems. However, anyone who works in healthcare knows that adoption of true risk-based models has been slow. Let’s explore why. We can start by exploring the history of VBC, shed light on the “missing ingredients” for making VBC a success, and then dive into how data–specifically advanced processing of data through automation–is the key to breeding trust and accelerating the shift away from fee-for-service.

What has prevented VBC models from becoming the norm? The missing ingredient

The first VBC pilots were rolled out by Medicare well over a decade ago, yet here we are, still operating in a predominantly fee-for-service system, rather than on the other side of the transition to value as anticipated. Oftentimes, the logistics of bringing together different stakeholders and disparate systems are pinpointed as the root cause of the issue. And it’s true, to say that the logistics are complicated is an understatement at best.

But I would argue that the logistics don’t present insurmountable obstacles.What was lacking was the key ingredient to all lasting and transformative relationships– trust. For value-based contracts to operate as intended, providers and payers must have a certain level of trust in each other, as well as in the data that connects their systems and informs their mutual decision-making. The foundation of trust in financial arrangements is always data, and healthcare’s limited technological advances have prevented not only data-sharing between parties in VBC agreements, but “good” data-sharing. The result is an inability to trust that either side has the quality of data required to accurately assess cost and performance. 

The role technology can play in deepening trust by improving data quality

That’s the “bad news.” But I’m delighted to say that there’s actually quite a bit of good news. While healthcare has long been a laggard when it comes to technology adoption, the pandemic spurred accelerated adoption of AI and automation and played a critical role in moving the industry forward. The tech is ready—and now the stakeholders who truly need the tech are ready to use it.

With this in mind, let’s look at a use case that illustrates the need for technology that improves data accuracy and transparency and therefore promotes trust, the missing ingredient in VBC. In order to get their members the care they need, payers (i.e., insurance companies) have to be in constant contact with provider organizations.  Provider organizations often send data updates on participating providers infrequently and equally often those files have errors. The data are also manually keyed in by associates at the payor, a process that takes weeks and tends to create duplicative or incomplete records, as well as further contributing to inaccuracy.

This exact issue derailed a VBC pilot program that my business was a part of. A state-based health plan we worked with backed out of their VBC agreement due to lack of provider data transparency. Each month the payor attempted to reconcile which claims could be attributed to VBC contracts. There were discrepancies in the participating provider rosters that slowed this process down, and eventually, ground the entire project to a halt. Data is core to establishing trust in these agreements, and illustrates how hard it is to execute them as designed in the face of poor-quality data. And remember, this is just a single use case. There are many more. 

Ensuring that the tech being used is as transparent as it is efficient

That annual trillion dollars in administrative spend in healthcare is a major issue negatively impacting all parties involved. In a VBC or any kind of contract, the goal should always be to provide patients with the best care possible while decreasing costs. Right now, a huge driver of administrative spend is the cost of manually processing data and the downstream waste that happens when data is inaccurate. A huge step forward is ensuring there’s data transparency so that inaccuracies can be identified and addressed.

So, what does transparency look like from a technology standpoint? What should payers be looking for when shopping for solutions to automate their data? Provider groups and their payor partners need a solid foundation of data to measure performance for VBC agreements, and they also need to understand how these measurements are made. Vendors that offer data solutions should always be ready to walk their clients through their processes and make clear how accurate data is obtained, maintained, and measured. Some technology vendors even build accuracy guarantees right into their contracts.

This level of transparency in vendor-payer relationships eliminates any potential mistrust in the tech itself, which has been a driving factor in AI’s relationship to VBC. In the event something does go wrong, there is a pre-established measurement system that both parties understand and that can be used to easily identify where the error occurred.

Is AI the solution to accomplishing our VBC goals faster?

I think so, yes, but with an important caveat–the AI vendors need to build trust, too. I’ve seen first-hand within my company and from industry peers the power that data automation tech solutions have when they’re a part of contracts built on trust in the tech and the people behind it. Understanding that trust is the missing ingredient with provider-payer relationships—and by extension, other key relationships such as those with technology vendors—is key to making inroads with future partnerships.

The pandemic spurred increased health tech adoption at the same time that patients were paying much more attention to their health and engaging with medical services as savvy consumers. These factors have moved the industry to a point where it is truly ready to accelerate VBC.

You know your business. We know data.

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Resources & Insights

Provider Data Solution Veda Automates Over 59 Million Hours of Administrative Healthcare Tasks Since 2019
October 21, 2024
HealthX Ventures Blog: How Veda Is Aiming to Fix Healthcare’s Broken Provider Directories
October 17, 2024
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