AI in Healthcare: A Model for Managing Risks as Well as Rewards

From the inception of 'artificial intelligence' in the 1950s to its current zenith in 2024, the journey has been nothing short of transformative. AI emerges as both a beacon of innovation and a harbinger of complex challenges, reshaping industries and societies alike. The Alliance for Artificial Intelligence in Healthcare (AAIH) explains, “Large-language models (e.g., GPT) and generative image models have been in development for many years but have now reached sufficient maturity that their future ubiquity seems all but assured.” The AAIH suggests that innovation around AI and machine learning (ML) will drive “healthcare to be more human-centric through combining automation, ML, and human (and human-derived) data.”

91% of healthcare leaders surveyed by Sermo see AI and machine learning integration as important or critically important to their organization’s growth and success.

How can AI be used clinically?

The clinical use cases for AI seem almost infinite: better risk prediction for disease stratification, faster clinical trials, improved disease diagnoses, and more sophisticated wearables to capture vital health information, just to name a few. An article published by the American Hospital Association (AHA) states that one of the top clinical applications of AI is in clinical decision-making, “AI algorithms analyze a vast amount of patient data to assist medical professionals in making more informed decisions about care — outperforming traditional tools like the Modified Early Warning Score (MEWS).”

The AHA also suggests that AI holds significant opportunities in diagnostics and imaging. The technology’s benefit comes in its ability to perceive and process large amounts of both structured and unstructured data, giving clinicians more insightful data for more accurate diagnostics and more effective, timely clinical decision-making. Enhanced patient safety is yet another top application of AI, according to the AHA, due to better error detection, patient stratification, and drug delivery.

What are the benefits of using AI in healthcare administrative processes?

Clinical documentation, now undergoing AI transformation, stands as a significant administrative burden contributing to clinician burnout. The integration of electronic health records (EHRs) has shifted the patient-clinician dynamic, diverting clinicians' attention from direct patient care to extensive data entry tasks. This shift to EHRs and the need for more care documentation not only diminishes the patient experience but also leads to increased charting and documentation during evenings and weekends, thereby encroaching on a clinician's personal time.

AI, along with technologies like machine learning (ML), natural language processing (NLP), and robotic process automation (RPA), streamlines workflows such as documentation and medical coding. For instance, when recording and transcribing exam room encounters—with patient consent—large language models (LLM) interpret transcriptions, feeding data directly into the EHR. Clinicians then review, edit, and approve the notes, drastically reducing manual data entry time from hours to minutes. This efficiency affords clinicians more time for direct patient interaction.

AI- and ML-generated documentation can determine the appropriate diagnosis codes and based on the data, assign them to the encounter, and automatically submit them to billing, significantly reducing administrative burdens for clinicians.

What are the security and privacy concerns of using AI in healthcare?

With over 3,300 healthcare AI startups in the U.S. and a projected global market value of $187 billion by 2030, ensuring safety, privacy, and transparency in AI adoption is paramount. The White House's 2023 Executive Order and subsequent government-wide policy prioritizes governing AI development for improved health outcomes while safeguarding security and privacy. That is a good place to start. The overarching concerns of AI in healthcare include critical issues like data security, patient privacy, and ethical considerations. One of the most significant concerns is how the large amount of patient data required to enable AI is collected and stored. This is especially problematic considering that data typically exists in multiple silos across the continuum, meaning it needs to be aggregated from numerous sources before being used. Therefore, AI solutions require access to a multitude of systems to capture the data it needs, which creates significant vulnerabilities for healthcare organizations who are developing and using AI models.

Another challenge is how, when, and by whom patient data is used. Research published by the National Library of Medicine warns, “Beyond the possibility for general abuses of power, AI poses a novel challenge because the algorithms often require access to large quantities of patient data and may use the data in different ways over time.” The article suggests that without the appropriate privacy protections and penalties in place, organizations may decide to “monetize the data or otherwise gain from them.” While HIPAA protections are in place today, there are gray areas around what data should be protected under HIPAA and what type should not. For example, a roundtable conducted by the HHS highlights inconsistencies, “Patient-generated data, such as data collected from mobile applications and wearable devices, can also contain sensitive information about individuals ranging from fertility treatments to mental health conditions. However, there are relatively few legal guidelines that protect this emerging data type from misuse.” The broad application of AI in novel ways in healthcare requires policies and guidelines that offer clarity and stringent penalties. This is an area where any level of ambiguity is not acceptable.

“The sheer volume of data, the ability to re-identify previously de-identified data, and the challenge of navigating through the regulatory landscape make AI a unique risk in healthcare security and privacy.” Health IT Security

How can a decentralized data model improve the use of AI in healthcare?

To address the risks of using AI in healthcare, providers and payers need a new way of sharing data that ensures privacy and security while eliminating the issues of data integrity.

Today, the primary model for collecting and training data for AI solutions is centralized data aggregation, which comes with significant privacy and security risks. This approach requires considerable safeguard measures during model training and solution deployment, and it provides limited transparency of how the data is used to train the models or how the generated data is eventually shared with or used by others.

A decentralized network enables a different way of exchanging and using data, which works by enabling the following:

Permissioning access to large, distributed, real-time data sets from network participants

Allowing stringent AI governance to determine which data can be used for what purposes (ex., which data elements can be used for training Gen AI)

Including network traceability and auditing to create a detailed understanding of the data and data transformations used in the modeling process

Deploying models with sensitive data residing in a private, secure, cloud-hosted environment where payers, providers, and other network participants can collaborate and transact directly with each other, allowing Gen AI solutions to be trained to generate responses based on custom data sets

Another benefit of a decentralized network is that it significantly improves data security by eliminating the need to send data outside the network to be aggregated. Data remains within the system and under the control of the data originator, keeping patient data safe.

Embracing AI Innovation while protecting patient data

AI has the potential to greatly simplify healthcare by enhancing patient experiences, improving outcomes, and reducing inefficiencies. However, realizing these benefits necessitates a safe and integrity-focused data network. The Avaneer Health Network™ offers a secure, decentralized platform to support permissioned access to data through purpose-built solutions. One solution already in use by payers and providers is Avaneer Coverage Direct™.

Avaneer Coverage Direct delivers updated health insurance coverage information and remediates coverage misalignment through a peer-to-peer network of payers and providers. Avaneer Coverage Direct evaluates patient/member coverage information when changes are made and proactively identifies when a participant is missing coverage, recording incorrect details about a coverage, or has an inaccurate view of coverage primacy. The information is instantly available in the source system if desired. Payers and providers both benefit from improved transparency and reduced costs while patients/members benefit from reduced delays in care and fewer surprise bills.

Learn how to keep control of your data while leveraging future AI solutions

Mitigating Cybersecurity Events with a Decentralized Network

Ransomware attacks like the one that happened to Change Healthcare in February of 2024 have grown more frequent in healthcare, with 460 attacks in the U.S. in 2023. According to the Department of Health and Human Services, threat actors have become increasingly aggressive in the healthcare sector, targeting both “known and unknown weaknesses in a victim’s environment.” The U.S. Department of Health and Human Services (HHS) suggests ransomware generally moves laterally throughout a network so segmentation can help limit its impact by containing the event within a single segment. This built-in segmentation is one of the benefits of a decentralized network.

What is a decentralized network?

Typical system architectures are designed with a central server through which all information and actions are processed. Conversely, decentralized networks are designed to use multiple distributed nodes, each acting in the same capacity as a central server while still managing its own information and connecting with other nodes.

In a decentralized architecture, if any single node on the network encounters an issue, it can be taken offline or isolated.

How does a decentralized network work?

On a decentralized network, participants have their own private, secure cloud-hosted environment. It’s populated with a prepackaged suite of utilities and services that connect, collaborate, and transact directly with other participants on the network. This eliminates the need to establish and maintain multiple single-use, point-to-point connections.

A decentralized network enables data to be securely shared, with the appropriate permissions, between participants without exposing the data to an intermediary. Because the data is not centrally aggregated, it remains in the control of each participant. Though the network provides an auditable record of data exchange between participants, the network itself never stores or accesses the data.

A decentralized network eliminates the need to deal with numerous custom, proprietary integration requirements for APIs and third-party platforms.

The benefits of a decentralized network

On a decentralized network, participants control how, with whom, and for what purpose data is exchanged. In this way, a decentralized network speeds the rate of data exchange while keeping data secure between all network participants. Other benefits include the following:

Provides increased data integrity, immutability, and traceability.
Enables data originators to control who has access to their data and how and when it can be accessed.
Data is always available when and where it’s needed without having to be requested, aggregated, and validated.
Data can be provided in any format or standard, and normalized when used on the network
Participants experience a reduced need to manage multiple interfaces and stand-alone connections.
As the network grows, data becomes more valuable.
Due to its design, participants can leverage the network for unlimited use cases.

How Avaneer Health’s decentralized network is different

Avaneer Health’s robust data governance model is a primary pillar of the Avaneer Network^TM and platform. The network’s decentralized architecture ensures that participants always remain in control of how, when, and by whom their data is accessed. Solutions available on the network are installed to each participant's network environment, eliminating the need to send their data to someone else’s cloud.

Unique capabilities of the Avaneer Health Network

Bring your own key. Participants can maintain adherence to their organization’s security requirements by bringing their own encryption keys to the Avaneer Network, ensuring their data is under their control.
Access control. Attribute-based access controls (ABAC) and configurable authorization controls enable participants to control what data is exchanged with their trading partners.
Secure environment. Network participants receive a private, secure environment provisioned with HIPAA-compliant health data storage and communication services.
Localized and in the cloud. Applications offered on the Avaneer Network are localized and operate where the data is stored.
Transparency in data access. All network activity is HIPAA-compliant, logged, and auditable.
Deny-by-default security architecture. No communication to any other participant or any Avaneer Health service is allowed unless explicitly turned on by the owner, providing security throughout the data layer, networking layer, and application layers.

A decentralized network in action: Avaneer Coverage Direct

One of healthcare’s most onerous, error-prone administrative processes is determining patient insurance coverage. Issues in this process can lead to denials, delayed reimbursement, write-offs, and surprise patient bills. Avaneer Health is simplifying the entire process with Avaneer Coverage Direct^TMby giving payers and providers near real-time coverage information that is always accurate, up to date, and available within their environment.

Because the Avaneer Network has a decentralized architecture, when any change is made to a member’s/patient’s coverage data, Avaneer Coverage Directautomatically determines missing, conflicting, and incorrect coverage details, and immediately updates all permissioned payers and providers on the network. In this way, Avaneer Coverage Directincreases transparency and data accuracy, without the data having to be sent or accessed outside of the network.

Because the Avaneer Health network is decentralized, payers and providers always retain control over their data; Avaneer Health does not see or store the data that is shared between participants.

Avaneer Health’s decentralized network allows payers and providers to share coverage and other types of transactional data without having to hand it over to clearinghouses and other third-party vendors and without having to build and maintain multiple, complex, single-use connections. Patient data is kept safely within the network.

The time to act is now

Cybercrimes targeted at healthcare systems are on the rise and organizations need to do all they can to prevent and protect against these threat actors. Decentralized networks can play a key role in doing just that.

Want to learn more about Avaneer Health? Contact us.

Decentralized Network: How Does It Work?

In a previous blog, we discussed a new approach to interoperability that doesn’t require data to be requested, aggregated, and validated each time it’s used or shared. Unlike a traditional network design, a decentralized network enables healthcare permissioned stakeholders to access continuously refreshed, always current data in real time, allowing them to communicate, transact, and collaborate with any other network participant.

In this blog, we discuss how a decentralized network enables more effective collaboration, drives innovation, and improves the healthcare experience.

How does a decentralized network work?

An excellent example of how a decentralized network works is the real-time claim adjudication process. This workflow includes:

A provider submits claims directly to a network payer from their home base instead of through their traditional clearinghouse pathway.
The network’s real-time adjudication (RTA) solution automatically examines each claim’s details against the payer’s RTA criteria.
If the claim is “clean” and deemed processable by the payer for RTA, the claim will be automatically directed to the payer’s designated RTA endpoint.
If the claim is not processable by the payer for RTA, it will automatically be directed to the payer’s traditional clearinghouse endpoint.

The ability for stakeholders to transact directly with each other simplifies the business of healthcare, modernizing how it operates and ultimately, lowers the cost of administering healthcare.

How do data security and immutability work on a decentralized network?

On a decentralized network, participants always have control over who can access their data and how that data can be accessed. This is made possible through services that manage and unlock access to permissioned data based on the use case.

When participants join the network, they must register their clinical or administrative data associated with members, patients, and practitioners. Each is given a person ID, a unique network identifier. When the network detects other organizations who share data for the same person ID, data-sharing authorization policies are automatically evaluated to determine if access to data is permissible. Where authorization is approved, data is shared directly and securely between network participants. The network itself does not see or store the data that is shared between participants.

The authorized transactions between network participants are trackable, auditable, and immutable. This effectively lowers issues of distrust, friction, and data hoarding between payers and providers.

How does a decentralized network improve the patient experience?

The administration of healthcare—those revenue cycle processes like coverage verification, prior authorization, and collections—are highly complex and often involve inefficient, manual, error-prone workflows that can impede a patient’s ability to receive timely care or to know how much it will cost. A decentralized network provides an entirely new way to administer those processes by:

Leveraging FHIR for standardizing data
Allowing real-time, permissioned access to accurate data for all healthcare stakeholders
Enabling processes that used to take days or weeks to be completed within seconds or minutes
Eliminating time-consuming, manual, error-prone workflows
Giving providers the information they need when and where they need it to provide high-quality patient care

Instead of continuing to add fixes on top of a broken system, healthcare needs to create a new, better system—a system built with a new kind of interoperability. Learn more here

How healthcare can become more interoperable with a decentralized network

The back-office administration of healthcare is fragmented and full of manual, inefficient processes that impact patient care, provider reimbursement, and costs. These processes are a result of our inability to connect effectively. While payers and providers have invested millions in multiple platforms and legacy systems, many still lack full integration and interoperable functionality.

The annual cost of administrative inefficiencies in the U.S. healthcare system has reached into the billions, with billing, coding, physician administrative activities, and insurance administration being primary drivers.

An ecosystem full of obstacles

The challenges of today’s outdated interoperability architecture are significant. From a connectivity standpoint, partner connectivity and workflows require multiple vendors and system integrations. From a data management standpoint, today’s interoperability systems require numerous third parties to support, which has led to a lack of traceability, control, and auditability, as well as security issues. These third parties must aggregate, store, and repurpose data, which means they control the redistribution to payers, providers, and partners. Because of this, payers and providers have little control over when, where, and how they can access it.

Most healthcare organizations have invested in digital and interoperability strategies that, ultimately, have narrow potential and limited scalability. The high costs to maintain connections to multiple third parties require payers and providers to implement and maintain numerous single-use, point-to-point connections.

We now have a web of interconnected systems that don’t easily adapt to evolving trading partner business needs. This has resulted in a wide array of custom, proprietary integration requirements for APIs and third-party platforms—all of which further deteriorate our industry’s quest for interoperability and administrative efficiencies.

Manual transactions, administrative burdens, poor interoperability, and costly and ineffective legacy systems have led to increased total processing spend, provider burnout, poorer outcomes, and limited innovation.

A new kind of interoperability in healthcare

Instead of continuing to add fixes on top of a broken system, healthcare needs to create a new, better system—a system built with a new kind of interoperability.

The term interoperability has different meanings. While we can all agree that sharing data is at the heart of the definition, there are disparities in what that looks like. For example, Fast Healthcare Interoperability Resource (FHIR) has given us a common set of protocols and standards for a payload of transactions on a network. Still, alone, FHIR does not give us full interoperability.

In a truly interoperable healthcare system, data would not need to be requested, aggregated, and validated each time it is needed. Instead, it would be continuously refreshed, always current, and accessible in real time via a secure, decentralized network to those who are permissioned to access it.

What is a decentralized network?

The typical network design consists of a primary server that manages all the information and activities on the network. On a decentralized network, there can be multiple servers acting as primary servers. They each manage information on their own while still connecting with each other. In this way, they “balance the load and distribute the work across the system.” This helps improve network resiliency and data redundancy; if one node goes down, the others are unaffected. Likewise, because data exists in multiple locations throughout a decentralized network, it cannot be changed in one place without changing it across the network.

Benefits a decentralized network can deliver include:

Participants have increased data integrity, immutability, and traceability to a single source of truth.
Data originators maintain control over their data and who has access.
Data is always available when and where it’s needed without having to be requested, aggregated, and validated.
Data can be consumed in any format: API, XML, database, etc.
Participants experience a reduced need to manage multiple interfaces and stand-alone connections.
As the network grows, data becomes more valuable.
Due to its structure, participants can leverage the network for unlimited use cases.

Eliminating data silos and resolving payer-provider friction

Payers and providers have made progress in improving data accessibility throughout their own enterprises but remain challenged to seamlessly make data accessible between organizations. That lack of data fluidity has led to an industry with a complete lack of transparency that has led to friction, distrust, and data hoarding.

With a decentralized network, payers and providers achieve complete transparency and data fluidity, and they do it without involving third parties. This allows for enriched transactions, providing more actionable patient and procedure-level specificity and clarity. Without a third party, payers and providers require fewer transactions to support operational workflows, while improved data insight supports more effective data management strategies.

This new way of transacting healthcare is not just redesigning current processes. It’s not just about streamlining the way we currently do things. It’s about disrupting how we conduct healthcare and doing things differently. It is about simplifying the business of healthcare.

A new era of interoperability

While we’ve made progress on the road toward interoperability, we have to ask ourselves if our current trajectory can get us where we need to be. Avaneer Health sees a new way forward. We are building a digital ecosystem that accelerates change and enables us to reinvent how healthcare operates. Our decentralized network is now live, and we invite you to join us as we reimagine healthcare together.

Webcast: Digital Transformation – How Automating the Back Office Delivers Consumer Trust

There’s been a lot of conversation about digital transformation, interoperability, and the rising administrative costs in healthcare. What if all three challenges could be addressed by digitizing the back office? Digitizing the back office is similar to how retailers have automated their processes and infrastructure to create experiences that are consumer-friendly and more efficient. It’s now possible in healthcare.

Join an exploration of how healthcare could work differently as the panel members challenge the way healthcare approaches data exchange today, what is meant by digitizing the back office, how the revenue cycle can be improved with automation, and how it could impact the healthcare experience. Payers, providers, and innovators are coming together to collaborate.

During the webinar, the speakers will be discussing:

How to move from point-to-point ecosystem to a connect-once-to-many
Ways providers can collaborate and co-create with payers to improve the patient healthcare experience
Ways payer-provider relationships can evolve and lower healthcare costs
How a decentralized, peer-to-peer network eliminates layers, complexity, and fragmentation in administrative processes and technology
Insight into how an interconnected, digital back office can support common processes for payers and providers while automating revenue cycle processes in a new, re-imagined way

https://youtu.be/wdJ30wRwH5U