Most healthcare IT leaders have already laid out their priorities for 2024 and a recent report by Bain & Company finds that revenue cycle management, clinical workflow optimization, and patient engagement are top priorities. To address the challenges in these areas, healthcare leaders have significantly increased investments in technology and now consider IT a “strategic priority,” citing its ability to enhance revenue and reduce costs by “streamlining labor-intensive processes.” These include subset areas like “revenue integrity, charge capture, and complex claims.”
Organizations can modernize their tech stacks to drive savings and reduce administrative burdens. We have identified three central areas of opportunity: data platforms and interoperability, automation, and AI.
For all our efforts towards interoperability, data remains siloed across the healthcare ecosystem and continues to be difficult to access in the delivery of care. This is why our industry is still highly reliant on APIs and third-party aggregators to share data. While healthcare is making headway with industry-wide data exchange initiatives and the increasing adoption of industry standards like FHIR®, both initiatives require a great deal of work, money, and IT resources.
Today, there are cloud-based data platforms that create a new kind of interoperability where payers and providers can share information without building and maintaining individual connections. These platforms enable data to be continuously refreshed and current, eliminating the need to question accuracy or integrity. These platforms include advanced technological components such as AI, machine learning (ML), and robotic process automation (RPA) meaning participants reap the rewards of greater interoperability without making substantial infrastructure investments.
Avaneer Health’s network and its platform are designed for interoperability, applying a modern, secure infrastructure that leverages the FHIR standard for data exchange. Thus, payers and providers communicate and transact directly, eliminating the need for third-party solutions and reducing the number of transactions needed to support operational workflows. Because the platform enables permissioned and audited data sharing without data aggregation, data owners have more control over their data.
We’re all familiar with the amount of financial waste in our industry, much of it related to inefficient manual administrative processes. While industry leaders have talked about the need for automation for years, today’s modern technologies hold much more promise than those of the past. Robotic process automation (RPA) is a prime example.
RPA works by mimicking repetitive processes through rule-based tasks. “A set of scripted processes can access applications and data sources using structured data and logic to automate decisions according to predefined business rules and conditions.” In this way, RPA eliminates the potential for human error in manual processes while also increasing productivity with fewer staff.
RPA is ideal for many patient access and midcycle processes like scheduling, coverage, and eligibility verification—all of which can impact the patient experience. RPA can also help with coding and can flag documentation requirements for prior authorizations and medical necessity as well, helping to reduce delays in care and denied claims, streamline revenue cycle processes, and optimize reimbursement.
According to a new study by KLAS Research and the Center for Connected Medicine, 79% of health executives surveyed said that “AI was the most exciting technology in healthcare.” It seems each day we hear of new clinical and administrative use cases for AI. But when it comes down to choosing the appropriate application in our own organizations, the decision should be made by measuring both short-term and long-term gains and weighing them against available resources and capabilities. Organizations must ask themselves which applications are quick wins, and which will take more time and effort. Both need equal attention.
Just 6% of IT leaders surveyed say they have a strategy in place for using generative AI, although 50% say they are or will be planning one soon.
One ingenious application of generative AI that could be considered a quick win is its use in responding to patient messages in the patient chart. We’ve heard a lot recently about the unmanageable number of emails providers receive each day from patients. While some health systems have begun charging patients to send messages to their providers via MyChart, others are testing AI as a way to answer more common questions. One approach gives patients a tool and then punishes them for using it, while the other seeks to solve the problem with innovation. This is an excellent example of how AI can be used to facilitate better care while also improving the patient experience and reducing stress on providers.
Longer-term applications of AI include better risk prediction for disease stratification, faster clinical trials, improved disease diagnoses, and better outcomes. But these more complex applications will only be beneficial if organizations can deploy them in a cost-efficient, timely, and easy-to-scale manner.
Healthcare systems have invested heavily in legacy systems that don’t typically play well with modern technologies. Bolt-on solutions and multiple APIs are required just to share information with other providers and payers. And managing these systems consumes most of a health systems’ IT budget, leaving little room or resources to integrate AI applications and models cost-effectively.
Interoperable data platforms, automation, and AI have the potential to genuinely transform our industry by enhancing patient experiences, improving outcomes, and significantly reducing clinical and administrative inefficiencies. But fully realizing these benefits requires a new kind of network through which these innovative technologies can be leveraged. That network is here today.
The Avaneer Health Network is a secure, permissioned, and decentralized network. Once a participating payer or provider connects to the network, they never have to establish a direct connection to any other participant. Data remains decentralized, and participants can control how and with whom they collaborate. Through an authorization process, their data can be shared with anyone on the network whom they have approved to receive it. Once the connection is established, data can flow freely and in real time, eliminating interoperability barriers and allowing genuine data fluidity.
Healthcare leaders have realized not just the need, but the immense potential of investing in technology. To get the most from those investments, they’ll need to be able to integrate and deploy those technologies in a way that makes them usable across the entire ecosystem. Once all the pieces are in place, we will truly be able to simplify the business of healthcare.
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