Transforming Field Reimbursement with AI: Introducing ReimbursementAI
Rachel Hohe, PhD
Oct 17, 2024
10 minutes read
Introduction:
Field reimbursement managers (FRMs) are highly skilled experts who act as an intermediary between healthcare providers, specialty pharmacies, and healthcare manufacturers by advocating for timely patient access to life-saving medications or medical devices. Their knowledge of insurance coverage, regulations in patient assistance, and health policy empowers healthcare providers with tools that reduce hurdles in treatment access. FRMs will respond in both proactive and reactive capacities to resolve patient access issues. Product lifecycle management necessitates up-to-date databases that can be proactively managed. Reactive case management occurs when prior authorization for treatment is denied, affecting timeliness of patient treatment (Braxton, 2024)(DeMarzo & Ayoub, 2021). Therefore, FRMs must be highly-knowledgeable communicators who realize the importance of urgency in patient access.
Manufacturers of expensive injectable biologics were one of the first types of company to first employ FRMs. Originally, the healthcare provider would proceed through a ‘buy and bill’ process, wherein the medical office first buys a stock of product and then bills the payer upon administration of treatment (Amplity, 2021). Nowadays, FRMs have become a part of the fabric in healthcare payer management. Their function has expanded to overcome unique access challenges that have emerged with new specialty pharmacy-delivered drugs. Some examples of these patient access hurdles by payers include NDC blocks, exorbitant out-of-pocket costs to patients, and prior authorization challenges. Prior authorization requests present a massive fiscal and health burden. It is the job of the FRM team to empower physicians’ decision-making to get their patients the care that they need. As healthcare advancements continue to occur at an ever-increasing rate, future FRMs must specialize in data analytics to effectively navigate reimbursement.
Graphical representation of the representative burden of prior authorizations as reported by physicians surveyed in 2021 by the American Medical Association, illustrating deleterious impacts of patient access issues on health outcomes. Patient harm was measured as a share of physicians who reported “prior authorization has led to a serious adverse event for a patient in their care, including hospitalization, permanent impairment, or death”. Bad outcomes was measured as a share of physicians who “reported that prior authorization has a negative impact on patient clinical outcomes”. Delayed care was measured as a share of physicians who “reported prior authorization delays access to necessary care”. Disrupted care was measured as a share of physicians who “reported that patients abandon treatment due to authorization struggles with health insurers”. Lost workforce productivity was measured as a share of physicians who “reported that prior authorizations had impeded a patient’s job performance.” Data sourced from (Mills, 2021). Survey details from (American Medical Association, 2023).
FRM teams possess a great wealth of knowledge that can be transformed into actionable insights with the assistance of third-party AI tools. The Accreditation Council for Medical Affairs (ACMA) is a leader of continuing education in medical affairs, possessing the largest database of knowledge specific to the field of prior authorization and reimbursement itself. ACMA has launched a first-in-class AI tool specifically designed for enhancing the existing capabilities of FRM teams: ReimbursementAI. ACMA’s ReimbursementAI tool combines the data-scraping power of AI, ACMA’s proprietary wealth of knowledge in field reimbursement, and the ability to seamlessly incorporate client documents to inform customized training data. In this way, the ReimbursementAI tool can decrease time spent scraping large databases for answers to queries, build large databases of interactions with healthcare providers that inform strategic corporate decisions, and increase engagement with key opinion leaders, ultimately driving increases in patient accessibility to life-saving treatment. In this article, the function of ACMA’s ReimbursementAI tool will be discussed in-depth before narrowing to the specific ways that ACMA’s ReimbursementAI tool meets those expectations. Herein, we address ReimbursementAI’s capacity to compliantly overcome long-standing pain points within FRM teams.
ACMA’s Reimbursement Tool
Core Functionalities of ACMA’s ReimbursementAI
ReimbursementAI is ACMA’s cloud-based language learning application model trained in-house on the largest compendium of medical affairs information using machine learning. The software itself is customizable to client-specific needs. To ensure easy implementation, the ReimbursementAI software integrates with pre-existing workflows, ensuring a seamless user experience. Additionally, the software is capable of accepting proprietary internal documents. The following sections will describe each feature’s function and its direct benefits to FRM teams.
Model Hosting
ACMA utilizes a series of high-quality services that host, store, secure, compute, and serve as a framework upon which the ReimbursementAI operates. Amazon Web Services (AWS) serves as the secure hosting platform for all cloud computing services which ReimbursementAI uses. Two-factor authentication, provided by Auth0, ensures safe access to the ReimbursementAI tool. Support for ACMA’s MedAffairs tool is available 24/7 through online chats with live representatives on both the ReimbursementAI platform and ACMA’s homepage (ACMA, n.d.). By providing a secure and intuitive AI platform, ReimbursementAI is poised to be easily adaptable across the field.
User Interface & Basic Navigation
Upon launching the ReimbursementAI tool, the user dashboard appears. The dashboard consists of a top-aligned menu and a welcome message, below which is a window labeled ‘Ask Question’ and ‘AI Outputs’. Underneath the ‘Ask Question’ window, a user can toggle between ‘Internal Data’ and ‘External Data’. Within the top-aligned menu there are a series of features displayed, including: ‘Search AI’, ‘Train AI’, ‘Documents’, and ‘Settings’. This highly-accessible user interface simplifies workflow and stratifies navigation, therefore positioning this tool as a powerful assistant to key players like FRMs and healthcare providers alike.
External data
By selecting the ‘External Data’ toggle tab, the user will be able to utilize an AI trained with the largest compendium of reimbursement and prior authorization information, courtesy ACMA. The user may submit a text-based query by typing inside the ‘Ask Question’ text submission box, then selecting the black ‘Ask Question’ button below. The software will then generate a concise text-based result from ACMA’s wealth of knowledge. By having the option to pose general industry questions to ReimbursementAI, users are empowered to access and utilize around a decade’s worth of educational reimbursement and prior authorization content. Since its founding in 2015, ACMA has developed the largest compendium of information in this field, ranging from regulatory standards on payer policy to regulatory document identification to government legislation in the pharmaceutical industry. FRMs may utilize this external data resource to help onboard new employees or to automate tasks like generating product lifecycle management plans with larger breadth and depth of knowledge. Likewise, this external data may be provided as a companion with traditional FRM services to healthcare providers in need of resources to support basic components of patient access.
Internal data
Alternatively, a user may choose to utilize ReimbursementAI’s ‘Internal Q/A’ by selecting it from the toggle feature. Although the use of this feature mirrors that of ‘External Q/A’, the database of knowledge must be trained on internal documents. This unique feature allows purposeful customization of the ReimbursementAI, with considerations for personal document upload and API integration with pre-existing data management tools. The AI output will provide a concise text answer to your query with specific references to internal document sources, a feature unique to ReimbursementAI’s internal data. By providing this integration capability, ACMA empowers its clients to accelerate their internal searches, widen the scope of their searches, and readily reference relevant documentation in answering queries. FRMs may utilize the internal data function of this software to inform case-by-case precedent when qualifying patients for specific therapies by utilizing historic databases. When provided as a companion software to healthcare providers, the internal data feature ensures timely and comprehensive information is disseminated. This ensures that healthcare providers have a seamless experience with their ability to effectively process appeals, thereby encouraging future dialogue between these teams and their FRM liaisons.
Documents
In order to train the AI with internal documents, the user must navigate to the ‘Documents’ tab within the top-aligned menu and select ‘Train AI’. Now, the user can upload documents in myriad formats including pdf, txt, png, and jpg. Once uploaded, the files appear within the submission window. To proceed with training, the user must click the button titled ‘Train AI’. After training, these documents will be available to view under the ‘Uploaded Documents’ window in the ‘Documents’ menu. This page lists the file name, the user who uploaded the file, the file size and type, the upload date, and options to download or delete selected files from the database. These documents are fully searchable, with a text-based search bar at the top of this page. By allowing a wide range of document accessibility, the ReimbursementAI software can digest, compile, and specify documents for restricted usage. This capability enhances specificity of results, therefore heightening quality of query responses. By uploading client-specific data, the information gathered here can inform discontinuation risk for specific patient populations by using AI predictive analytics. This empowers medical affairs teams to turn reactive workflows into proactive workflows by anticipating trends in adherence.
Modifiable Accessibility Settings
When the ReimbursementAI is purchased for an organization, member permissions can be managed within the software by the group manager. Here, the group manager can view all user profiles, control who can upload or download resources, and moderate access to internal or external queries. Moderators can change permissions of individuals over time to the tool capabilities. In this way, the ReimbursementAI tool can be integrated with user roles in mind and reduce content modification, therefore ensuring content compliance and trustability. By incorporating modifiable accessibility, a company is able to effectively manage and customize their AI tool to their specific needs. FRM teams and healthcare providers using this tool will have different needs and will therefore require different experiences. Profile management in ReimbursementAI helps to build a software that is effective and useful for all teams.
Considerations for Adopting Artificial Intelligence
Advisory boards identify legal and compliance issues arising from AI implementation across industries to strategize risk management for individualized use cases. The expertise and long-standing experience of these advisory boards help strategically implement technologies while adhering to regulatory changes in the rapidly-evolving field of artificial intelligence. Alex Shandro, a partner at Allen & Overy Shearman, is a member of one of the longest-standing firms advising use case risk in artificial intelligence technology. In a highly-informative webinar with ACMA, Shandro highlighted key takeaways from his experiences with risk management in biotechnology companies (Soliman & Shandro, 2024). This advisory relationship helps ACMA’s MedAffairsAI tool stay ahead of the regulatory curve by anticipating compliance issues before they occur. Shandro’s key insights into operational integration, oversight compliance, strategic implementation and use case risk mitigation can be accessed at ACMA’s post here [link to ‘Revolutionizing Medical Affairs with AI: Introducing MedAffairsAI’ Article].
ACMA consults experts in both AI regulation and directors of leading field reimbursement teams to evaluate possible considerations for AI integration. In doing so, ACMA’s ReimbursementAI will implement industry-standardized safeguards to protect AI software clients. This includes implementation of a software disclaimer that protects against HCP misuse. This disclaimer protects against HIPAA violations by limiting personal health record disclosure. In addition, ACMA supervises the curation of up-to-date external training data that the Reimbursement is trained upon which ensures seamless updates with emerging regulations. In order to best train their teams on AI software use, clients can take full advantage of ACMA’s training modules and FAQs on ReimbursementAI. Ultimately, with the guidance of ACMA’s expert AI panel, clients can take full advantage of ReimbursementAI, which readily anticipates changes in compliance guidelines.
Conclusion
The possibilities of AI implementation in field reimbursement are massive and have promising implications for overcoming patient access issues. ReimbursementAI, in particular, provides an intuitive platform where FRM teams can be empowered to develop all-encompassing project management objectives from project launch and throughout its lifecycle. FRM teams will be empowered to respond in a timely and effective manner to payer benefits investigations by scraping large-scale databases for historical precedents. Compliant AI will enhance the depth and breadth of database searches and provide referential evidence for each case-by-case situation. Within FRM teams, this resource is an invaluable tool to enhance existing training processes, equipping agents with the informed dialogue necessary to excel in this role. When paired with AI-powered FAQs, FRM teams can achieve agent competency across both therapeutic and regional territories. Further, this tool may also be provided as a secondary resource to healthcare providers that have a high need for services and low accessibility to FRM teams. In providing this software as a supplement to traditional FRM interactions, healthcare providers are provided a platform which increases their engagement with FRM teams. By licensing this software to healthcare providers, FRM teams increase their reach to offices they may not have otherwise had the capacity to help.
ReimbursementAI is the first-in-class artificial intelligence created to empower FRM teams to overcome these patient access issues. The crux of AI adoption issues lies in software compliance, risk mitigation, and accuracy of the model itself. ACMA’s expert panel guidance in AI compliance ensures the quality of this software that ultimately reduces risk to the end user, while ACMA’s leading expertise in field reimbursement information is integrated into the training of this software. The benefits of AI implementation into field reimbursement teams are far-reaching. In this article, we’ve addressed ReimbursementAI’s capacity to compliantly overcome long-standing pain points within these teams and propel medical manufacturer organizations into the future.
References:
Accreditation Council for Medical Affairs. (2024). ReimbursementAI Tool Demo. United States of America. Retrieved July 15, 2024.
American Medical Association. (2024). 2023 AMA prior authorization (PA) physician survey question list. https://www.ama-assn.org/system/files/2023-ama-prior-authorization-survey-question-list.pdf
American Medical Association. (2024). 2023 AMA Prior Authorization Physician Survey. https://www.ama-assn.org/system/files/prior-authorization-survey.pdf
Amplity. (2021). Field Reimbursement Managers: Overcoming Patient Access Barriers Through One-on-One Support. An Amplity Health Article. https://www.amplity.com/images/wpuploads/2021/03/FRM_Overcoming-Patient-Access-Barriers_Amplity-Health-Article.pdf
Braxton, K., Dixson, K. (2024, June 20). Career insight: A day in the life of a field reimbursement manager. YouTube. https://www.youtube.com/watch?v=IMmGtMJkPvA
DeMarzo, A., & Ayoub, D. (2021, March 2). Field Reimbursement Manager: A Day in the Life with Deena . Prior Authorization Certified Specialist Program Blog. July 2, 2024, https://www.priorauthtraining.org/field-reimbursement-manager-a-day-in-the-life-with-deena/
Mills, R. J. (2021, June 21). AMA survey indicates prior authorization wreaks havoc on Patient Care. American Medical Association. https://www.ama-assn.org/press-center/press-releases/ama-survey-indicates-prior-authorization-wreaks-havoc-patient-care
Soliman, W., & Shandro, A. (2024, March 22). The Next Frontier: Generative AI in pharma and legal considerations. YouTube. https://www.youtube.com/watch?v=Kg9LpCIZqs0
