Skip to main content
Image of two scientist looking at data on a computer

This article originally appeared in G2xchange Health, which you can find here.

Recently, we spoke with Elisabeth Schmidt, Senior Vice President of Technology Consulting Services for Federal Health at Maximus, about the roles of automation, artificial intelligence (AI) and machine learning (ML) in the transformation journey of federal health agencies as they respond to the nation’s health challenges while also driving delivery of digitally-enabled customer experiences balanced with operational efficiencies.

Elisabeth has worked in the technology consulting industry for over 30 years, with prior experience as a Partner at IBM Consulting, as Senior Director at Eagle Hill Consulting, and for the majority of her career, as Managing Director at Accenture. Throughout, she has always focused on delivering comprehensive solutions and capabilities that enable her clients to achieve their mission and expected outcomes to best serve their constituents: citizens.

The impact of the use of AI and ML in Healthcare

To provide some context, Elisabeth noted that over the past three years, we have had to learn how to work differently – virtually – as well as more efficiently while still trying to maintain human connection and interaction, which are especially important in the provision of healthcare. In many instances, some advanced technology and tools were already in place for typical “back office” functions, and it was more a matter of maximizing their use for employees or service providers as well as for the service recipient – the citizen, the Veteran, the patient – for the “front office” functions to provide care. “Some of the keys to successful transformation of service delivery, including the use of automation and AI tools, are proactive communications and outreach; accessibility of communications as well as access to the data itself; and ability to use technology solutions in conjunction with data analytics, data governance, and cybersecurity capabilities,” Elisabeth said.

Once these capabilities are in place, the user community will develop more trust in the data being exchanged across patients, providers, and other entities. Agencies will be able to expand data interoperability, enabling more access to and consistency of the data across entities, which will allow for more timely and more personalized data delivery – ultimately providing a better user experience across the board.

In addition, Elisabeth foresees greater efficiencies. “We will continue to see an increased efficiency of the workforce, shifting workload away from more rote tasks (such as scheduling, appointment follow-ups, billing, invoicing) or more redundant tasks (answering questions over and over again) to more mission-focused, patient-centered responsibilities of healthcare provision,” she said. She envisions the use of AI, data modelling, data analytics, and Natural Language Processing (NLP) – all of which further enable data retrieval and aggregation at various levels – will increase the efficiency of healthcare providers and improve customer access. She noted that agencies should be asking how they can use these tools and capabilities to capture geographical nuances and account for the larger spectrum of possible diagnoses, enabling healthcare providers to arrive at more accurate and timely treatment plans.

Even with the benefits these technologies provide, Elisabeth asserts that it is critical to understand that automation, AI and ML are only assistive in healthcare delivery. “They really can only support healthcare delivery and decision-making by giving the providers much more easily digestible data, which may often be accompanied by data visualizations,” she said. “While healthcare providers may be able to come to conclusions more quickly, these tools will never fully replace the human interaction and the all-important relationship between a healthcare provider and a patient.”

Scaling and expanding the use of automation, AI, and ML capabilities

To truly maximize the use of automation, AI, and ML capabilities, Elisabeth emphasized that health agencies focus on technology adoption. As seemingly simple as it may be to develop a chatbot or virtual agent, “in addition to making the investment in the technology itself and the implementation of the technical capabilities, you also need to make the investment in teaching your workforce the skills to use them effectively and confidently,” Elisabeth said. One no longer needs to be a software engineer to be able to build out additional use cases to support their mission when the user community has had the appropriate training to do so.

Further, as organizations implement automation, AI, and ML capabilities, workers may be concerned that they are being replaced by technology. Elisabeth stressed the importance of having a proactive, ongoing dialogue and distinct efforts focused on helping the workforce understand how important they are in the implementation and use of any technology. “What will always be needed is the workforce’s domain expertise, knowledge and experience of how things work in order to develop the requirements, design, and build of any solutions – to inform, to teach and to validate – the data, NLP, and learning models being used in automation, AI and ML,” she noted.

Elisabeth also pointed out the importance of clearly articulating the value proposition of new technology, how it will improve mission outcomes and the workforce’s roles in making it happen– in order to gain buy-in from the workforce. These capabilities are being implemented to enable the workforce to focus on mission-critical work and delivery of an increased high-quality scalability to help patients, rather than replace the workforce.

Equally important, health agencies must proactively address the ethical and responsible use of AI. “We have to make sure that agencies are prepared and have the policies and the education in place, so everyone understands how to use these capabilities, especially since the data that is accessed and exchanged is highly sensitive health data,” she said.

Increased cybersecurity and other technology infrastructure considerations

Elisabeth highlighted that the implementation of automation, AI and ML capabilities are really part of an agency’s overall digital modernization journey, “one that should be thoughtfully laid out in a roadmap with near-term, mid-term, and long-term goals that can be prioritized and incrementally implemented throughout at a pace that meets their needs.”  For example, agencies need to consider where they are in the migration of data, applications, and infrastructure to the cloud – are they just starting this journey or are they partially there? Have they achieved the expected value of their modernization efforts along the way? How quickly do they want to (or can they) move forward? Have they integrated cybersecurity every step of the way of developing and implementing the technology solutions?

Agencies will need to achieve Continuous Authorization To Operate (cATO) and perform continuous security checks, building Zero Trust security protocols into every stage of application and system design. For health agencies these considerations are particularly critical, as highly sensitive health data is subject to strict compliance requirements under the Health Insurance Portability and Accountability Act (HIPAA) and the Health Information Technology for Economic and Clinical Health (HITECH) Act.

Driving towards increased health equity

Through the implementation of responsible automation, AI, and ML tools and capabilities, an agency’s reach of healthcare service delivery across many populations and communities can be increased.   These capabilities enable the secure and trusted exchange of communications and data for use by various parties, designed for and delivered in a manner that meets the vast needs of those being served. Elisabeth noted that the impact of these capabilities can be further enhanced through community outreach focused on the citizen experience to drive continuous improvement. She pointed out a key example of this in Maximus’s work with the CDC to deliver call center capabilities and technology solutions that addressed the ever-evolving needs of citizens throughout the pandemic.

Initially Maximus provided information to citizens about where one could find Covid-19 vaccinations, which quickly evolved into supporting the scheduling of vaccination appointments and sending Covid-19 test kits, always focused on continuous improvement of the call center agents’ tools to deliver a seamless citizen experience.  A robust employee feedback and engagement process was implemented to ensure frontline staff provided continuous input from customer insights which were then incorporated into test-and-learn pilots and program enhancements.  The workflow and screens used by the Customer Services Representatives (CSRs) were also streamlined such that they could manage an entire call in one place, rather than navigating across tools, and as a result allowed the CSR to spend more time interacting and assisting their callers and enhancing the experience for both the citizens and the employees.

Maximus deployed its Intelligent Virtual Assistant (MIVA), one of many advanced technologies implemented to deliver conversational self service to the public.  Using a multi-channel approach to provide equitable access to critical vaccine information, the citizens were able to ask in their own language and determine how they wanted to access the information available to them.  The solution’s foundation was phone-based, offering voice, TTY and language line services providing services in over 170 languages. SMS and WhatsApp messaging provided self-service options for citizens who did not need to speak to a live agent as they requested vaccine provider locations within their nearest zip code.  In addition to vaccine provider information, the WhatsApp FAQ bot was developed to provide accurate health information to Spanish-speaking communities, WhatsApp being deemed as the “trusted” communication vehicle based on community outreach and feedback. SMS was also integrated into employee tools, allowing CSR’s to send vaccine provider information, free ride share programs, and links to HHS resources as needed.

The pandemic emphasized the need for science-based and accurate health information.  Working with Maximus to bring technology and human-centered design approaches together, the CDC was able to rapidly evolve its operation to deliver timely information to its citizens, when they need it and in a way, they prefer to receive it.

“In summary, human-centered design must continue to be at the forefront of all things that we do going forward to achieve the desired outcomes of health equity and providing our citizens with access to services,” Elisabeth said. “For this to happen, our focus needs to be on the requirements to deliver on mission and expected outcomes, and the full use of technology that can make it a reality.”

What is Maximus’ role in advancing federal health agencies digital journey?

To accelerate digital transformation and modernization that is both impactful and sustainable, Maximus knows it requires a combination of front-line experience, a deep knowledge of the agency’s operations and mission, and a comprehensive understanding of when and how technology solutions and capabilities can drive an agency’s desired outcomes. As a top 20 federal contractor with 200+ active federal contracts, we have been part of transforming programs, systems and services for federal health agencies including, the Centers for Disease Control and Prevention (CDC) and the Centers for Medicare & Medicaid Services (CMS).