As we kick off 2024, we wanted to start the new year with a series of 2024 Health IT predictions.  We asked the Healthcare IT Today community to submit their predictions and we received a wide ranging set of responses that we grouped into a number of themes.  In fact, we got so many that we had to narrow them down to just the best and most interesting.  Check out our community’s predictions below and be sure to add your own thoughts and/or places you disagree with these predictions in the comments and on social media.

All of this year’s 2024 health IT predictions (updated as they’re shared):

• John and Colin’s 2024 Healthcare IT Predictions
• Health Equity Predictions
• Healthcare Cybersecurity Predictions
• Telehealth and VR Predictions
• Value Based Care Predictions
• Pharma IT and AI Predictions
• Healthcare Interoperability, Data, and Cloud Predictions
• Healthcare Workforce Predictions
• Healthcare Generative AI and Data Predictions
• Healthcare AI Regulations and Ethics Predictions
• Cautionary Views of AI
• Patient Preditions
• Uses of AI in Healthcare Predictions
• General Health IT Predictions
• Health IT Predictions (on video)
• Healthcare AI Predictions

And now, check out our community’s Uses of AI in Healthcare predictions.

Greg Wujek, Global Health Industry Consultant at SAS
Robots as providers comes of age.
The use of robots in health care will exponentially mature with the development of robots capable of performing basic medical tasks, such as taking vital signs, administering medications, and providing wound care. Expansion of the use of robots in telemedicine and remote patient monitoring will enable health care providers to reach patients in underserved areas.

Joel Diamond, MD, Co-Founder/Chief Medical Officer Aranscia; Co-Founder 2bPrecise at Aranscia
Artificial intelligence was a major buzzword in the world in 2023, and that was also the case in the healthcare space. 2024 will likely see continued hype regarding A.I. in medicine in all aspects. True advancements will be seen in predictive algorithms for drug benefits and toxicities, particularly in cancer treatment.

Caroline Carney, President of Behavioral Health and Chief Medical Officer at Magellan Health
AI in behavioral health: Now is the time to engage
The behavioral health community must quickly elevate discussions about what constitutes the appropriate use of generative AI. As generative AI capabilities rapidly expand, the age-old and important tension between high-tech, human touch, and high-touch promises to make significant advances in the coming year.

There is an understanding that human-to-human connections in behavioral health are necessary–especially when the potential for self-harm is involved. However, we must weigh the benefits of human rapport against the shrinking healthcare dollar as we consider the potentially positive impacts of AI. For example, is it better for someone seeking crisis care to be connected to the appropriate help via a call center, or voice-distress detection automation that connects them directly to an individual? Arguably, AI that can accurately measure the distress in someone’s voice might be more helpful in routing through a call center. Alternatively, should individuals be informed that the app they are chatting with is AI generated, and not a human interaction?

As behavioral health practitioners, we must make our voices heard from the very beginning of the generative AI conversation to bring the evidence-based data and experience to the conversation. It is all too easy for non-clinicians to bear on what is a therapeutic clinical experience. What are the measurements needed to ensure that quality care is delivered? Now is the time to engage and help inform the fast-developing guardrails and regulations that will undoubtedly impact how we deliver patient care.

Alexander Nazem, Co-founder and CEO at Nomad Health
As with seemingly every other industry, we can expect that AI will play a large role related to the healthcare workforce in 2024, particularly in temporary clinician staffing. With the clinician shortage expected to continue – and possibly even worsen – in 2024, automation is key from the start of the clinician’s staffing journey (i.e. the job posting) to accepting an offer.

This means clinicians will experience faster processing times and facilities will get clinicians to the patient’s bedside faster. Along with automation, better algorithms will continue to enhance personalization, which leads to an all-around better clinician experience. And for healthcare facilities – many of which are struggling with operating costs – automation will further reduce these costs, allowing facilities to build better internal tools and automate even more.

Patty Riskind, CEO at Orbita
Clients tell us, emphatically, that they need tools to relieve the administrative workload burdening staff. Automation and digitization are key to addressing this critical need, particularly solutions combining conversational and generative AI.

Russell Teague, Vice President, Advisory Services at Fortified Health Security
My prediction for 2024 is that we will see significant growth in adoption of artificial intelligence across healthcare, from daily task automation like patient notes to interactions being captured through AI listening in and crafting notes real time, saving physicians and clinicians time while improving on accuracy and completeness. This process will add to the data volume that will be made available to large language AI models, possibly allowing predictive analytical models to improve on patient outcomes, diagnosis, and follow-up care.

It seems as though most healthcare providers and payors fall into one of three camps: those who are already responding to this disruptive technology and are in the early stages of investigating and developing AI Governance models; those who remain doubtful, choosing to take a restrictive approach and block organizational access; and those who are ignoring it and waiting to see what others do.

There’s still much to be learned about AI and healthcare automation, and how it’ll impact our lives and medical care, but it’s clearly here to stay. As such, now is the time to start seriously considering joining the camp that’s taking a proactive approach to governance and management. Embrace the value while protecting the data.

Patrick Higley, Vice President of Operational Transformation at AVIA
If 2023 was defined as the peak of the hype cycle, I expect 2024 to be where Generative AI demonstrates its first level impact to the provider industry. We expect a majority of health systems will be engaged with AI (NLP, Gen AI) use in clinical documentation and conversational AI either in pilot or some level of scale form. Further, we expect the majority of leading organizations to have deployed internally controlled versions of ChatGPT to support their internal knowledge management efforts.

Dr. Carl Marci, Chief Psychiatrist and Managing Director of Mental Health at OM1
The industry needs commitment, not hype related to AI in mental health: As we move into the new year, the industry will continue the hype-cycle around the myriad uses of AI in mental health. New data and tools will spark conversations and innovations, but companies will over promise and under deliver for the next 6-18 months. To move the needle on mental health care and treatment, the industry needs real and valuable applications – transitioning from the promise of the possible to the delivery of accessible, high-quality, and personalized treatment plans for each patient.

Actionable delivery will need to encompass understanding of patient populations based on high quality real-world data, industry partnerships for bedside decision support and taking the hype out of what artificial intelligence (AI) and technology tools can (and can’t) do – AKA, AI won’t replace doctors in 2024, but it can aid in earlier, more accurate diagnoses and treatment plans. Truly making a difference in mental health next year will require evolution and long-term commitment, otherwise, we’ll stay in the same hype-cycle and patients will continue to suffer from a lack of access to high quality mental health care.

Carolyn Ward, M.D. and Director of Clinical Strategy at Particle Health
I believe a huge place where generative AI will be able to gain traction in healthcare in 2024 is in developing operational workflows and clinical pathways for resource allocation to specific patient cohorts. Understanding who are the riskiest patients (who are the sickest in a population, who requires the most resources, and who is the most likely to develop a complication), and how much of that risk can be impacted is only as valuable as an organization’s ability to actually act on that risk and direct resources effectively.

Sanjeev Agrawal, President & COO at LeanTaaS
In 2024, the potential of generative AI could create new purpose – helping clinicians function at the top of their license. Imagine all of the mundane, manual, repetitive analytics and tasks currently performed by healthcare workers that can be transformed by tools like ChatGPT.

What does this look like in practice? Imagine that anytime and anywhere, on any device, at home or on the weekend, hospital leaders, clinicians, and staff can ask a generative AI-powered chat assistant the specific question they need answered, like “across all of my units, do I have enough staff scheduled to cover tomorrow’s 7am-7pm shift?” to proactively close staffing gaps and make strategic decisions to utilize the available workforce. The result: an answer that looks more similar to a result from Google, rather than another new dashboard.

It’s like your homework being done for you before you even asked for it to be done. The power to simplify and remove burden is massive. This will help with clinician burnout, improve patient access to care, and restore the joy of medicine to our workforce.

Melissa Easy, VP of Clinical Technologies at IQVIA Technologies
AI Enhancing Humans, Not Replacing:
As we move into 2024, the integration of AI in clinical operations is set to enhance, not replace, human roles. Contrary to ongoing discussions about AI displacing jobs, the use of AI tools marks a significant shift in the healthcare landscape. New AI tools, like generative AI, are poised to augment human capabilities, alleviating administrative burdens by automating routine tasks and enabling professionals to focus on more strategic aspects of their roles.

In the different phases of clinical trials, the advent of generative AI will empower research sites with tools to address anticipated study start-up challenges. This includes increased adherence to regulatory standards across countries, enhanced collaboration among multiple sites and optimized patient recruitment. For sponsors, on the other hand, this could mean being able to sort and select the right sites for the right study, ensuring they are following the correct protocols and, ultimately, successfully rolling out new trials.

The implementation of AI will lead to a more collaborative and efficient trial environment. Instead of taking over jobs, it will allow professionals to dedicate optimal time to patient-facing activities – and add in the context that only humans could provide.

Technology’s Role in Driving Clinical Trials Speed and Agility:
The heart of clinical trials lies in the ability to deliver results faster and more accurately. With more studies anticipated to be conducted in hybrid and remote environments, more challenges will arise, specifically distinct ones for patients, sites and sponsors.

As we start the new year, effectively recruiting patients and personably connecting with them will be a major undertaking. Sites and sponsors will also see increasing challenges in terms of improving their workflows, orchestrating interactions with patients or effectively gathering study data. AI will play a key role in analyzing the increasingly vast volume, velocity and variety of data generated to deliver deeper insights faster and automate actions for faster resolution to potential issues.

In this context, strategies and solutions that empower all stakeholders will be paramount. In fact, next year will highlight the need for further trial transparency and personalized experiences to optimize outcomes.

We will also see a transition to connected intelligence. Clinical trials will exponentially increase their adoption of AI and other newer technology trends searching for the best formula to enable better protocol design and site selection, patient accrual and enrollment, enhance operations and accuracy across clinical trials and keep studies on track.

The ultimate goal for trials is to enhance the quality and efficiency of the study, ensuring the successful delivery of life-saving therapeutics.

The Interoperability Year: More Technologies in the Marketplace Drive the Critical Need for Interoperability:
In the rapidly evolving landscape of clinical trials and the myriad of technologies going to market, the imperative for interoperability will become increasingly evident.

We have seen an influx of diverse technologies, which has led to siloed systems and inefficient processes, hindering the seamless collaboration essential for trial success. A glaring example underscores the urgency: a single site navigating a staggering 22 different systems daily. It is natural to see issues piling up – from gathering data from one system to another to simply logging in to all the different systems.

This segmentation compromises efficiency and jeopardizes the utilization of critical site data. As sponsors adopt new tools, they will increasingly seek strategies that enable a harmonized, interoperable ecosystem. 2024 is not only the year of the implementation of new technologies, but the year when the disparate tech stacks start to seamlessly communicate, ensuring streamlined processes, enhanced collaboration and ultimately, the delivery of impactful, patient-centric clinical trials.

Sameer Bhat, Cofounder and Vice President of Sales at eClinicalWorks
Even with strong early adoption, we’re just getting started with AI. AI has the power to relieve one of the top contributors to burnout: administrative work. We’re already seeing an increase in AI solutions: According to a 2023 Healthcare IT Leaders survey, more than one-third of organizations have at least partly implemented AI solutions, and another 25% have started AI pilots. But what most healthcare professionals don’t realize is that AI can do so much more than respond to patient messages.

AI can listen to patient visits and integrate accurate notes and next steps directly into the EHR. It can also automate the review of incoming faxes, identify gaps in care, streamline tasks with robotic process automation, and even alert providers of patients most likely to miss an appointment. I’m excited to see how it will transform clinical workflows and, in the end, create a better patient experience in 2024.

Branden Neish, Chief Product & Technology Officer at Weave Communications
AI Will Enhance, Not Replace Human Care: AI is quickly becoming table stakes in healthcare, with 67% of consumers expecting that AI will soon become commonly used. As AI becomes widely integrated into healthcare settings, it will enhance – not replace – human care. Generative AI tools can help clarify complex information, enhancing understanding for patients. For smaller, independently owned healthcare practices with limited staff, AI will not only enhance operational efficiency through services such as voicemail transcriptions, but also improve the patient experience through streamlined intake forms, communication, and automated responses from staff on routine inquiries such as scheduling or changing an appointment. In the year ahead, the versatility of generative AI in streamlining administrative tasks and enhancing patient communication positions it as a transformative force in healthcare operations. However, effective communication from healthcare providers will be pivotal in navigating this transition to foster understanding across all age groups and ensuring AI’s acceptance as a valuable asset in healthcare.

Shifting Patient Expectations Amid Economic Uncertainty: Patient expectations around the care they want to receive are shifting and healthcare providers must hone in on improving the patient experience in 2024. In our post-pandemic world, where nationwide economic uncertainty has increasingly resulted in Americans spending more than they earn, patients are asking for more from their providers, wanting to leave a healthcare visit feeling heard, understood, and unrushed. They want to feel that their visit is worth the high financial strain that seeking care may put them under, and providers must ensure they are delivering a top-tier patient experience or they run the risk of losing valued patients. Heading into the new year, providers will leverage three key strategies to improve patient experience: prioritizing the needs of loyal patients, investing in their practice and its convenience factors, and rebuilding the trust that has recently deteriorated between patient and provider. Overall, the long-term success of any healthcare practice in 2024 will be dependent on the individual experience they create for their patients.

Rethinking the Staffing Model to Better Address Shortages and Burnout: Staffing shortages, burnout, and strikes among healthcare workers will continue to make headlines in 2024. It’s not just clinicians who are feeling stressed, office staff are also overwhelmed with time-consuming admin work, leaving them resentful towards a job they once loved. These challenges are complex and there is no end-all-be-all solution for addressing the rising dissatisfaction we’ve seen to date among healthcare workers. Instead, practices must rethink how their operations can be changed and improved as a critical first step toward creating a healthy work environment, which ultimately results in the best possible care for their patients. Increased investment in new technologies meant to streamline administrative tasks and reduce the workload of healthcare office staff members will be one such strategy in the new year. For example, instead of answering phones all day and manually scheduling appointments, office managers and their teams can provide online scheduling tools and quickly text patients to connect, allowing them more time to focus on patients in the office. The result: happier, more efficient staff and satisfied patients.

Marie Flanagan, Director, Offering Management, Vigilance Detect at IQVIA
Next year we expect a continued trend of artificial intelligence (AI) supporting medical information and pharmacovigilance teams in automating the identification of safety risk in audio files. It is expected that audio will be a bigger consideration in society and medicine moving forward. With the emergence of Generative AI, this will also mean that the end-users of this software have the necessary guardrails in place to mitigate some of the known (and as yet, unknown) risks inherent with the adoption of this technology.

Also expect that cost containment will continue to be a pressing theme in the industry in the coming year. This applies to AI and large language model (LLM) investment as it is a hefty financial commitment and organizations are still determining the relevancy and opportunity this technology represents.

The biggest challenge at the moment for many is cost containment, and unfortunately GenAI will not displace the financial concerns in the industry. Instead of ‘going all-in’ investing in AI, we expect more organizations to be strategic in the way they carve out use cases in their operational workflows and find a middle ground that affords them clear efficiencies, optimizes their resources and improves insights in what will continue to be a highly regulated environment.

Proven technology that enables augmented users will serve as guardrails for GenAI, maintaining compliance and safeguarding patient safety. However, operationally, it needs to make sense for the challenges in your organizations and be cost effective.

There is also the potential for virtual AI agents to be used increasingly, as an accessible way for patients to report safety events, especially in layman’s terms. |To a certain degree the intelligence of AI agents can democratize safety reporting, though traditional channels will remain open.

Arun Nagdev, Senior Director of Clinical Education at Exo
In 2024, health systems will need to leave behind software built for processes to prioritize workflow solutions that are built around the user. With a keen understanding of what each individual caregiver needs to effectively capture, diagnose, and treat patients at the point of care, these tools will deliver monumental value for an industry that has been often referred to as a digital laggard. By investing in workflow solutions with a focus on user experience, health systems will see more success when implementing new technology and caregivers will experience less burnout.

The introduction of AI will create an entirely new education paradigm in healthcare, ensuring every individual has access to the skills development they need to perform at their highest capacity. A hands-on expert in the form of AI assistant technology will provide medical students with the proper skills to diagnose patients, allowing for real-time learning within the flow of work. AI will also be used in the classroom to build problem-solving skills, develop new curriculum, and improve the overall efficiency of learning.

The combination of AI coupled with medical imaging will unlock critical predictive analytics for health systems. Caregivers will be equipped with the ability to see deeper into the human body and make smarter decisions about their patients, ensuring the best possible care from anywhere. These predictive capabilities will be applied not only to elevate medical imaging acquisition and interpretation but also to alleviate the burdensome documentation that has historically led to significant levels of burnout amongst caregivers.

Navaneeth Nair, Chief Product Officer at Infinx Healthcare
In 2024, healthcare providers will significantly increase their adoption of cloud-based solutions, integrating AI and automation technologies with their EMR systems. This shift, driven by the scalability and accessibility of cloud computing, will streamline patient access and revenue cycle management workflows, allowing their staff to focus more on patient interactions.

AI’s role, particularly through more robust machine learning algorithms and natural language processing, will be critical to quickly and accurately analyzing data to accelerate authorization processes. This becomes increasingly important as the volume of cases requiring prior authorization expands due to more complex treatment protocols and evolving regulatory requirements.

In revenue cycle management, AI’s predictive analytics will play a crucial role. By forecasting reimbursements with greater certainty, identifying potential delays, and suggesting proactive measures, AI will enhance cash flow management and financial stability. This includes identifying trends and anomalies in billing, reducing errors, and preventing fraud.

Another advancement will be the integration of automation agents in revenue cycle workflows. These “digital workers,” capable of operating unattended, will revolutionize the way routine tasks like eligibility and benefit checks, prior authorization initiation/follow-up and claim payment follow-ups are handled, eliminating the need for human intervention in these areas.

In 2024, there will be the adoption of the “human-in-the-loop” or attended automation model. In this model, automation handles mundane, repetitive tasks, while human expertise is utilized for critical clinical decisions and data input. This synergy ensures not only efficiency and clinical accuracy but also compliance with healthcare regulations.

OpenAI’s GPT and other large language models (LLMs) have revolutionized unstructured clinical processing, and this will lead to “intelligent digital agents” that can reason on clinical documents like progress notes and charts to provide the right information to the payers. This will lead to multiple elimination of human tasks in multiple revenue cycle processes like prior authorizations and denials and appeals submissions.

The integration of AI, automation, and human collaboration will mark the emergence of a more efficient, patient-centric healthcare system. Enhanced interoperability between different systems and platforms will be crucial for this seamless integration, ultimately improving patient experience through more personalized care and faster service delivery.

2024 will witness healthcare administration being reshaped by a harmonious blend of technology and human touch, leading to more responsive and effective healthcare delivery.

Meghan Schaeffer, National Public Health Advisor & Epidemiologist at SAS
Forecasting and modeling are rapidly becoming the cornerstone of public health work, but government needs help. Enter academia. We will see an increase in academic researchers carrying out AI-driven modeling and forecasting on behalf of government.

Dinesh Kabaleeswaran, Senior Vice President, Consulting and Advisory Services at MMIT
Artificial intelligence (AI) is already being considered for a variety of purposes within healthcare and pharma, but in 2024, I predict we’ll see the applications of AI expand into stakeholder groups such as managed care organizations – payers and PBMs. The benefits that other industries have seen from AI have inspired and encouraged many payers to have conversations within their organizations on the applications of the tool. In fact, according to recent market research, 81% of payers consider themselves familiar with AI tools such as ChatGPT, and 64% are already having preliminary discussions about how it could impact their day-to-day activities. For payers and PBMs, AI tools can be useful for tasks including claims processing, prior authorization review, and data retrieval.

That being said, payers may still be slower to adopt the technology compared to other industries or areas within healthcare. Payers experience significant challenges with their current infrastructure and may hesitate to adopt new tools that could further complicate things. However, because the majority are already keen on developing their AI knowledge base and how it could reduce administrative burden, I hope and believe that 2024 will be the year when managed care begins to embrace the benefits of ChatGPT and other AI tools.

Sean Crandell, SVP of Healthcare Economics at MultiPlan
Machine learning and generative AI will change the course of healthcare costs by lending advanced analytics to the payer and provider space. This shift will help manage plan costs and identify potential emerging risks and high-risk patients, and ultimately help healthcare stakeholders and organizations to make data-driven decisions that result in better patient outcomes and a healthier community. Predictive and prescriptive analytics – known as advanced analytics – can revolutionize the consumer health experience and enable a proactive approach that focuses on prevention, early intervention, and the efficient allocation of resources to properly address the health needs of a population and continue the drive toward value-based care.

Identifying high-risk populations, tailoring care plans, offering predictive modeling, optimizing resource allocation, and enabling continuous improvement will be pivotal to payers in 2024. This dynamic process fueled by advanced analytics will allow for the continuous enhancement of care and the adaptation to changing healthcare needs, tailoring care plans to individual patients – a key aspect of value-based care that improves patient engagement, adherence to treatment regimens, and patient outcomes overall. When deployed more broadly, this technology will be instrumental in moving the needle toward proactively minimizing disparities and optimizing outcomes for all communities.

Joseph Mossel, Co-Founder and CEO at Ibex Medical Analytics
The escalating demand for pathology services, fueled by a surge in cancer cases and a global shortage of pathologists, is propelling laboratories toward adopting AI-driven solutions for improved accuracy and efficiency. Historically, labs resisted moving toward digital solutions which were limited in their workflows and decision support tools. However, a transformative shift is underway with new and comprehensive AI-powered pathology solutions.

To unlock the full potential in going digital and improve patient outcomes, there is a critical need for end-to-end AI-enabled workflows and integrated diagnostic pathways. With new AI technology, seamlessly integrated into existing multi-vendor end-to-end solutions, these AI-powered solutions are moving cancer diagnostics away from microscopes and propelling the industry into a new digital era that ensures all patients have access to accurate and timely cancer diagnostics.

 Venu Mallarapu, Vice President of Global Strategy & Operations at eClinical Solutions
Conversational & Predictive Analytics: As the advances of generative AI, like ChatGPT’s ability to handle audio and visual content, come to fruition, the ability to build platforms and systems with capability to deliver more accurate predictive and conversational analytics is increasing tremendously. I feel 2024 will be the year where conversational analytics for decision making will see mainstream adoption and predictive analytics for scientific and operational decision making will take off. Use of Generative AI and machine learning will be the key to success of both.

Cham Williams, Associate Director, Safety, Regulatory and Quality Solutions at IQVIA
In 2024, technology and automation will be a main focus for regulatory labeling. Organizations must maintain compliance, and the growing complexity of the regulatory field is pushing organizations to turn to more automated processes.

Automation in the form of generative artificial intelligence within labeling is highly anticipated, but it will take time to build confidence in the technology. It holds promise in terms of generating and translating content, but human review will remain necessary to validate the output. The coming year will see exploration of how to apply the technology, but we will not yet see a full integration of generative AI within labeling.

Beyond generative AI, various other forms of automation are poised to change the playing field. Processes at the forefront of fully incorporating automation include change management, content editing and artwork creation. We will also start to see the use of artificial intelligence to capture and identify regulations or competitor information with automated tools like natural language processing. As the use cases expand, 2024 will bring more widespread automation.

Structured content authoring, a versatile source format that is based on defined and enforced consistency in the organization of information in documents, will also be a priority for many organizations as multiple companies see that it is a viable solution for variation and deviation challenges. This will be top of mind as companies recognize the need to componentize or break up existing documents. The journey to structured content authoring requires an intense effort, and we will see many begin the process.

Anish Sebastian, Co-founder and CEO at Babyscripts
All About AI – It’s almost guaranteed that we will see more AI adoption in healthcare in 2024. While some optimists envision AI-powered predictive clinical models in the near future, it’s a more realistic bet that non-clinical applications, like documentation and education, will make the first inroads into a cautious sector.

Dr. Kate Sasser, Chief Scientific Officer at Tempus
AI will help usher in precision medicine across the broader healthcare system: In the pursuit of personalized medicine, we know that there are still many different gaps in deployment and implementation, and some of these will become easier to address with AI driven tools and technologies. Take something simple and agreed upon across clinical guidelines, like genomic testing for EGFR in NSCLC. We know that roughly half of patients get the necessary testing and recommended treatment, but as AI tools enter EMRs and are able to become ‘smart’ about the data they have access to, they will be able to flag patients that should receive guideline driven testing and treatment with the appropriate therapy. As more personalized regimens enter the clinic, AI tools will help physicians keep up with the plethora of testing to match patients to therapies, and to switch therapies when early signs of molecular response occur. AI will be in the background on top of all these diagnostics and data, helping them become more integrated and impactful.

Precision medicine will continue to evolve in 2024: In disease areas like oncology, we will start to see AI playing a larger role in target discovery and biomarker or patient subpopulation identification, the cornerstones to early precision drug development. We will see more personalized treatment regimens, including specific combinations that are based on multimodal tumor immune profiling.

It’s also exciting to see the evolution of precision medicine in other disease areas, which is long overdue. It took oncology over 20 years to just begin to realize impact from precision medicine, but it is now moving more quickly into areas like diabetes, immunology, and cardiology.

Robert Connely, Global Market Leader for Healthcare at Pega
As an election year nears, AI’s importance for healthcare payers is increasingly evident. The focus will be on using AI to streamline operations and align clinical and administrative data, especially in benefit processing. This alignment improves claims experiences and transparency, preparing for upcoming regulatory changes. With Medicare Advantage set to exceed a 50% share of Medicare coverage markets, generative AI will play a crucial role for payers. It will enhance member experiences in plan selection, provider choice, healthcare financing under new Part D Prescription Payment plans, and navigating the evolving healthcare landscape.

As healthcare organizations face staffing shortages, AI will equip workers with the necessary data and intelligence for better care. Imagine community health workers (CHWs) or family caregivers with AI co-pilots aiding in-home care. AI could guide them, suggest discussion topics, or provide insights needed by the medical team. It could remind patients about appointments, arrange transportation, and analyze voice markers to detect potential health issues like depression and anxiety, updating the medical team for follow-up actions. With AI copilots, CHWs can follow up with patients more accurately, identify potential issues, and ensure better health outcomes. By democratizing healthcare tools, AI will bridge the workforce gap and usher in a new era of efficiency and accessibility, shifting towards social and community-driven healthcare roles in the 21st century, ultimately delivering superior care for all.

Daniel Curling, CTO at Experian Health
In the near future, two key areas of investment are set to take center stage in the healthcare industry: security and operations, with a particular focus on Robotic Process Automation (RPA). RPA, which leverages software robots and artificial intelligence agents, is poised to revolutionize healthcare operations by emulating tasks traditionally carried out by human clerks. From an operational standpoint, RPA streamlines processes, freeing up valuable time and resources for healthcare professionals to concentrate on other critical tasks. This enhanced efficiency can have a cascading effect, leading to increased productivity and, ultimately, improved patient care.

Justin Norden, MD, Partner at GSR Ventures
Ambient documentation will be the most widely used generative AI application in 2024. Furthermore, the price of ambient documentation will drop by 3-5x from its current price point as the underlying technology has been commoditized.

Patty Hayward, General Manager of Healthcare and Life Sciences at Talkdesk
Provider organizations in 2024 will be motivated to leverage Artificial Intelligence (AI) and Generative AI to improve the customer experience for patients. But it is important that they approach Gen AI in a way that will scale in a responsible and compliant way. They need to establish guardrails to ensure their patient or member data does not wind up on systems or in training data where it shouldn’t be, and to ensure bots are accurate and unbiased.

Conversely, providers can’t wait for a “perfect moment” to start exploring Gen AI, or else they’ll fall behind their competitors, since optimization and iteration are so important to long-term success. They must explore non-clinical use cases as the technology matures, such as using Gen AI to help with patient scheduling and provide healthcare contact center workers with better tools to do their jobs.

Michael Gao, CEO and co-founder at SmarterDx
Soon, AI-driven automation of clinical documentation will be actively helping physicians capture their visit in real-time. Automated pre-bill reviews will then validate documentation, eliminating any remaining leaks. This 1-2 punch will improve financial capture while maintaining accuracy. Just as importantly, this robust documentation will enhance patient care coordination and safety, perfectly aligning financial and care delivery incentives.

Julie Stegman, Vice President, Health Learning & Practice at Wolters Kluwer Health
The AI has to be right: the role of AI in nursing education
In 2024, we will see students and professors continue to experiment with the use of AI in education. Both students and educators are looking for ways to improve the traditional workflows of the classroom. By leveraging AI, faculty can reduce some of the workload burden with development of lesson plans, and more efficiently testing student knowledge and adjusting learning accordingly. For students, the proper use of AI can give them access to trusted learning materials in an easier to find, and digestible, conversational format.

Education companies will act as fast movers since they are already dealing with time-pressed students – who are also savvy consumers – who expect to be engaged and leverage personalized study resources. For medical and nursing education, the AI has to be right – students must graduate clinically competent and confident, and they cannot learn from content that is not evidence-based, current and accurate. While there are many discussions and pilots happening currently, 2024 will be the year we see both of these groups push their institutions for real-life implementations.

Preeti Kaur, SVP of Engineering at Honor Technology
AI is where home care is headed in 2024
There have been more advancements in the healthcare space around senior health and technology, especially as 53% of U.S. adults age 55 and older leverage some type of assistive or health-related technology to age in place. In 2024, tech like AI, in tandem with the human touch and interaction from caregivers, will be used to augment care, create care plans and further deliver quality care. AI and other emerging tech will also be employed to help care for more vulnerable patients to detect falls and prevent future ones, to address the undercurrents of interactions like language barriers and to create better interactions with patients through greater personalization.

James Yersh, Chief Revenue Officer, Senior Care at PointClickCare
AI-Driven Predictive Analytics: A Game-Changer for Resource Allocation: While there are of course many downsides to inflation, the good news is that CMS has increased skilled nursing facilities (SNF) payment rates to 4% for 2024. This is a clear sign that healthcare providers across the continuum are struggling to maintain operational margins. Confronted with budget constraints and persistent staffing challenges limiting their ability to increase census, providers will increasingly embrace technology to enhance operational efficiencies.

In the coming year, I expect a significant increase in the integration of cutting-edge technologies, including AI and predictive analytics to arm care teams with the insights they need to predict trends in the health of patient populations, possible disease outbreaks, and individual patient risk factors. Looking ahead, senior care providers will continue to embrace the opportunity to proactively allocate resources, such as personnel, equipment, and medications, where they are most needed, to help in increasing top line revenue, to improve efficiency, patient outcomes, all while reducing costs. I hope that in 2024, we continue to move towards an era in healthcare that places emphasis on both financial accountability and the well-being of patients.

Be sure to check out all of Healthcare IT Today’s Uses of AI in Healthcare content and all of our other 2024 healthcare IT predictions.