Telehealth and Artificial Intelligence Toolkit
Seizing Opportunities and Meeting Challenges
This toolkit is intended to give a broad overview of Artificial Intelligence (AI) and Telehealth for both patients and providers. Feel free to contact us at [email protected] with any questions about this toolkit or with any additional questions about RPM.
Artificial Intelligence Basics
What is Artificial Intelligence?
There are few things that have managed to fascinate those in the technology space as much as artificial intelligence. But what exactly is this new technology? Artificial Intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems.
AI works by collecting and processing data, selecting and training algorithms, creating models, and continuously learning and improving. AI systems use algorithms and vast amounts of data to identify patterns, make decisions, and solve problems. These systems can range from simple rule-based systems to complex neural networks capable of deep learning. The goal is to enable machines to perform tasks that typically require human intelligence.
This toolkit aims to provide a foundational understanding of AI's role in telehealth, highlighting its potential benefits, challenges, and the ethical considerations that accompany its use.
The History of AI and Healthcare
The integration of AI in healthcare has a rich history that spans several decades. The journey began in the 1950s with early attempts to create intelligent machines and has evolved significantly with advances in computing power and data availability. Key milestones include:
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Opportunities and Challenges of Artificial Intelligence
Telehealth Applications of AI
AI is has the potential to positively impact telehealth by enhancing various aspects of patient care and healthcare delivery if used in a practical way.
Remote Patient Monitoring and Data Analysis
The growing prevalence of RPM devices utilized to collect patient data has been hugely beneficial when it comes to monitoring patient health, but in some cases the sheer amount of data has led to data bloat. In some cases, providers are unable to parse through the massive amount of data that has been collected and come to conclusions about care decisions. AI excels when it comes to analyzing data, and identifying trends and anomalies. Using AI tools to comb through RPM data and cut down on amount of time providers must spend checking data before coming to conclusions about what care decisions to make for patient health.
Virtual Health Assistants and Administrative Efficiency
Provider shortages have been an ever-increasing problem in the healthcare space, with this problem exacerbated in rural and other historically underserved areas. At the same time, the wide-spread use of EMRs and patient portals has necessitated additional time spent per patient for providers and office staff. One promising potential use of AI is the ability to offload some time-consuming administrative functions. Chatbots and virtual assistants have the ability to assist patients with appointment scheduling and basic symptom checking. Automation of administrative tasks, such as billing and scheduling, can also improve efficiency and reduce potential user errors. By offloading non-critical processes, providers have more time to do what they do best - provide excellent patient care.
Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697552/
It should be noted that these applications are currently still being developed in many cases - actual use cases may vary significantly. Regardless, speculation on how AI can best be used in the healthcare and telehealth spaces will likely continue as AI technologies are further developed and refined
Understand the Limits
While AI is still a developing technology, there a large amount of enthusiasm for its potential – and not without reason. There are many aspects of telehealth practice that do have the potential to be positively impacted by the utilization of AI. However, understanding its limits is crucial when considering how we can fully harness its benefits as well as realistically manage our expectations.
Data Quality and Availability
AI systems require large amounts of high-quality data, which may not always be available or accurately represent diverse populations. Additionally, conditions that are less common or do not have data available for analysis are not able to be examined with AI models. Data is also susceptible to bias. Datasets that contain only information from a certain subset of the general population will not accurately reflect reality. There is a tendency to inadvertently exclude historically disenfranchised populations from collected data, leading to recreations of regrettable divides that already exist in healthcare.
Regulatory and Legal Challenges
The use of AI in healthcare must comply with strict regulatory standards, and liability issues can arise if AI-based decisions lead to adverse outcomes. Because AI is an emerging technology, industry standards and government regulations related to the field are still being developed. Until there are concrete rules and regulations in place around the use of AI in healthcare, there will likely be lingering uncertainties around how best to use it.
Looking Forward with AI and Telehealth
Ethical Considerations
AI has the potential to be a useful tool in the digital health landscape. However, the use of AI in healthcare raises several ethical issues that need careful consideration.
Health Equity
As discussed in the previous section, it is important to acknowledge that data can contain biases and miss crucial aspects the healthcare landscape. Certain people that are often overlooked – namely minority populations – are oftentimes not accurately reflected in the data that is utilized when training AI algorithms. Because of this, AI models can overlook health disparities that exist and recreate the disenfranchisement that has long existed in certain populations.
While there are currently no AI tools solely being used to make critical healthcare decisions, it is vitally important to understand that integration in those sorts of decisions is the current end goal for many AI projects. If the data used does not accurately reflect the population being served, results will only move us further away from health equity.
Preparing for the Future
It will likely be years before the potential of AI is fully realized. Much of what is being discussed around AI use in the telehealth space is still very much theoretical – its actual use may look very different than what is currently being proposed. Regardless, there are ways that patients and providers can both prepare for AI to play a larger role in patient treatment and care.
Education and Training
As AI tools develop and become integrated into our existing healthcare systems, providers will need to ensure that they are properly trained. It is vital that the use of AI is understood – from what it can do to where its limits fall.
Public Communication
When using AI, it is important that the public be made aware of it. It is never appropriate to utilize AI tools without informing a patient of their use.
More Information about Artificial Intelligence
AI Podcasts
Check out a few of our podcast episodes about AI and its telehealth applications.
The Future of Telehealth and Healthcare with Arthur Cooksey
Danielle talks with Arthur Cooksey, the Founder and CEO of Let's Talk Interactive, Inc. about how emerging technologies and increased connectivity will impact the future of telehealth and healthcare.
Artificial Intelligence with Jessica Devine
This week, Cam talks with Jessica Devine from the UMTRC and the Indiana Rural Health Association. Applications of Artificial Intelligence, misconceptions, the need for diversity, and how to get started in AI are discussed in detail.
More Questions? Contact us at [email protected]
This toolkit is intended to be informational, not to guide care or coverage decisions. For specific questions, we recommend you contact your physician or insurance provider.
Last Updated Sept 4, 2024