How is Artificial Intelligence Impacting Telehealth?
With the rising popularity of telehealth technology, the healthcare industry is looking for ways to improve telehealth service delivery. By integrating Artificial Intelligence (AI) with telehealth software, healthcare providers can streamline administrative tasks, identify future research directions, and improve patient outcomes.
While AI is shifting the way the healthcare sector operates, it’s important to look at how it’s actively being used and the limitations that have been discovered. Here are just a few of the ways the healthcare system is utilizing AI technology:
Health Information Technology
Health Information Technology (HIT) allows systems to store and manage data, including Electronic Health Record (EHR) and Electronic Medical Records (EMR) solutions. Implementing this technology will typically require the use of AI algorithms to retrieve the medical data that provides healthcare professionals with information on conditions and treatment plans.
Remote Patient Monitoring
Remote patient monitoring is a telehealth tool that uses wearable sensors to monitor a patient’s health conditions outside of a medical office. These sensors can track activity levels, sleep patterns, and vital signs. Remote monitoring devices can use artificial intelligence and machine learning to manage chronic conditions and promptly alert health professionals when there is a sudden change.
Diagnosis Support
Since AI can process a large amount of data at a quick rate, it can be used to improve diagnostic accuracy and speed. AI algorithms can process medical images to recognize patterns the human eye could miss. With the support of AI technology, medical professionals can give a more accurate diagnosis, improving patient health outcomes.
The Benefits of AI in Telehealth
The potential impact AI could have on the healthcare industry is expansive, and it’s clear why when looking at just a few of the benefits.
Performing Time-Saving Tasks
When medical professionals are no longer performing simple but time-consuming administrative work, they can prioritize time spent with the patient diagnosing conditions and outlining treatment plans. With the help of AI and natural language processing algorithms, these processes can become automated, lessening the strain of administrative work on the medical staff.
Expanding Access to Healthcare
Patients who experience access barriers to healthcare, including rural communities and those without means of transportation, can receive medical care through a virtual care platform. Telemedicine platforms that remotely deliver healthcare services to patients utilize AI to provide virtual appointments, prescription management, and mental health services.
Reducing Strain on Medical Professionals
Medical professionals experience large workloads in a high-paced environment. With the help of AI, minor tasks can be automated, and diagnosis research can be performed efficiently. With time-saving support and research aids, medical professionals can operate with a less stressful workload.
The Most Common Pitfalls of AI in Telehealth
While we can see AI’s potential in healthcare and the benefits both patients and providers can experience, it’s important to consider the pitfalls and challenges that come with it.
Potential for Inaccuracies
For AI to be successful in a healthcare setting, it relies on the available data from historical cases and diagnoses. When the system attempts to perform patient data analysis to diagnose a condition lacking in historical data, there’s an increased likelihood of a misdiagnosis. Not being able to analyze patient data related to the current case can be a critical error, as it impacts treatment plans and medications.
Overlooking Social Variables
Treatment plans are built around a patient’s unique needs and available resources. While AI systems can build a treatment plan based on the diagnosed conditions, they may not consider the social or economic factors that impact these decisions. As the patient’s care depends on more than the textbook treatment plan, the use of AI could be limited in this case.
Security Risks
Security is a concern with any software, but especially in the healthcare system, where organizations must follow HIPAA compliance regulations to protect patient health data. AI is typically dependent on data networks, exposing AI systems to security risks. Since healthcare organizations process a large amount of sensitive data, they are at a higher risk of becoming a cyberattack target.
What the Future of AI in Telemedicine Looks Like
AI systems have the potential to revolutionize the way the healthcare industry operates, but there are obvious pitfalls that must be examined before integration with telemedicine software. These challenges may be resolved as AI technology advances, and AI can be applied in more innovative processes for delivering healthcare.
Reach out to Geneca today if you’re ready to explore ways your healthcare organization and telehealth platform can benefit from AI.