Artificial Intelligence in Telehealth - Alliance Voice Solutions

Medical technology concept. Electronic medical record. Telemedicine.

With the advancement of technology, artificial intelligence (AI) is no longer a science-fiction fantasy in today’s world. It has become a key component of numerous workflows and systems.

Many telehealth companies owe their success to AI today as the introduction of AI-driven telehealth has adeptly streamlined the accessibility of healthcare services to patients.
Developments in Telehealth with AI

Incorporating AI within telehealth platforms has the potential to streamline services and expand healthcare capabilities. In utilizing AI, efficiency is maximized in that machines can gather and fill in the information required to obtain a health history, while health professionals focus on patient concerns they are uniquely qualified to address.

The telehealth and Al alliance has led to the following developments and associated advantages:
Better Diagnoses

Hospitals have a large collection of medical scans received remotely that need to be categorized, collected, and stored efficiently. This collection helps in training AI systems not only to collect and categorize the scans but also analyze the images to identify a myriad of diseases.

AI has had a global impact in enabling providers to diagnose ailments using machines. Remote monitoring is conducted in tandem with machine learning which helps healthcare providers arrive at appropriate diagnoses with less direct provider effort.

An algorithm can track the treatments for particular diseases, and gather specific information related to recovery from patients affected. This helps glean insight into future treatments of these diseases. Machine-learning algorithms can also help remotely diagnose diabetic retinopathy using retinal images, which are received and analyzed via telehealth systems. Moreover, FDNA, a digital health company, is a startup that trains a machine-learning algorithm to detect and diagnose rare genetic diseases using photos of patients’ faces. A computer algorithm using convolutional neural networks has also helped in diagnosing melanoma.

Many diseases share similar symptoms which can make differential diagnosis via virtual means challenging. Such cases may call for a face-to-face examination. AI assists the providers in such conditions and helps deliver accurate information related to diagnosis and prognosis to patients virtually.
Adherence to medications

Information and communication technology can promote increased patient adherence to recommended treatment regimens. It helps in implementing closed-loop healthcare paradigms and establishes collaborative care networks that involve all stakeholders necessary to optimize treatment outcomes. It often uses speakers or home-based assistants to remind the patients about their medication. Additionally, some providers ask telehealth patients to log their daily medication doses using AI programs, which can provide a means of ongoing progress-monitoring for providers.
Resolving Logistical Challenges

In the case of telehealth, AI not only refers a patient to a physician, but also provides patients access to specialty care providers equipped with the necessary expertise to address a patient’s reported concerns. It can also assist in identifying complex constraints and engaging in proceedings to reduce hospital wait times.

It helps in circumstances when the demand for healthcare providers exceeds supply. AI manages to address this issue by developing algorithms that detect the availability of healthcare providers in the near vicinity. It also helps solve issues related to telecommunication link failure or the remote unavailability of a specific provider.
Elderly Care

Eldercare assistive robots have been developed as telehealth care providers, which are smart machines that help elderly patients with their daily tasks in a cost-effective manner. They move semi-autonomously, perform their chores, and use sensors to detect their surroundings.
Chatbot and Robotic Process Automation (RPA)

AI Chatbots have been introduced on telehealth websites to help register and connect patients with a physician. These chatbots have the capacity to help the patients recover their usernames and passwords if forgotten. They also assist patients in analyzing insurance options and suggesting the one most suitable to their needs and coverage.

Robotic Process Automation (RPA) is a model that helps healthcare organizations focus on their patients, ensuring an intense healthcare ecosystem with the best possible care options.
Connecting Patients

AI is being trained to advise patients seeking telehealth services about optimal healthcare plans according to cost and other features, thus enabling patients to maintain a perfect balance between care and cost.
Preventing burnout

The use of AI applications in telehealth may lower the likelihood of provider burnout in reducing overall workload demands. Further, the use of AI systems can save providers time that they can direct to other essential duties, such as clinical documentation.