Vivek Mittal, CTO, Yugasa Software Labs talks about the features and barriers related to AI-driven virtual assistants in healthcare
The future of technology is always fascinating, and one area that has undergone substantial development and expansion in the past few years is the area of conversational AI assistants. These assistants have become more prevalent and are used in various applications, especially in the healthcare sector. However, they also come with particular obstacles which have to be addressed. Let’s examine the features and barriers related to AI-driven virtual assistants in healthcare.
Features of AI-driven virtual assistants in healthcare
24/7 availability: Healthcare chatbots can offer round-the-clock availability to patients, allowing them to access knowledge and assistance anytime. This can be especially helpful for tackling non-emergency medical queries, setting up appointments, and offering basic health advice.
Personalised care: Chatbots can leverage machine learning and artificial intelligence algorithms to evaluate patient information, his medical records, and understand the problem symptoms to suggest the relevant medical practitioner who would be the correct person to treat the patient’s that Bots can adapt to a person’s needs, preferences, and medical histories, offering customised healthcare guidance.
Medication reminders: Virtual assistants can assist patients in handling their medications by sending reminders for dosage schedules and refills. This feature can improve medication adherence while decreasing the risk of missed doses or medication adherence while decreasing the risk of missed doses or medication mistakes.
Health tracking and data analysis: Chatbots can integrate with wearable devices and other wellness-tracking tools to track patients’ vital signs, physical activity, and sleep By assessing this data, they can deliver insights into health trends and provide suggestions to keep a healthy lifestyle.
The future of medical care chatbots is brimming with promise, driven by developments in modern technology. Virtual assistants will be essential in providing tailored and efficient healthcare support. With machine learning and natural language processing improvements, virtual assistants will become even more advanced and capable of comprehending and responding to human commands.
Challenges in AI-driven virtual assistants in healthcare
Data privacy and security: Healthcare chatbots deal with sensitive patient information, making data security and confidentiality an important issue. Ensuring robust encryption, compliance with data protection rules, and secure preservation of patient data is crucial to sustaining trust and maintaining patient privacy.
Liability and accountability: If a healthcare chatbot offers incorrect data or makes an incorrect diagnosis, a problem of liability arises. Determining accountability when errors occur can be complicated.
Language barriers: While the competent chatbots have capabilities to talk in multiple global languages, use of mix languages, for example Hindi + English or typing Hindi in English script can confuse chatbots and hence a non performing or an inaccurate communication may take place between patients and the chatbot.
Integration with existing systems: Healthcare industry has plethora of IT software and hardware solutions under use for different purposes, to manage different departments and through various vendors globally. Seamless integration of chatbots with multiple such IT softwares and hardware (IoT) can be time consuming and difficult. Compatibility issues and data-sharing procedures are not yet well standardised in healthcare causing challenges in enabling effective collaboration between AI assistants and healthcare providers.
Human-machine collaboration: While chatbots can streamline routine tasks and offer preliminary support, they should not replace human medical Balancing the roles of AI chatbots and human medical personnel.
Balancing the roles of AI chatbots and human medical professionals while developing effective human-machine collaboration models is essential for optimal healthcare outcomes.
Conclusion
As we look to the future, Conversational AI Assistants will play an important part in our technology use. However, we have to tackle the difficulties related to data privacy and ethical considerations to ensure an ethical and secure implementation.