Recommendations for the correct implementation of an AI-based conversational solution in healthcare centres, for both staff and patients.

For both the staff and the patients to experience all of the benefits of an AI-based conversational solution in healthcare, health centers need to ensure a safe and correct implementation. Recommendations for the correct implementation of an AI-based conversational solution are many and proper implementation for an AI such as Patricia includes careful planning, integration, and execution of the natural language processing model into the world of healthcare. Here are some of the major recommendations to take into consideration when implementing an AI solution in healthcare centers.

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Best practices for correct AI implementation – Identifying the main problems in healthcare where AI can help

To begin with, implementation should first start with understanding the problem. If we understand the problem, we can do a much better job integrating and implementing solutions. In the modern world of healthcare, digitalization is far from something new. The majority of clinics around the world are slowly transitioning to more digital means of communicating with patients. With the constant expansion and evolution of machine learning and natural language processing, AI has become more than just a helpful tool. Fully functioning conversational models acting as virtual health assistants are now a reality. Therefore, it is safe to say that there is a clear path ready for further integration of AI.

When it comes to identifying the main problems in the world of healthcare today, we can simply take a look at what happened during the global pandemic. The need for a more responsive and faster communication solution, especially for those living in remote areas and those suffering from chronic diseases is necessary. So, as long waiting lists, slower communication, and overly complicated call center menus are some of the globally shared problems in health centers, we can take the need for faster and more responsive communication as one of the places where an AI-based conversational solution would be most needed and valued. This includes initial communication between a patient and a health center, the process of scheduling and rescheduling appointments, follow-ups, and patient education

Engaging both healthcare staff, patients and stakeholders

Stakeholders and medical staff need to be properly and timely shown what AI-based conversational solutions in healthcare centers can be used for and then together they can examine the main recommendations for the correct implementation of such AI. Both the stakeholders and the medical staff should be familiarized with the development process and where the most progress can be made as well as which areas need further improvement. Patients’ opinions should also be evaluated, analyzed, and observed for any potential improvements or changes that need to be made to the AI model and how it communicates.

Using the most innovative and proven AI solutions

While there are numerous AI solutions available, the combination of machine learning and natural language processing for an AI-based conversation solution has a proven record of successful practice in the world of healthcare. This kind of AI needs to be adaptable, and customizable, and it needs to comply with the standards and requirements of each health center and patients’ needs. Comprehensive training for staff members who will interact with the AI system is also necessary for proper implementation. This will help the medical staff understand AI’s capabilities but also its limits.

Testing and monitoring with a team of highly trained experts

Once a natural language processing AI has been developed for the purposes of providing new and innovative conversational solutions in healthcare, it needs to be properly and thoroughly tried and tested. Simulations, data gathering, and data processing are some of the things that AI does best, and with a team of highly-trained experts who are behind it, constant tests would facilitate the best possible development route. By providing constant testing and support, AI can be developed constantly and inconsistencies isolated and removed before its implementation in the healthcare system.

Tackling Data quality and security concerns

When talking about any kind of AI use in healthcare, one concern that often comes up is security and data quality. AI has an immense power to gather data but it also relies on data to properly function and learn. This data needs to be protected at all times and processes such as data encryption, restricted access, and cleaning and pre-processing the data to remove any unwanted issues are needed in order to protect the data and ensure its quality. Ensuring that patient privacy is protected at all times is one of the top priorities.

Recommendations for the correct implementation of an AI-based conversational solution – Main takeaways

To sum up, AI solutions based on conversation models are becoming more popular in the world of healthcare. With technologies such as natural language processing and machine learning, AI has reached a point where it can function as a fully operational virtual healthcare assistant. However, before AI can assume this role, proper integration is needed. Therefore, for both staff and patients, health centers need to ensure that this kind of AI follows all of the safety and security protocols, uses the right technology that can be trained, monitored, improved, and customized, ensures the safety and protection of the data, and engages stakeholders, medical staff, and patients to better educate and inform them on what a conversation AI model brings to the world of healthcare.