A reliable, robust, and secure automation platform that works intelligently is crucial for any healthcare institution transforming itself to be future-ready. As Conversational Artificial Intelligence (AI) and other intelligent automation systems become more prevalent in use, so does the possibility of becoming vendor-reliant increase too. However, a one-size-fits-all philosophy can be risky. This is where an intelligent and automated vendor-neutral platform begins to shine.
A platform that supports the healthcare institution’s entire communications and automation network is an incredible value proposition. Be it Conversational AI or RPA solutions, KeyReply’s platform can act as the orchestrator between them. Here are two case studies of how KeyReply’s AI platform has made healthcare professionals’ jobs easier.
Case Study 1
The Challenge
To be amongst the leading healthcare providers in a particular region requires adapting to patients’ demands and navigating the challenging landscape of the pandemic. With a constant change in medical services, protocols, and business needs, it is also vital to streamline communications to ensure a high level of service and consistency.
The Solution Provided by KeyReply: Patient Engagement Platform
To address this solution, a brand teamed up with KeyReply to develop a platform that can answer patient-related queries such as booking appointments. In addition, KeyReply’s patient engagement platform provided the company with live chat services across multiple communication platforms.
KeyReply’s AI platform helped the brands to address general patient inquiries related to contact hours, room rates, services, admissions, etc. In addition, this platform directed patients to the correct forms for booking appointments for specialist visits and healthcare screenings.
Case Study 2
The Challenge
A leader in public healthcare that serves millions of residents wanted to improve its Key Performance Indicator and increase patient satisfaction ratings. The healthcare institution required a platform that can allow them to:
- Bring all systems together in the long run as an orchestrator. This would help healthcare institutions connect with patients, data, systems, and workflows to improve outcomes and facilitate coordinated care.
- Grow with the business’s evolving needs. Intelligent automation can see trends in data and predict patients’ needs. This way, it can grow with the business without requiring replacement over many years.
- Provide enterprise-level security, governance, and flexibility in deployment options to suit potentially sensitive use cases.
AI can analyze the relationship between suspicious
IP addresses or malicious files in a matter of a few
seconds or minutes.
- Be Omni channel ready and multi-lingual ready for the culturally diverse population. This can provide a pathway for the patients to have more control over their health outcomes and openly communicate with the clinicians through their preferred channels.
- Allow effective self-administration. A no-code or code-free platform can enable AI-inexperienced personnel to test and implement ideas without requiring AI experts.
The Solution Provided by KeyReply: Center of Excellence and Patient Engagement Platform
Instead of building numerous standalone intelligent automation platforms, KeyReply built a centralized knowledge base structured across different types of healthcare institutions. This helped the healthcare institution access information in a more manageable than earlier. Our patient engagement platform also helped a few teams enable live chat for support services. As a result, since April 2021, the Virtual Customer Associate Assistant has handled countless general inquiries, ranging from types of clinical services to the payment of medical bills.
The platform provided by KeyReply was easy to use, scalable, and highly versatile. Additionally, KeyReply’s team shared valuable tools and best practices to train the contact center team of the healthcare institution. This helped the team handle the platform independently without needing a data scientist. As an added advantage, this practice also helped to reduce resource costs. It also empowered healthcare institutions with control over the system to make continuous improvements to meet our users’ needs and expectations.
