From reactive to proactive and predictive care
The US healthcare industry is transitioning from volume to value-based care. This makes proactive patient engagement a key business goal for providers. Digitally empowered consumers today seek on-demand access to personal health data for preventive care and prompt responses to their queries. This makes it imperative for hospitals, clinics, physicians, and other caregivers to reimagine their customer service function, and provision intuitive touch points for effective patient interaction.
TCS’ Cognitive Assistant is an application based on machine learning, pattern recognition, and natural language processing technologies. The application aims to help providers proactively engage with patients. It offers automated and relevant recommendations to patients, enabling them to take timely and informed decisions regarding physicians, care plans, and appointments. The application generates data-driven insights on individual patient conditions. It also facilitates effective preventive care for robust wellness management.
Personalizing customer care – At scale
Despite the growing emphasis on proactive patient engagement across the care ecosystem, several core business processes and related IT systems at the providers’ end are ‘reactive’. The configuration principle that supports these workflows focus on episodic care, instead of preventive treatment. As a result, providers are unable to effectively interact with patients and provide adequate, actionable information on the latter’s health conditions and diagnoses. The high wait times at call centers reflect this acute pain point for consumers. Caregivers need to automate their business processes—relating to appointment scheduling, remote patient monitoring, and payment processing—to improve customer service.
TCS’ Cognitive Assistant application is built around cognitive technologies. It empowers providers to deliver personalized customer care, at scale. It uses pattern recognition, natural language processing algorithms, and analytics, to derive actionable insights from patients’ historical data and current medical conditions and provides customized recommendations.
The self-learning virtual assistant enhances the efficacy of caregivers’ patient engagement platforms through automated voice interactions. It serves as the primary touchpoint for patient assistance for several activities. These include booking physician appointments, finding the nearest provider, optimizing benefit plan selection, and tracking claims reimbursement. The application also triggers SMS, e-mail, and mobile app notifications and reminders to patients, for effective remote care.
TCS’ Cognitive Assistant application facilitates effective preventive care and improves patient outcomes.
The benefits offered by the application to healthcare providers are:
- Proactive engagement: Improve care outcomes by monitoring patients’ health parameters, digitizing health records, and driving actionable patient-centered response. Providers can also increase patients’ awareness about various conditions by disseminating targeted educational content.
- Increased customer satisfaction: Deliver proactive care, based on accurate data. This enables patients to manage their conditions better, harness relevant data from diverse sources to make quick and informed health-related decisions, reduce delays in responding to queries, thus improving customer satisfaction, and strengthening brand loyalty.
- Higher operational efficiency: Reduce the volume of customer center queries by automating the underlying workflow. The self-learning cognitive assistant can address most of the health-related queries and events with the help of an updated centralized database. This saves costs as it eliminates the need for a complex physical infrastructure.
The TCS advantage
Partner with TCS to avail unique advantages
Analytics engine: Built around a data analytics engine, the application predicts patient outcomes based on their health data and patterns. It also notifies patients to take appropriate action in time. These could include recommendations to visit a doctor or schedule a screening check-up.
Consumer-focused approach: The application ensures continual improvement in service quality. It uses machine learning algorithms to capture data and change the models accordingly.
Easily customizable: The application is highly customizable. Providers can configure branding and the app theme as per their business objectives and use-case scenarios.
Product and platform-agnostic: The application ensures integration across multiple care providers, mobile apps, and data elements.
Innovation focus: By investing in innovative technologies, we provide superior solutions to clients. Our holistic connected health and wellness solutions are built on our intellectual property (IP) and combine the power of digital technologies—mobility and pervasive computing, cloud computing, social media, big data and analytics, artificial intelligence, and robotics.