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The ROI of Artificial Intelligence in voice-based patient follow-up

Despite the availability of text-based solutions like SMS, apps, and patient portals, these options often yield poor engagement and retention metrics, catering mainly to tech-savvy patients.

Despite the availability of text-based solutions like SMS, apps, and patient portals, these options often yield poor engagement and retention metrics, catering mainly to tech-savvy patients.

Healthcare professionals, particularly nurses, dedicate a significant amount of time to patient follow-up via telephone. Despite the availability of text-based solutions like SMS, apps and patient portals, these options often yield poor engagement and retention metrics, catering mainly to tech-savvy patients. For the majority, phone calls remain the most effective method of communication. However, human-based follow-ups come with inherent inefficiencies. This is where Tucuvi Health Manager (THM) and its voice-based virtual clinical assistant, LOLA, offer a valuable solution. By providing follow-up through simple phone calls, THM ensures that every patient receives comprehensive care when they need it.

Examining the Return On Investment (ROI) of utilizing Tucuvi Health Manager and its voice-based conversational Artificial Intelligence (AI) assistant LOLA for patient follow-up reveals the following benefits:

1. Cost savings

  • Reduced Labor Costs: THM automates the follow-up process, eliminating the need for healthcare professionals (HCPs) to make individual phone calls. This results in substantial savings in terms of labor expenses.
  • Increased Efficiency: THM can handle multiple calls simultaneously, expanding the reach to more patients in less time. In contrast, HCPs can only make one call at a time, limiting their productivity. By optimizing efficiency, THM reduces the time spent on each follow-up, leading to further cost savings.
  • Decreased Readmissions and Complications: Regular follow-ups through THM help identify potential issues early on, preventing hospital readmissions and complications. This proactive approach significantly reduces healthcare costs associated with avoidable readmissions or emergency room visits.

2. Time efficiency

  • Automated Follow-up Process: LOLA initiates and completes follow-up calls autonomously, freeing up HCPs to focus on other critical tasks that require their expertise. This automation streamlines the process and eliminates time-consuming manual dialing and note-taking.
  • Rapid Outreach: LOLA reaches patients in a more timely manner compared to HCPs, who may face constraints due to workload or availability. Prompt follow-ups contribute to improved patient engagement, adherence to treatment plans, and timely detection of potential issues.
  • Consolidated Documentation: Conversational AI enables THM to document patient responses and update electronic health records automatically. This eliminates the need for HCPs to spend additional time on paperwork, ensuring accurate and up-to-date information is readily available for healthcare providers.

3. Scalability

  • Extended Reach: LOLA efficiently reaches a larger patient population compared to HCPs. With the ability to make hundreds of simultaneous calls, THM ensures follow-up care is provided to a broader demographic without increasing the workload for HCPs.
  • Language and Cultural Adaptability: Conversational AI technology allows THM to communicate with patients in multiple languages and adapt to cultural nuances. This enhances accessibility, ensuring patients receive follow-up care tailored to their specific needs and comfort.

4. Data collection

  • Comprehensive Data Collection: THM consistently and systematically collects patient responses, symptoms, and other relevant information. This data provides a comprehensive overview of patients' health statuses, enabling healthcare providers to identify patterns or trends that may require intervention.
  • Data-Driven Insights: THM analyzes the collected data, providing healthcare providers with actionable insights. These insights inform personalized care plans, identify potential risks, and improve treatment strategies. In contrast, manual calling lacks the structured data collection and analysis capabilities offered by THM.
  • Continuous Improvement: THM continuously learns and adapts based on the collected data and patient feedback. This iterative process facilitates ongoing improvement in patient interactions, ensuring follow-up conversations become more effective and patient-centric over time.

If these reasons weren’t compelling enough to convince your management team to invest in voice-based conversational AI for patient follow-ups, maybe this will be: introducing Tucuvi Health Manager’s ROI calculator. By inputting the number of patients to follow-up, the number of calls per patient per year, and the average call duration, the calculator returns the amount of HCP hours and their equivalent in euros that your organization could be saving by using Tucuvi Health Manager.

Tucuvi Health Manager’s ROI calculator

Investing in voice-based conversational AI for patient follow-ups not only improves efficiency and reduces costs but also enhances patient care and satisfaction. Incorporating Tucuvi Health Manager and LOLA into healthcare practices leads to better outcomes and a more streamlined healthcare system.

Discover how top organizations have successfully implemented Tucuvi here.

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