Client

Tucuvi

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  • Client

Voice and Artificial Intelligence (AI) to monitor patients at home.

From pre-consultation to disease monitoring, Spanish organization Tucuvi automates outpatient communications to save time and provide data to healthcare teams. To do this, they use advanced AI with a low-tech user experience via phone calls. To facilitate data transmission, the CE-marked software integrates with a care organization’s Electronic Health Record (EHR) and the patients’ telemedicine platform, so healthcare professionals receive structured and prioritized data on their patient’s condition daily, enabling them to make smarter and faster decisions. By automating medical phone calls, Tucuvi addresses the main pressing challenges of today’s healthcare industry. First, the urgent and growing demand for healthcare due to aging and chronic conditions, and second, the global shortage and burnout of healthcare workers.

To learn more about Tucuvi, we spoke with Fernando Dal Re, COO of Tucuvi.

Virtual nurse Lola

Tucuvi uses a virtual nurse named Lola, based on speech technology and Natural Language Processing (NLP). Lola conducts natural and empathetic conversations with patients via phone calls. Her backend algorithms analyze the calls in real time and send structured information about patients’ well-being, symptoms and vital signs to the medical team to support them in the process of decision-making.

Tucuvi also features an online tailored dashboard for healthcare providers that previews structured patient information. It enables the creation, configuration and customization of monitoring protocols and alert management for each patient or groups of patients.

How does Tucuvi impact patients’ health?

Tucuvi is an innovation for both healthcare professionals and patients.

For healthcare professionals:

  • Increases remote monitoring capacity of healthcare professionals.
  • Better planning of daily care activities.
  • Alerts that anticipate decompensation.
  • Reduces unnecessary visits, readmissions, and hospitalizations.
  • Analyzes patterns with historical information.
  • Improves health outcomes and patient experience.
  • Enables early hospital discharge of patients.

For patients, their families, and their caregivers:

  • Personalized and continuous care at home.
  • Follow-ups between visits.
  • Fewer commutes to the hospital.
  • Improved treatment adherence.
  • Peace of mind.

What is the story behind Tucuvi?

Before founding Tucuvi, Maria Gonzáles Manso worked at Medtronic and Marcos Rubio worked in the AI field. With both a biomedical engineering study background, they were well acquainted with the many problems in how healthcare is delivered. They decided to join forces to use AI to change healthcare one process at a time.

Any success stories/use case/interesting studies that the client is most proud of?

“For healthcare systems, we reduce chronic patient costs by 70% by avoiding readmissions and saving doctors’ time while multiplying by 30 their capacity to monitor patients at home. We’ve obtained those numbers by working with Spanish public hospitals. Working with the hospital of Torrejón (Madrid), we conducted a retrospective study where 241 patients were included during 9 months, resulting in 26,4% fewer average hospital stays, 62.1% fewer hospitalization required, 55,8% of ER visits reduced, and 55.6% fewer readmissions. Besides, this implies a huge efficiency cost saving, adding up to almost €500.000 in savings. In another retrospective study with the hospital of Vinalopo (Valencia), 149 palliative patients were monitored with LOLA for 5 months. Besides reporting a 9.6/10 satisfaction rate, evidence showed there was a 70% reduction in nurses’ time phone calling, 25% reduction in primary care visits, and 20% reduction in ER visits.”

Watch the following video to understand more about Tucuvi’s patient journey.

Are you curious about Tucuvi or could it be of value in your daily practice? Feel free to contact us by sending a mail to aletta@medscaler.com. Do you want to read more of our client cases? Read it here.