
DEARhealth
AI-powered platform enabling dynamic care pathways, real-time clinical decision support, and chronic condition management.
Date | Investors | Amount | Round |
---|---|---|---|
- | investor investor | €0.0 | round |
investor | €0.0 | round | |
investor investor investor | €0.0 | round | |
investor | €0.0 | round | |
* | N/A | Acquisition | |
Total Funding | 000k |







USD | 2020 | 2021 | 2022 | 2023 |
---|---|---|---|---|
Revenues | 0000 | 0000 | 0000 | 0000 |
% growth | - | 5 % | 22 % | - |
EBITDA | 0000 | 0000 | 0000 | 0000 |
Profit | 0000 | 0000 | 0000 | 0000 |
EV | 0000 | 0000 | 0000 | 0000 |
EV / revenue | 00.0x | 00.0x | 00.0x | 00.0x |
EV / EBITDA | 00.0x | 00.0x | 00.0x | 00.0x |
R&D budget | 0000 | 0000 | 0000 | 0000 |
Source: Dealroom estimates
Related Content
DEARhealth is a healthtech platform that delivers AI-driven care pathways for the personalised management of chronic conditions. Designed to integrate seamlessly with electronic health records (EHRs), the system enables real-time clinical decision support based on continuously updated patient data. By analysing risk levels and patient-reported outcomes, DEARhealth generates dynamic care plans that adapt to individual needs and clinical progress.
The platform is structured to support care teams in managing complex diseases across multiple stakeholders, including specialists, nurses, patients, and caregivers. Its engine uses clinical guidelines and AI to recommend next best actions, aiming to reduce avoidable hospitalisations, treatment delays, and healthcare costs.
Clinically validated in academic hospitals in the US and Europe, DEARhealth has demonstrated improvements in patient satisfaction and health outcomes, while reducing unnecessary interventions. It supports multiple chronic conditions such as epilepsy, oncology, and inflammatory bowel disease (IBD).
Founded as a spin-out of the University of California, Los Angeles (UCLA), DEARhealth focuses on enterprise-grade solutions for healthcare systems, life science companies, and payers.
Keywords / Tags: ai applications, connected device, healthcare, ehr integration, chronic disease management, clinical decision support, personalised medicine, digital health, enterprise software.