A5010357331- Health Systems, Economic Evaluations, Quality of Life
- Sepsis Diagnosis and Treatment
- Patient-Provider Communication in Healthcare
- Statistical Methods in Clinical Trials
- Palliative Care and End-of-Life Issues
- Neonatal and fetal brain pathology
- Non-Invasive Vital Sign Monitoring
- Clinical practice guidelines implementation
- Economic and Financial Impacts of Cancer
- Frailty in Older Adults
- Cancer survivorship and care
- Nutrition and Health in Aging
Leitat Technological Center
2023
Instituto de Investigación Sanitaria La Fe
2022
INCLIVA Health Research Institute
2019
Cancer is a primary public concern in the European continent. Due to large case numbers and survival rates, significant population living with cancer needs. Consequently, health professionals must deal complex treatment decision-making processes. In this context, quantity of data collected during care delivery. Once collected, these are for access support clinical performance review. There need innovative tools that make more accessible activities. Following co-creation, an interactive...
LifeChamps is an EU Horizon 2020 project that aims to create a digital platform enable monitoring of health-related quality life and frailty in patients with cancer over the age 65. Our primary objective assess feasibility, usability, acceptability, fidelity, adherence, safety parameters when implementing routine care. Secondary objectives involve evaluating preliminary signals efficacy cost-effectiveness indicators.
This study is to evaluate healthcare needs, preferences, and expectations in supportive cancer care as perceived by survivors, family caregivers, professionals. Key stakeholders consisted of survivors diagnosed with breast cancer, prostate or melanoma; adult caregivers; professionals involved oncology. Recruitment was via several routes, data were collected either online surveys telephone interviews Greece, Spain, Sweden, the UK. Framework analysis applied dataset. One hundred fifty-five...
Heart rate variability (HRV) monitoring has shown to be promising early diagnose neonatal sepsis and therefore the objective is develop a minimally invasive cost-effective tool, based on HRV machine learning (ML) algorithms, predict risk in neonates within first 48 hours of life. Seventy-nine new-borns, with less than life gestational age between 36 41 weeks, borned Consorci Hospital General Universitari València were enrolled after tutor's authorization. Fifteen them diagnosed sepsis....