RELIANCE
RELIANCE Project summary
Cancer is a prevalent and devastating condition, with surgical resection often being the best hope for patients. However, the current perioperative care system is overwhelmed, straining hospital resources like staffing and bed availability. This bottleneck means fewer patients receiving treatment soon after diagnosis, leading to delays that may worsen patient outcomes. Cancer patients undergoing surgical resections typically spend 1 day in ICU and 7 days in a surgical ward before being discharged to home. Alarmingly, >25% of them experience (severe) complications and over 10% require rehospitalization. Research has shown that automated detection of patient deterioration can significantly improve patient outcomes.
Currently, perioperative care teams lack the tools to extend patient care beyond the hospital setting, and low-acuity wards are not equipped for continuous vital sign monitoring. This results in labor-intensive and prolonged hospital stays, as well as delays in identifying patient deterioration both in low-acuity care settings and at home.
Extending perioperative care from high- to lower-acuity settings, including the patient鈥檚 home, through continuous vital signs monitoring offers the potential solution. By providing timely, and ideally predictive, updates on patient health, care teams can intervene promptly, optimizing postoperative outcomes. Pre- and post-operative risk assessments and (remote) early detection or prediction of patient deterioration allows improvement of patient outcomes and experiences, from pre-operative condition optimalization to post-operative recovery.
The RELIANCE-project aims to develop advanced monitoring strategies using wearable technologies for patients undergoing surgical procedures for cancer treatment. These strategies will predict and signal adverse events in a timely manner, ultimately enhancing clinical decision support. Together, these results will deliver an integrated solution for smart wearable measurement technologies, improving patient monitoring and clinical workflow and decision-support in peri-operative care, including: (1) reliable algorithms for remote clinical decision making; (2) user-friendly workflows; and (3) clinical validation via proof points.
Research references:
Holland High Tech project page: