Existing interventions including improving communication and self-care to improve readmission of patients undergoing high risk colorectal surgery involving new ileostomy formation has shown limited results. Our proposal is to deploy a wearable solution that predicts physiological perturbation with continuous remote patient monitoring and advanced machine learning algorithms which will be connected to structured, cascading, escalation pathways and care coordination involving home health nurses, colorectal and ostomy nurses, and colorectal surgeons, and has the potential to transform surgical management in the post-discharge period, where patients are the most vulnerable for readmission. This feasibility study will contribute to the understanding of post-discharge continuous remote monitoring of ileostomy patients, promote patient self-care, and has the potential of improving patient outcomes.
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Attrition Rate
Timeframe: 30 days from patient discharge date
Enrollment Rate
Timeframe: Through study completion, an average of 30 days for each patient