WARD: Wireless Assessment of Respiratory and Circulatory Distress in Surgery and Rehabilitation

Background:

More than 200 million cases of major non-cardiac surgery are performed worldwide annually. A high percentage of patients undergoing major surgery develop severe postoperative complications (1). Cardiopulmonary vital parameters are measured at least every 12 hour in the hospital to assess clinical state of the patients (2). However, some patients may deteriorate between the measurements and continuous wireless monitoring may provide early detection (3). 

Project Objectives:

Complications in postoperative - and rehabilitation patients are related to a high morbidity, mortality and increased costs in the healthcare system. 
It is estimated that 20-30 % of all patients undergoing major abdominal surgery will develop a severe complication.
The aim of this study is to assess the association between deviating vital parameters and serious adverse events.
By combining machine learning technology and wireless continuous monitoring of vital parameters, we aim to develop a clinical support system to predict physiological abnormal values before they occur, to allow early intervention and ultimately to prevent adverse outcomes in both postoperative - and - rehabilitation patients.

References:

1. Fields AC, Divino CM. Surgical outcomes in patients with chronic obstructive pulmonary disease undergoing abdominal operations: An analysis of 331,425 patients. Surgery. 2016;159(4):1210–6.
2.  The Royal College of Physicians (RCP). National Early Warning Score (NEWS) RCP London. https://www.rcplondon.ac.uk/projects/outputs/national-early-warning-score-news-2.
3. Haahr-Raunkjær C, Meyhoff CS, Sørensen HBD, Olsen RM, Aasvang EK. Technological aided assessment of the acutely ill patient – The case of postoperative complications. European Journal of Internal Medicine. 2017;45:41-45