RASUS: Rapid Assistance System through Uber-inspired Software for localization on-line of nurses and doctors

Abstract

We present RASUS: Rapid Assistance System through Uber-inspired Software aimed to provide information in real time about the geolocation of healthcare practitioners and patients. RASUS is designed to be used in the cases where rapid assistance and intervention is required. Once the patient has located the closest doctors (or nurses), the subsequent step is the decision of the patient to make a call to one of them. The usage of this software might be advantageous in those patients whose localizations are far from hospitals (or health centers) but pretty close to doctors or nurses which might be available to provide services in cases of emergency. The efficiency of RASUS is evaluated in the cases where type-2 diabetic patients are under imminent risk of being assaulted by unexpected diabetic coma. We have simulated random geolocation for both patients and healthcare practitioners in a Peri-urban area of Lima city in order to predict the advantages and disadvantages of software. From a Monte Carlo simulation, a 78% of diabetes patients (of a simulated sample) using RASUS might surpass the diabetic coma with a deviation of order of ±10%.