HyperHack-2023 - Rapid Response

HyperHack-2023 - Rapid Response

Use Case Description

Problem Statement:
The Ambulance Routing Problem (ARP) is a global concern, leading to substantial loss of lives due to unprepared hospitals and delayed ambulance arrival during emergencies. Delayed responses lead to heightened mortality rates, especially for time-sensitive medical conditions and severe injuries, worsened by urban traffic congestion. Inadequate hospital bed availability upon patient arrival further hampers timely care, disproportionately affecting vulnerable patients. Urgent action is crucial to develop an optimized ambulance routing system, enhancing emergency medical services and saving more lives. Recent incidents like 500 Brits dying due to ambulance delays and over 10,000 patients dying from ambulance delays in India underscore the severity of this global issue.

Solution:
The proposed solution is to develop an advanced UiPath Apps application for ambulances and hospitals, integrating AI Center, Studio workflow, and Data Service, along with Bing Maps API. This app will optimize emergency response with real-time ambulance routing to the nearest hospital based on the patient’s medical needs, minimizing response times. The application will also allow paramedics to communicate directly with the hospital, providing them with vital updates on the patient’s condition en route. AI Center will use patient vitals info to infer the patient’s condition, assisting paramedics in diagnosing critical conditions during transit. This seamless integration enhances emergency medical response and support for paramedics and healthcare providers.

Benefits:
Shortened Response time for the ambulance to pick a viable hospital without any third party required.
Routing to the hospital based on live traffic conditions.
Functionality to share requirements and info during travel.
Sharing Vitals and implementing predictive analysis using Machine Learning.
Hospitals can choose services they are able to provide to help with their preparedness.

AS IS Flow:
The following depicts general medical emergency scenario -
An emergency call is connected to the nearest ambulance
The ambulance reaches the address of emergency and attender provides first aid and records vitals
The ambulance navigates to the nearest hospital with no real-time information on traffic or diversions or information on specialist’s availability
Based on the diagnosis, the emergency section of the hospital can confirm whether there is a specialist for the condition of the patient available or a bed available in the hospital before commencing the treatment
If the hospital is not the right fix, the ambulance and the patient navigate to the next nearest hospital. This continues on until the right hospital is found for the treatment of the patient which results in loss of crucial time

AS-IS WORKFLOW, TO-BE WORKFLOW

Other information about the use case

Industry categories for this use case: Healthcare Pharma

Skill level required: Advanced

UiPath Products that were used: UiPath Studio, UiPath AI Center, UiPath Apps, UiPath Data Services

Other applications that were used: Python, Windows SDK Library, Bing Maps API, Speech Recognition Library

Other resources: -

What is the top ROI driver for this use case?: Other

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