Rakesh R Shinde, Harish Bharti and Sanjib Choudhury recommend a model for enhancing the emergency medical response system through IT
It was a Friday morning when a colleague got a call informing his brother had met with a near fatal road accident. We rushed to the spot of incident to find that he had been taken to a nearby hospital.
We reached the hospital only to realise that he had been transferred to a different hospital as there was lack of expertise and infrastructure to do the treatment where he was admitted first.
Trouble followed us to the second hospital as his situation aggravated for want of matching blood samples.
Time was short and we were running around endlessly. We were finally fortunate to be able to arrange blood and the patient survived an urgent operation.
The reason why we recounted this experience is because we were analysing this situation later – a very common problem with emergency services in developing countries.
In this article, we present a completely distributed method, leveraging crowd sourcing for availing medical emergency services, resulting in best committed response time for individual services (which includes and not limited to: ambulance, first aid, medical practitioners, hospitals, blood bank service, pathology services, medicines etc.) wherein:
- Each medical service provider can calculate their own ‘committed response time’ based on:
a. ‘Current location’ vs target ‘emergency location’ and additional parameters (weather, traffic, availability of logistics) - Choosing the right medical service provider for each individual medical service by scoring the following:
a. Best ‘committed response time’ offered by providers
b. ‘Committed response time’ compliance history of providers
c. Quality of service of the providers
In developing countries, personal emergency response has an immense scope for improvement in terms of efficiency and effectiveness. Budgetary constraints, lack of political will and inadequate infrastructure pose further problems in providing better emergency care.
On the other hand, mobile (smart phones) and mobile coverage are reasonably good, at least in densely populated cities.
A smart emergency response system leveraging mobile, location-based services and abundantly available skilled medical practitioners can offer an effective solution which is fairly quick and is efficient economically as well as in terms of response time.
Here is a method and model which is unique in addressing medical emergency situations in developing and impoverished countries where infrastructure is often inadequate.
The ecosystem
The adjacent system context diagram showcases the fundamental components which are into play for this method and model. As the model shows – green lines are the preferred source of aid whereas red dotted lines are non-preferred ones. Likewise a ‘single’ star rating for a medical practitioner is of low preference compared to the medical practitioner who is with high stars. All these preferential parameters will be auto computed and managed by the method.
The way we can implement this idea
The interaction diagram showcases varied distributed sources; connected on a cloud hosted centralised repository, allowing the cloud hosted analytics engine to provide high grade lifesaving information related to medical emergency.
Participating hospitals, and critical services third party providers will upload their offering and capability details in a centralised repository which will in turn get uploaded in a separate cloud hosted centralised system of records.
The model will allow all medical service providers to participate in an eco-system where they can register for services they would prefer to offer. Zonal police departments will also be engaged in the process of jurisdiction details, logistical facilities available which the method can leverage to engage appropriate police stations.
In a highlight, the model will allow volunteering medical practitioners to come forward and register for this social cause and upload skill details and volunteering history.
The method, based on the system of records, will auto initiate an authenticity check for the involved actors. For instance; valid operating license check for participating hospitals and critical service providers such as ambulance services, blood banks operators, medical store operators, medical practitioners and so forth – to ensure better quality of service and compliance.
The method, being an advanced medical emergency response system, will allow civilians, medical practitioners and medical service providers to collaborate on this highly intelligent platform and benefit from its cloud-based analytics offerings and capabilities.
The method, is to adopt and offer benefits of cloud computing – ensuring that the adopting government is benefitting from
a) Optimised server utilisation
b) Lower cost
c) Dynamic scalability
d) Shortened development life cycle
e) Reduced time for implementation
The adjacent flow diagram showcases an overview of the overall interaction flow of the method.
During the decision making journey, the method will offer a reliable solution which is equipped with cutting-edge solutions such as cloud infrastructure, smart mobile apps, global positioning system (GPS) enabled – yet secure, cost effective and easy to implement and adopt. In addition, this method will also offer solutions for scenarios where smart mobile phones, GPS are unaffordable or unavailable – the solution will offer a reliable, secure, cost effective, easy to implement and adaptive model.