One of the leading microfinance institutions in India started an initiative to empower rural women, by providing them with micro loans. Their main purpose is to encourage entrepreneurship amongst rural women. In addition to the micro-loans, this organisation also provides free healthcare insurance. Their primary goal is to create opportunities for rural women to become financially independent. However this does not mean that healthcare insurance is just a simple addition.
The microfinancing institution looks after providing an end to end solution towards providing healthcare services to their customers. In the unfortunate circumstance if someone falls ill, the insurer only needs to get in contact with a field officer. The rest of the steps from finding the correct hospital to getting the sick admitted will be taken care of by the organisation.
What were some of the major challenges faced by the organisation
Prior to automation the entire model for processing the health insurance, was lengthy and required a lot of manual work and coordination. This model wasn’t very sustainable to scale, here are the reasons that drove the institution to seek out another workflow:
- Data availability: Since this workflow model depended entirely on the three coordinators, on a simple WhatsApp chat the access to data was very limited. Finding out important things like the policy number, customers insurance cover, etc was not easy to find, making the process more time consuming,
- Poor tracking of service: The whole process involves chat messages between the coordinators, and phone calls. This basically makes it difficult for the Central Medical Team to look at the process and identify whether or not a patient has received treatment.
- Higher chances of mistakes: Since the entire process is manual and completely decentralized the scope for error is high. A simple miscommunication in even one step of the way could cause the entire chain to get affected.
Working manually raised a bunch of issues ranging from managing data, to requiring higher time in processing, lack of control from a centralized perspective, and high scope for error in documentation or processing of the clients information.
How did the model for the insurance scheme work?
The agenda behind providing healthcare insurance along with microfinancing loans, is to make healthcare accessible for rural families.This is the flow of how the Insurance scheme model worked at large:
- Customers would get in touch with their respective Field Officers regarding the need for medical assistance.
- Field Officer raises the customer's request on a WhatsApp group consisting of an insurance representative and company medical coordinator.
- Medical coordinator gets in touch with the customer to get a better understanding of the claim query.
- Medical coordinator then gets in contact with the insurance representative, to identify treatment facility based on the case.
- Medical coordinator assists the customer to the assigned facility and helps them out with their admission documents.
Why Automation?
As we all know, time is of the utmost importance when it comes to treating a patient. This is precisely why the microfinancing organisation was on the lookout for a quicker more reliable workflow to streamline the processing of healthcare claims. App development can take a lot of time and money, and hence the organisation was keen on finding a solution that can leverage an existing platform to help them streamline everything.
They got in touch with the team at Quickwork, and together we created a Journey using Facebook Messenger to solve these issues, giving birth to a bot that provides data access, transparency, and reduces the scope of error, while being both cost and time effective.
How Facebook Messenger helped change the face of processing healthcare claims
Facebook helps connect over millions of people across the world,free of cost. What started out as a project for ranking college kids, is now one of the most widely used and recognised social media platforms. So much so, that Facebook can be accessed in over 12 Indian languages. It is precisely the diversity and scope of potential to be unlocked through this platform that led to us choosing Facebook Messenger as the platform for the face of our automation.
Here’s a look at the model for insurance schemes with automation:
- A chatbot was created using Facebook Messenger as the platform to access everything and provide better coordination.
- The Field Officer would raise a request on the chatbot, which would then be passed on to the other two entities.
- The chatbot ensured that action is being taken in a timely manner, by sending notification reminders to the concerned person, and by raising the issue to higher authorities for faster clearances if needed.
- Complete transparency was created, since the central team can access and follow each step of each case through a dashboard in the backend.
- Data can be easily accessed, the chatbot can retrieve data regarding patients insurance cover from the backend, reducing the time of manually searching.
- Reduced need for coordination, as the chatbot would correctly contact the right POC for each step.
- This entire flow was created and made active in a week’s time, providing a real time quick solution to solving a persisting issue.
Overall with the help of automation the microfinancing organisation was able to solve their issue, and find a streamlined long-term solution which didn’t require much training to access and implement in the daily workflow. Get in touch with us to know more about such streamlined success stories.
