1. Tell us about yourself and Inforich technology solutions.

Actually Inforich technology solutions was born in April 2012 and from that time onwards our focus has to solve the healthcare problems in the health informatics space specifically so, we were trying to build a solution or a platform which will solve the problems for entering the data from the doctors perspective, a nurse perspective and ultimately from all the stakeholders in the ecosystem. With this solution, we two founders started this off and it’s been like a long journey of seven and a half years of experience and this has taught us and we have all created client bases across the Middle East, South East Asia, and India and we hope you’ll take this as a global product.

2. What was thought to create an entity to work on the problem of healthcare?

Basically it’s a very simple motivation because when you personally go to any Hospital you don’t have all your records in one place, so multiple times people ask you very simple things starting with what is your age what is your name. Those basic things are also not solved. We have a lot of IT systems at the moment in the hospital environment or the clinical environment but then these are more of billing solutions. Like electronic medical record system, you don’t have something very comprehensive just as a quick check. If you want just to go back and see whether you have your medical history for the last one year or two years. So that itself will answer your queries. This is the very strong pain point which is required but with the futuristic thing. There are a lot of technologies which can actually help you to predict diseases. If you have a history of data with you, you can actually predict and this will actually help you to prevent and protect yourself from more diseases and all falling sick. So the model which we are trying to focus used to move from ‘sick care’ to ‘healthcare’.

3. What were the challenges you faced in implementing an AI solution and how did you overcome it?

Basically this is a terminology which is widely used nowadays ‘artificial intelligence’. We were using this technology almost like seven years back but we did not put it the term like AI on top of it. The whole model is like when you have data in one place, then only you will have the AI and all to run on it whatever algorithms will be built. But the challenge at the moment is we don’t have data in a structured format from different sources. That is the first point and we are trying to solve that problem to aggregate the data into one place, so that all the hospital owners or the patient side or the doctor side, they all can accept the data in whatever form and then make meaningful outcomes out of it. That is where we will use techniques like AI and machine learning. These two things will help improve the efficiency of the doctors so that they can see more patients very quickly and more accurately. That is the most important point.

4. Data protection bill is coming in India. How the EMR companies like you will change its strategies in data collection storage and transfers etc?

Whenever any ERP solution which is like EMR is one of the database applications. Data is the most critical element, everybody says data is the new oil. Definitely you need to secure it. How would you secure it? There are a lot of protocols which are coming up which has to be defined authorized by the concerned cyber security team or the Ministry of Defense and all those guys are supposed to manage all this data. What we are trying to do is we have the capability in our product to chew it to tweak the data in such a way that you yourself will find the data in a secure place. The data regulatory companies can tell us what are the requirements and we can very easily comply to it, that is the strategy. So, we flipped it from that side we don’t have to change our product. The only thing is to tell us what are the regulations which you want to implement in the region. We can get compiled to it automatically because what we are going to build is a global product so may be the rules in India might be different from the rules in the US may be rules are different in Europe. Our solution is capable of adopting to multiple security levels at different country levels. This is where we have this kind of idea which is coming up like in Europe. We are working on GDPR because that is the way how you protect your data, so they are up to it.

5. You being an EMR and AI company do you think healthcare is prepared for it?

Healthcare at the moment is not prepared that’s what I said because the data is not in a single place at the moment. We have created a lot of silos. All your data is in different-different parts. The first thing is you have to integrate everything together, then only you can talk about AI. The first challenge for AI to be executed is to have the data in one place. That is where we are working on and we are getting all these stakeholders to put data in a structured format so that it is much easier to manage.

6. How does your organization fuel innovation in healthcare IT?

I think innovation actually comes in when you get closer to the customers. Our customers being the hospitals, clinics and doctors, we spent a lot of time with them. We understand what are their pain points, we don’t develop solution sitting in our offices. We actually get on the ground and discuss with the IT guys and the doctors to understand what are the problems. Technology has got a lot of benefits like AI, machine learning and all but doctors need not to understand that. It is our responsibility to understand the technology and it is the doctor’s responsibility to tell us the problems that they’re facing and technology can solve all the problems. Listening to the customers at their locations is the most critical element and that is how we think innovation is helpful. Otherwise, if I innovate sitting in my office that might not be relevant to them.

7. To all the startups out there who are hustling in AI and healthcare, what message would you like to give them?

My advice to all the healthcare startups is to focus on one domain like could be cancer, it could be diabetes, it could be obesity, concentrate on one and then build a huge database on that. Then maybe you trained your algorithms and all based on that. Then you go to the next lead where you can go and scale and use this evidence-based kind of solutions to take the what you call the best practices and all across different parts of the world. II think that’s the way to go forward, focus on one niche domain and then be the master in that, have a lot of data because the people are not very comfortable sharing data so first we need to build that confidence for them to share the data telling them that you will give them more insights from which they can take decisions based on that.