Healthcare data : Trends
There is a lot of work happening in the healthcare data space and giving everything that’s happening around us in the healthcare ecosystem a lot of new data is being generated new technology applications are being adopted. As a result of that digital-held records are now excessively getting produced what’s happening as a result of this is excessive data is available so excessive data processing is required as well as how do you make that data usable. How do you make that data clean, how do make that data analyzable and it’s finally 3rd trend which is building all the used cases of processed data, whether it’s personalizing care better whether it’s about research whether it’s about building, whether its about algorithm global application are being created to generate value from this data. In general health care data is getting created in a lot of processing engines, are being created to process and make this data analyzable and then finally building series of applications to deliver value from healthcare data.THB’s Focus
THB is a healthcare data technology platform, our focus is to deliver value from healthcare data.
Generation of data, Processing of that data, and building application on top of that. Our focus is on 2nd and 3rd as to how do we process that data to make it analysable. We have proprietary healthcare data take technologies and then we have series of applications doing multiple things, today the industry needs personalization of care for patients that are area of focus.
There is a lot of work happening in clinical research vaccines, medicine, speed & O2O market to launch are accelerating which means more research needs to be created. After they have launched there is a lot of focus on real-world evidence as a result of that and there is a bunch of focus now happening around to take the clinical evidence and help doctors, help practitioners, and help the medical fraternity to take the decision of treatment for timely diagnosis, better diagnosis, timely treatment and so on and so far. A lot of focus is that we at THB is generating is around 3 big themes personalized care of patients, generate fear world evidence research and support medical practitioner with a decision support system.
The impact of work we do and anyone in health care space the end beneficiary is always a patient, why are we doing research? Because we want the best medicine to reach the patients! Why are we personalizing the care? So that each customer, each patient who has specific needs from his therapy and thus indication and his condition perspective gets the right targeted treatment. Why do we want the right decision support system to available to doctor? So that timely diagnosis can be done so a lot of the impact directly or indirectly is benefitting the end patient. It’s truly said if give better care what that means is stickiness for the hospital goes up so indirectly benefits the hospital as well if timely the right medicines are being given its benefits to the pharma company if patients don’t necessarily get admitted in the hospital. Moreover, preventive in nature and the risk can be preempted in a time insurance company is benefited so, of course, everyone in the ecosystem benefits but the primary end beneficiary will always be the patient.
Making data usable: Challenges
There are a bunch of challenges thankfully technology has evolved to a scale now that a lot of those technology-related challenges that used to exist cannot be solved cloud technology, big data architecture has evolved to a level where we can process terabytes of data sets. The quality of data still continues to be a challenge. People don’t necessarily follow the standard of recording the day, people don’t necessarily follow ICD coding that is globally acceptable and a lot of systems are still not interoperable as they don’t talk to each other.
There are a lot of challenges that how do you make this better usable and in fact as life saver, write a lot of about 70% of work that anyone needs to do is really about making that data so much usable. There are challenges and almost all of this work is novel in nature. Patients, are still learning how will this deliver results for them and how will this help them deliver better care so on.
So far a lot of things are being experimented, proof of concept is being done so a lot of those things are yet to see the level of scale impact for a country which has 1 billion population but you know the typical challenge is how do you process the data and how do you really sort of creating that scale impact by demonstrating real outcomes of all the pilot work you do.
Future of health care data
I think the future is going to be great, we have seen the evolution of almost every industry and technology we have seen fintech. We have seen education tech, we have seen mobile tech, we have seen e-commerce we have seen all the industry scaling up. I think this is the era of healthcare, next three to five years the maximum disruption and evolution an option of technology as well as data is going to be in the area of healthcare and as a result of that we believe that the way treatment is being given.
The way patients are getting care, the way patients are consuming treatments, the way pharma companies are delivering medicines, the way hospitals are delivering care is going to fundamentally change a lot of hospitals are now doing outpatient through digital technology. Really a lot of hospitals are going to evolve doing more impatient surgeries, similarly, pharma companies used to have large feet of street medical representatives to meet doctors a lot of that is getting digitalized now a lot of that nonlinear sales growth is not going to start taking in.
Insurance companies are more conscious about how to take data and help the patients get the right timely care so that they don’t reach the stage where they need hospitalization and at the end of the day how do we show patients really starting to see clinical outcomes and improvements. So, I think the future is great people are using technology for efficient efficiency, for revenue acceleration, for better clinical outcomes.