Vaibhav Tewari, Co Founder, CEO, Portea Medical, in an exclusive interview with Asia Business Outlook, shares his views on how healthcare organizations leverage patient feedback for personalized care plans, challenges involved in integrating wearable technology, how healthcare providers balance the use of advanced data analytics and more. He has over 28 years of extensive experience in building new businesses across industries such as healthcare, business process outsourcing, technology, and supply chain management.
From a healthcare or consumer data perspective, if we look at how the data has evolved or how the communication with the patients has evolved over 25 to 30 years back, we only had satellite TV, which had just come in, followed by Laptops, desktops and smartphones. Hence, over time, information has become closer and closer to us. Given that more and more data is being collected and information has become very personalized for us. Healthcare, for instance, is picking up now, but even across industries, companies are always looking at consumer preferences. And of course, and many times, whether we give feedback or not, how we are treating that particular content, which means if we look at things like OTT platforms, the way we're consuming content over there or content from any website or any of the apps, companies have a fair sense on spending habits, reading habits, eating habits and so on. Hence, whether we're giving feedback or not, the behavior is giving the feedback, and behavior is known all the time as what we're consuming and is known to the organization. Then, the behavior, patterns, and preferences are known to the organizations in detail.
Using that to create content, products, and services is becoming easier along with personalization. And that is something that will only gain more and more momentum as we go along. For instance, with e-commerce sites, the kind of recommendations they are offering, the kind of content that is being shown to us, which is basically about preferences and behaviors, and the data is available to the provider. Hence, I think that is something that we are seeing more and more happening as we go along.
Personalization of healthcare is the most significant positive outcome of AI, data analysis and digitalization prevailing today. The reason is that we can analyze the patient data and create a personalized plan. However, data needs to be collected and collecting data has become much easier with wearable devices. For instance, we look at diabetic patients monitoring their sugars and even healthy people monitoring their sugar levels to make sure that they are not falling into borderline cases of diabetes. Earlier, people had to go to the labs, give their samples and get their sugar levels checked. In the last decade, we got devices like glucometers, which patients could use in their homes and access that data much faster.
However, it was standalone for the patient. We can note it somewhere, and that data can be analyzed and used. Moreover, we have continuous glucose monitoring patches, which have been there for the last few years. We can quickly put that patch on ourselves. Then, the sugar levels are monitored, and the data is available for the clinician to evaluate and create plans for. Now, consider the data a clinician or doctor had available while making a plan earlier versus the kind of information available for himself when making a plan today, and that's where the transformation is. So, what we should do hourly and how we manage our diet, medicine, and day-to-day activities can be much better in today's scenario with these connected devices.
Data security and privacy are important, predominantly in healthcare data, and there's a lot of sensitivity around it. Quite a few regulations are being created, and various organizations are looking at creating the right infrastructure, which becomes technology infrastructure and is very important. Also, it is essential to ensure that we're storing and anonymizing the data the right way.
However, implementing proper data security or management practices in any organization dealing with sensitive data is very important. For instance, when dealing with the patients and their information, you also share data with the family members and spouse and with consent only. Putting some checks and balances into place becomes very important, and some of the regulations are coming into play. Hence, healthcare spaces will become a lot more regulated from a data privacy perspective, and there's a welcome change because so far as those regulations have been there, they are not as strictly adhered to as needed. For the companies that are looking at analyzing data, privacy and ethics become very important. Also, the right rules, regulations, and systems have to be followed through.
The evidence-based approach appears because of the data we are collecting. As per personalization, it will be for particular individuals based on their data. So, we can look at the trends and create patterns and treatment plans, but those remain generic plans. The data and technology available from a larger population will create templates and structure, and that structure will superimpose the decision tree. So, the data and patterns available will give the first three steps of the decision tree, and there is no need to go through those decision tree questions. Subsequently, when we look at treating a particular patient or creating a plan, the rest of the steps will come from the patient's specific data. The good thing is that variable devices and data portability with digital missions will be available to create the next steps. Hence, it's a combination of what is available with the overall technological trends and what is possible to create with individual data, and a combination of the two will make the right personalized plan, which is something any company is looking at doing will end up doing that.
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