Techseen: How is Big Data in Healthcare different from the Big Data that enterprises are dealing with?
Ramaswamy: It is not different; in both the situation you are analyzing the data to make the consumers life easy. In healthcare we save lives with this data and in enterprises we work towards making life comfortable/easier for the user. Big Data in healthcare allows flexible patient monitoring, leading to a better diagnosis and cure for the ailment. Accessing medical data at the point of care through mobile devices helps in reducing medical errors and improves yield. The flexibility of healthcare organizations is increasing significantly, moving towards better healthcare experience.
Techseen: How according to you has the healthcare industry evolved, taking Big Data Analytics into consideration? What major changes have you seen in this sector?
Ramaswamy: The last decade has seen large advances in the amount of data generated on a regular basis, this is being collected for almost everything we do. This also enables us to use technology better, analyze and comprehend it well. Healthcare is no different. Apart from yielding better profits, cutting down on wasted overhead and enhancing the efficiency of the health care providers, Big Data in healthcare is being used to predict epidemics, cure disease, improve quality of life and avoid preventable deaths. The focus now lays on understanding much about the patient as early in their life as possible, making treatment more responsive and benefitting.
Not only are the healthcare providers looking to benefit from these technological advances but also the customers are being responsive to the findings and the offerings. The analysis of big data has been very useful for countries like Africa where it helps the care givers to fight against the epidemics. The spread of Ebola virus was tracked by the mobile phone location of the users, the movement of the population carrying the virus was tracked and thus an analysis was made.
Techseen: What are the initiatives that Philips has undertaken to make Big Data a part of Healthcare? Can you share an example?
Ramaswamy: We started as a modest competence building exercise in 2013 to understand methods and tools used for “Big Data & Analytics”, engage with Philips businesses to analyze existing data, and deliver proof-points that businesses will recognize. One major proof point delivered was the “Data base selling project” of MRI, where based on analysis of historical log files, marketing could approach the customer with engagement models to improve their workflow efficiency. In that process also sell number of equipment’s and spares.
During the process of delivering these proof-points and building competency, a basic Big Data platform got created that could potentially serve many business use cases. The Health Suite Digital Platform (HSDP) as a backbone for all Philips was also starting at the same time and it made best sense to make this Big Data platform as part of HSDP so that it becomes a skeleton for all Analytics uses cases at Philips.
Over the last 2 years this basic platform has matured into a robust reliable cloud based framework that could ingest, process and manage data at scale and support number of business in doing their analytics applications. The platform is also augmented with number of Machine learning framework so that predictive/prescriptive applications could be built on the same. Many businesses are in the pipeline with a spectrum of Analytics use cases across the Health continuum.
Techseen: When you say Big Data in healthcare, what does it mean? Does it revolve around managed services, patient management and equipment management? Or goes beyond?
Ramaswamy: Big Data is not limited to any of these. It covers all of the above spaces and also ventures into the space of personalized medicines. Forbes states, “If you want to find out how Big Data is helping to make the world a better place, there’s no better example than the uses being found for it in healthcare.” Beyond improving profits and cutting down on wasted overhead, Big Data in healthcare is being used to predict epidemics, cure disease, improve quality of life and avoid preventable deaths.
With the world’s population increasing and everyone living longer, models of treatment delivery are rapidly changing, and many of the decisions behind those changes are being driven by data. The drive now is to understand as much about a patient as possible, as early in their life as possible – hopefully picking up warning signs of serious illness at an early enough stage that treatment is far more simple (and less expensive) than if it had not been spotted until later.
Techseen: Can you explain the concept of a ‘Smart Hospital’? How does Analytics fit into this system?
Ramaswamy: A smart hospital is the one that works smart. It has better resources, is creative and can perceive what the doctors and the patients need. However, it should be noted that as much as technology is important so is the design of the facility. The hospital needs to be designed well to allow smooth operations of the new machines and should facilitate patient and supplies management.
A smart hospital works on the seamless blend of multicarrier cellular and Wi-Fi services. Allows information exchange and real time communication for various users. For example it allows monitoring of temperature, humidity, airborne viruses, room pressure, light and sound. This allows the hospital to maintain the conducive atmosphere in the patients room, helping in faster recuperation.
Predictive analytics can help the care givers to diagnose and start the patient’s treatment well in advance. The needed infrastructure and the experts can be arranged well in advance. Apart from this, based on the analysis patient can be kept in favorable conditions to help him/her recover faster. This can help in reducing the healthcare cost, which can be shared with the patients. This also helps to eliminate the unnecessary testing the patient may need to go through.
Techseen: Can Big Data and analytics reduce healthcare sector’s expenditure? Will this affect innovation and increase productivity in any manner?
Ramaswamy: Big data and analytics will surely work towards reducing healthcare sectors expenditure. Healthcare is a growing sector and innovations here are a continuous process. Given the growth of the mobile industry as also internet, apps help mobile phones to be used as everything from pedometers to measure steps walked per day, calorie counters to help you plan your diet, heart rate when exercising – the list is endless. Millions of us are now using mobile technology to help us try and live healthier lifestyles.
More recently, a steady stream of dedicated wearable devices have emerged such as Philips Moonshine/Moonshot, Fitbit, Jawbone and Samsung Gear Fit that allow you to track your progress and upload your data to be compared alongside everyone else’s. In the very near future, you could also be sharing this data with your doctor who will use it as part of his or her diagnostic toolbox when you visit them with an ailment.
Even if there’s nothing wrong with you, access to huge, ever growing databases of information about the state of the health of the general public will allow problems to be spotted before they occur, and remedies – either medicinal or educational – to be prepared in advance. In the realm of the care Continuum, prevention helps bring down costs substantially.
Techseen: You talked about the factors limiting Big Data entry into the Indian Healthcare segment. What are these factors? How does it compare with the global approach? Is it all about regulations and compliance?
Ramaswamy: Regulations play a major role in limiting the Big Data entry in the India Health care segment. Government needs to provide some sort of incentives to the healthcare providers. As on date we pay huge customs duty on the import of any healthcare product and if we manufacture it in the country we have to pay for the import and other such charges. These regulations and limitations act as a deterrent.
However, another most important factor limiting the entry of Big Data is data security. There are guidelines to limit the use and access of the data provided but we need refinement in these policies. This data can be easily misused by anyone who can lay their hands on it, which may cause harm to the patient. Simultaneously, there is limited access too, some healthcare providers/professionals do not reveal the needed data due to vested interests, limiting the scope of analysis or diagnosis.
Techseen: What are the trends that you have seen in global healthcare in terms of Big Data? What is the way forward? And what is the need of the hour?
Big Data revolution is in its infancy. There quite a few value creations that we can expect going forward. The healthcare industry is embracing this phenomenon and is setting itself up for some radical changes and new innovations. Big Data will bring about innovations in process automations which will help reduce cost of care. Big Data will bring in analytical capabilities that will help in recording, monitoring and trending of patient parameters thereby enabling creation of new decision support system which will be a big aid in decentralizing healthcare. Till today, “Health for all” was a distant dream. Big Data coupled with mobile/internet communications could help realize this vision and impact billions of lives in a very positive manner.
