Big Data Application in Indian Healthcare

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1 e-issn Volume 3 Issue 5, May 2017 pp Scientific Journal Impact Factor : Big Data Application in Indian Healthcare Miss. Sonali Vinaychandra Pandit BVIMIT, CBD, Belapur Abstract Big data and the related technologies have improved health care tremendously, from understanding the origins of diseases, better treatment, helping patients to monitor their own conditions. By digitizing, combining effectively with big data, healthcare organizations in our country can improve their quality of service by analyzing the effectiveness of the treatment and also the efficiency of the healthcare delivery process by detecting waste, drug abuse and fraud more quickly and efficiently. This paper gives various solutions for how and where big data can be applied in the health care system in India. The main purpose of this study is to determine whether the use of big data can effectively reduce healthcare concerns in India, such as the selection of appropriate treatment, improvement of healthcare systems, increase the efficiency of clinical care, and finding opportunities for cost savings. By providing an overview of the current state of big data applications in the Indian healthcare environment, this study is going to explore the current challenges that Indian government and healthcare stakeholders are facing as well as the opportunities presented by big data. Keywords Big data, Healthcare, analysis, raw data, Digitalization, treatment, quality of service I. INTRODUCTION Big data, that is, massive bodies of digital data collected from all sorts of sources that are too large, raw, or unstructured for analysis using conventional relational database techniques, is the important field of the day for the research community, businesses, and most recently, government. Almost 90% of the global data existing today has been created during the past two years, as 2.5 quintillion bytes of data are generated every day. Even though businesses are leading big data applications, the public sector has begun to be very active, particularly in the search for effective uses of big data with the aim of serving citizens better. [4] Before discussing big data practice in the Indian healthcare environment, it is important to look at what the main attributes of big data are. Today's big data era is based on the following stages: 1) Data processing in the 1960s, 2) Information applications in the 1970s-1980s, 3) Decision support models in the 1990s, 4) Data warehousing and mining in the 2000s, and 5) Emergence of the big data era. [4] The big data era is still in its early stage as most of the technologies and analytical applications emerged around In 2001, Doug Laney, coined the term the 3 V s to define big data Volume, Velocity, and Variety. Big Data has changed the way we manage and analyze data in any industry. One of the most promising areas where Big Data can be applied to make a change is healthcare in India. This paper contributes for collecting data and figures from patients and communities, and using analytical tools to make sense of it, find trends in diseases, predict epidemics, highlight All rights Reserved 27

2 pre-disposition to diseases and suggest solutions for the same are some areas where big data is changing the face of healthcare. Big data opportunity in India is fairly diverse and consists of providers, pharma and medical device R&D, including clinical trials, consumers and marketers and lastly the Government, which would be laggard in adoption curve.[3] Big Data in Healthcare Clinical data: Doctor s notes, prescriptions, machine generated data, large format of images, cine sequences, scanned documents which are generated during clinical care and are not analyzed as normal text data analysis Genomic data: Data acquired from gene analysis and sequencing Health tracker data: Data acquired from various devices, sensors, home monitoring and telehealth Web and social media: Health related data tweets, posts and publishers Health publications and clinical reference data: Clinical research, drug information, disease information, ministry and health body reports Other related data: Personal preferences, behaviors etc. Administrative, commercial, socio economic, population etc. II. LITERATURE SURVEY While studying about Big Data Application in Indian Healthcare, I did survey of other technologies and their problems which contributes in the efficient use and importance of Big Data. These are as follows: 1. Traditional Business Intelligence- BI has always been top-down, putting data in the hands of executives and managers who are looking to track their businesses on the big-picture level. Big Data, on the other hand, is bottom-up. It empowers business end-users in the trenches, enabling them to carry out in-depth analysis to inform real-time decision-making.bi could never have anticipated the multitude of images, MP3 files, videos and social media snippets. 2. Traditional Data Warehouse- The traditional data warehouse system approach would have required extensive data definition work with each of the systems and extensive transfer of data from each of the systems. Copying all the data from each system to a centralized location and keeping it updated is unfeasible. 3. Data Analysis: Analysis is really a large activity, where scanning through all the data the analyst gains some insight. The Healthcare organizations might not have enough working capital to afford the expensive machine and they would have to decide whether to purchase the cheaper machine and incur the additional maintenance costs and risk the downtime or to borrow money with the interest payment, to afford the expensive machine. 4. Data Analytics: Analytics is about applying a mechanical or algorithmic process to derive the insights for example running through various data sets looking for meaningful correlations between All rights Reserved 28

3 5. Data Mining: International Journal of Current Trends in Engineering & Research (IJCTER) This term was most widely used in the late 90's and early 00's when a business consolidated all of its data into an Enterprise Data Warehouse. All of that data was brought together to discover previously unknown trends, anomalies and correlations. 6. Data Science: A combination of mathematics, statistics, programming, the context of the problem being solved, ingenious ways of capturing data that may not be being captured right now plus the ability to look at things 'differently' and the significant and necessary activity of cleansing, preparing and aligning the data. 7. Machine Learning: It uses statistical analysis based on a sample of a total data set. This is one of the tools used by data scientist, where a model is created that mathematically describes a certain process and its outcomes, and then the model provides recommendations and monitors the results. 8. Predictive Analytics: Creating a quantitative model that allows an outcome to be predicted based on as much historical information as can be gathered. In this input data, there will be multiple variables to consider, some of which may be significant and others less significant in determining the outcome. The models become useful if there are certain variables than can be changed that will increase chances of a desired outcome. Hence, on the basis of this literature survey, I can conclude that Big data is generating a lot of importance in every industry including healthcare. I ve learned that they re looking for answers about big data. They ve heard that it s something important and that they need to be thinking about it. But they don t really know what they re supposed to do with it. 2.1Questionnaire- When will we need big data? What should I do to prepare for big data study? What are Healthcare organizations doing with big data in India? What s the best way to use big data in Indian Healthcare system? [2] It s important to describe the place of big data in healthcare today, along with the role it will play in the future. After a lot of research I came to know that healthcare is one of the top social and economic issues in many countries, such as the India, United States, the UK, South Korea, and even middle-income countries. Indian healthcare delivery system is categorized into two major components - public and private. The Government, i.e. public healthcare system comprises limited secondary and tertiary care institutions in main cities and focuses on providing basic healthcare facilities in the form of primary healthcare centers in rural areas. The private sector provides majority of secondary, tertiary care institutions with a major concentration in All rights Reserved 29

4 Considering the size of the Indian population, there is no reason that the premiums cannot be brought down. If we need to participate globally to compete against the cities like China, healthcare is very important. The number of beds in India stands at 1.3 per 1,000 people. In such a situation, the country needs to think ahead of the problem rather than chasing it. Big Data is more than just studying clinical records and mining them; it s also about linking up multiple sets of data to find trends. The country lacked basic health infrastructure, which needed to be functional, before getting into Big Data analytics. For such cases, big data play efficient role to overcome such problems. III. OBJECTIVE We are living in a world dominated by data and its usage. Assessment, analysis, compilation and the systematic usage of available data to improve services is very important and beneficial. According to my research, there are two dimensions where India needs to pay attention; these are the quality and the affordability of healthcare. The country spends just 4% of its gross domestic product on healthcare, with 1.2% coming from public sources and the remaining from private spends on insurance. Globally, private spends are just 20% of overall healthcare spends, but in India this figure stands at around 60%. India should focus on taking healthcare closer to the people in rural India. Around 3/5 th of the people (in rural India) have to travel beyond 5km to access healthcare. Around 50-70% of the time doctors are not available in public healthcare centers. We have among the poorest performing healthcare systems. We have some of the best hospitals, technology. Therefore the Indian Healthcare System should be integrated, networked, based on the principles of primary healthcare. Indian Healthcare organizations and Indian Government must think about it. This paper contributes to 1. Reduce costs of treatment 2. Predict outbreaks of epidemics 3. Avoid preventable diseases 4. Improve the quality of life in India. Average human lifespan is increasing together with the world population which poses new challenges to today s treatment delivery methods in India. Doctors can get massive amounts of All rights Reserved 30

5 and look for best strategies to use this data. The main purpose of this study is to explore whether the use of big data in Indian Healthcare sector can effectively reduce healthcare concerns, such as the selection of appropriate treatment paths, improvement of healthcare systems etc. IV. METHODOLOGY By providing an overview of the current state of big data applications in the healthcare environment, this study has explored the current challenges that governments and healthcare stakeholders are facing as well as the opportunities presented by big data. The methodology used here in this paper is Evaluation. By evaluating data, I got to know about big data application in Indian healthcare more and more. It helped me to get more information about big data in Indian context. Big data enabled technology has made life easier for the medical personnel by enabling cost effective methods of testing and diagnosis through online and mobile applications. Its usage is proving to be highly useful in remote patient monitoring which allows medical practitioners keep an assessment tab on their patients without necessarily seeing them every day. Remote monitoring cuts the costs needed for travelling and regular in-clinic visits, saves time and energy both on the part of doctors and patients. By cutting out on many overhead costs, rent, inventory and labor charges, digitalization enables medical firms to earn better profits and keep funds for purposes of extensive medical research. It also reduces dependence on personnel for customer service, thereby overcome the problem of shortage in medical professionals in clinics and hospitals at a given time. As the lack of skilled talent is one of the problems in Indian healthcare, this is a welcome change. With increasing life expectancy and higher incidence of lifestyle diseases, there is growing consensus among the medical community that the next line of healthcare management will be dedicated to prevention. Much like vaccines helped human kind fight a number of deadly diseases, preventive lifestyles are now being touted as the line of defence against modern lifestyle induced diseases. And helping make sense of the same is use of data analysis to help people adopt preventive measures. One of the major benefits of this cutting edge technology is the convenience experienced by the potential patient. The ability of data analyzers to pick up from available data and provide to the patient what is relevant to them in a matter of a few minutes is remarkable. People now have the chance to consult for a medical opinion by using mobile applications specifically designed to answer their questions as well as connect them to their respective physicians for reminders for tests and check-up. In case of a serious disease, the reduced time in consulting and understanding of symptoms, due to a virtual presence is crucial in making a real difference in medical success. V. RESULTS Patient history takes central role in big data. Digitalization of patient files makes the system far more reliable and accessible for immediate use. Genetic disorders and other warning signs can be tested with the help of such information. In fact, special health packages can be customized for each patient according to their specific needs. A brilliant example of the widespread big data application in the Indian market is the diabetes management industry. Studying Asthma, dengue and malaria- 1) In just 24 hours, using already established data sets and the talents of just 5 of our big data experts, the team was able to describe 3 data stories and write two applications to help physicians. Without specific expertise in the pulmonary healthcare field, they were able All rights Reserved 31

6 International Journal of Current Trends in Engineering & Research (IJCTER) Link geographic areas with greater than expected asthma prevalence to higher ozone levels for extended periods during the summer. Find that 17% of the asthma patients do not show up to the pharmacy to pick up prescribed medications, and are then 13% more likely to have an asthma related hospitalization. 2) Also in the news this week, IBM teamed up with some researchers to study how to predict outbreaks of dengue and malaria. Now, thanks to their efforts we have the chance to identify outbreaks early, to better contain its spread, and allocate resources more effectively. Using an open-source modeling application dubbed the Spatio Temporal Epidemiological Modeler (STEM) created by IBM, researchers will have open access to use any kind of data and quickly correlate it with disease data. While building this application, researchers found they were able to see how changes in local climate and temperature affected the spread of the disease. Now they can use that data to figure out where the next outbreaks will be. VI. CONCLUSION Indian healthcare industry is moving towards the big-data business opportunity. However, we do face manpower shortages as the trained workforce for this big sector is going to be hard to come by. Big business will only come when there is adequate risk capital coming to develop this sector, else it will not be big business in India. With the help of such applications which are based on data collection and analysis, people can find out different areas of concern about their health, including heart rate, sugar level and even calories intake. It helps in an overall development of self-awareness about one s own health. If taken forward with the right approach, Big Data can be a part of the quest for universal health coverage in India. BIBLIOGRAPHY [1] Available from: [2] Available from: [3] Available from: [4] All rights Reserved 32