Impact of Big Data on Healthcare Sector - Essay Example

?Impact of Big Data on Healthcare Sector? By Table of Contents Table of Contents 2 Introduction 3 An Overview of Big Data 3 Opportunitiesoffered by the Big Data 4 Major Implementations 5 Issues with Big Data 6 Tools and Techniques utilized on Big Data 7 The impact of Big Data on Healthcare Industry 8 The Concept of Big Data in Healthcare Industry 9 Dealing with Inefficiencies 11 Other Implementations 12 Conclusion 12 Introduction Without a doubt, in the past years, the majority of business organizations have started heavily relaying on data and information not only to survive in this competitive environment but also to compete with other business organizations. In fact, these data and information are believed to be the most important asset for business organizations for the reason that they make use of these data to drive useful patterns on the basis of which they take effective decisions. In addition, because of latest tools and technologies such as the Internet this world has turned into the information based age. There is a huge amount of data available on the Internet. This report presents an analysis of big data. The basic purpose of this research is to present an overview of big data and how it can be used by the organizations for the betterment of their organizational tasks. This report will start with an introduction of big data. After that a general discussion will provided on big data and its associated aspects. In the start this report discusses the general concepts associated with big data however after that a detailed discussion will be provided on the impact of big data on a specific organization. In this scenario, this report will present a detail discussion on the impact of big data on healthcare sector. An Overview of Big Data Basically, “the term big data is normally used as a marketing concept refers to data sets whose size is further than the potential of normally used enterprise tools to gather, manage and organize, and process within an acceptable elapsed time.” (Josyula, Orr and Page 89). In fact, the size of these huge data sets is believed to be a continually growing target. Additionally, the size of big data is presently ranging from a few dozen terabytes to a number of petabytes of data in a single data set (Josyula, Orr and Page 89). In view of the fact this era is known as the age of information and communication technology in which everything appears in digital format, and as a result everything comes under the domain of data. For instance in the medical sector, an electrocardiogram is now used in digital format which can be collected and stored as a dataset and information (attained after the processing of these data). In the same way, MRIs, CT scans and a variety of medical images are at the present digital, and these unique digital records and files are being stored and processed in the form of datasets. Hence, thousands and thousands of distinct datasets are adding up to the big data (Ackerman). Opportunities offered by the Big Data At the present, with the big data the majority of business organizations and retailers make use of data more efficiently to make planned decisions that commence with the customer and help to develop a more thorough design process. In addition, “this analytics-driven design can intensify major touch points all the way through the customer experience at the same time as improving sales beneficially” (Trank p.2). The research has shown that the organizations that use big data for their business can be familiar with their customers and the way they communicate with the business and shop online much better than many of those customers can be familiar with themselves. In fact, these datasets are not only the huge volumes of data but also they provide the organizations with excellent ways to determine and keep records of their transactions as well as other communications with suppliers, retailers, banks, utilities and service providers. In addition, at the present there have emerged a number of algorithms which can be applied on these data sets to determine their customers’ behaviors, shopping patterns, usage of sales coupons and how the business organization performs transactions and certain tasks are recorded and analyzed with the purpose of getting a broad and effective depiction of who your customers are and what products you should take the chance to offer them. In their research article, (Arthur) discusses an example in which Portland Oregon Savory Spice Shop owners Jim Brown and Anne have decided to put into practice social media based marketing and advertising with the intention of getting “the best of big data's” support and capabilities for launching their new boutique store. In this scenario, by making use of their Facebook ads they have been capable of routing to catch the attention of those potential customers and groups of purchasers who almost certainly wish to purchase their high-end specialty products. It is an admitted fact that in the past few years the majority of business organizations have started utilizing social networking based sites such as facebook to advertise their products and services for the reason that these social networks provide huge amounts of data. Considering these innovative aspects of social networks, they just had to invest in the ad and then Facebook algorithms and performing analysis by utilizing ton of consumer data available on Facebook in order to identify those people who most directly match their customer profile. “Those potential customers then get targeted ads and special announcements from the store.” Though, big data provides a large number of advantages and if it is used effectively then it can bring a number of opportunities and benefits to organizations. On the other hand, big data can also be turned into a potential source of annoyance (and even bad) when it encourages unnecessary and unwanted advertising and marketing movements, emails, phone calls; or get the wrong impression about the main theme, causing refutation of credit, wrong charges, or in serious cases, the harmful certainty of identity theft (Arthur; Costonis; Schultz, Schwepker and Good). Major Implementations At the present, the majority of organizations heavily rely on data to not only run their business tasks but also for the improvement of their organizational performance. Hence, the implementation of big data can be seen in every field and industry. However, healthcare industry is believed to be the largest that has taken the maximum advantage of this technology (Southard, Hong and Siau). Issues with Big Data However, there are various problems associated with big data for instance there can be some data security and privacy related problems. In view of the fact that big data contain large volumes of raw data and extracting useful information from these mountains of data is a challenging, costly and time-consuming task (Ackerman). Without a doubt, the emergence "big data" analytics have transformed the way that data is gathered, stored and processed. In fact, a wide variety of techniques are applied to that stored data in order to transform it into business intelligence and make effective use of this data. Without a doubt, this is an amazing technology however with little or no rules with respect to its use. Additionally, companies and users dealing with big data are surrounded by a number of concerns and issues such as information ethics, data privacy and data ownership; however up to now these issues have not been addressed effectively. In this scenario, there is not a particular research or study that differentiates between privacy and data analytics. In fact, the emergence of big data analytics has made this line even more blurred. In addition, the advancements and developments in the field of big data analytics have raised a wide variety of privacy, security, and ownership concerns and issues, not only for customers, however as well as for company making use of data and analytics to deal with these customers. In spite of all the developments and improvements, data privacy and security strategies are up till now serious concerns. Moreover, any questions related to these subjects have a propensity for obtaining little or even no attention (TechTarget). Undoubtedly, huge amount of data and complex analytical techniques applied on data not only make it simple for organizations to redevelop and update their services for customers, however these practices frequently disclose lots of private information related to the customers, their daily activities, their personal living styles together with those of their families, relatives and friends. Additionally, at the present, there exist a number of powerful algorithms and programming tools that can disclose facts that, otherwise cannot be identified regarding particular person as well as promptly show a relationship among a number of components of the data puzzle and find out from time to time with wonderful intelligibility the parameters, such as, record, and even health conditions of a particular person. The extent of this correlation will increase with the amount of data. In this scenario, before implementing big data analytics organizations should cautiously think about the possible privacy and security issues that automatically come with big data and analytics. In addition, there is no appropriate rule or law which defines certain measures on the use of big data. For instance, how much data will be used and for what purpose it will be used and what are the penalties for the misuse of this data (Herold). In addition, the majority of people do not known for what purpose their information is being collected in fact how much information is being gathered. In some cases, they are fully unaware that stores are recording and keeping track of their purchases in due course). Moreover, the fact goes to substantial problem to put out of sight its knowledge from its customers. Though, this information is being collected for some positive activity but in many cases this information is hacked and misused by hackers and the customers bear considerable loss (Stanley). Tools and Techniques utilized on Big Data At the present, a large number of business organizations make use of regression models to identify some useful trends in their business data. Without a doubt, regression analysis is a form of business analytics. In this scenario, regression analysis allows the business organization to use the value of some variable(s) which is known or they are able to control to forecast the value of another variable. In addition, it can be acknowledged as a metric for which a firm can optimize (almost certainly obtain as far above the ground as possible). In simple words, a regression analysis method can refer to the equation for a line that goes onto a disperse area. In this scenario, each value refers to an object of one variable’s response provided the condition of another variable. However, it requires the business management to learn basic concepts of fairly sophisticated linear algebra especially the partial derivatives. There are many software applications which provide excellent support for regression analysis. Some of the well-known software applications can be MS Excel or SAS, or R, or a wide variety of other statistical analysis applications and tools. In a business regression analysis can be acknowledged as the relationship between two variables. For instance, what will be the effect on variable B if the value of variable A changes to some extent? This scenario can be understood with another example, in which a business wants to invest in e-commerce but what will be the return on investment. In this example, investment will be variable A and return on investment will be variable B. In another example, a business can use this regression analysis to determine if a number of employees are increased then what will be the effect on business performance (Jeff) The impact of Big Data on Healthcare Industry The healthcare industry has a significant impact on the quality of our lives as well as how we live within the world. Hence, the mistakes in the healthcare industry can have critical and dangerous consequences or penalties that can have an effect on our capability to carry out communal and creative activities. In their paper, (Fichman, Kohli and Krishnan) discuss that up till now a large number of researches have been carried out to see the impact of information technology (IT) on the healthcare industry. These researchers draw attention to the seriousness of hostile measures in hospitals and the threats such actions cause to the public and the individuals. On the other hand, any kind of medical mistakes (that is a major reason of unfavorable actions and other troubles are costly, raise patient hospital duration of stay, and sometimes cost human lives. In addition, if the healthcare sector fails to have power over infectious diseases it can lead to serious public health problems. For that reason, ensuring maximum quality in the healthcare sector is industriously followed and carefully carried out. In this scenario, information technology can make easier to deal with such issues by identifying and keeping an eye on mistakes at a variety of phases all along the range of care. In addition, information technology performs a critical job at both national and individual levels (Southard, Hong and Siau). In this scenario, big data and analytics are some of the major forms of information technology that are being used in the healthcare industry. In fact, healthcare firms have already started adopting these latest IT trends. The Concept of Big Data in Healthcare Industry In view of the fact that healthcare industry has started to shift from a fee-for-service payment system to a value-based payment system, hence in this scenario big data will surely play an all the time more critical role in how health care providers treat their patients. It is admitted fact that at the present almost all the operations of organizations are based on huge volumes of data so big data or large sets of applicable information can modernize the healthcare industry. Though, big data’s industry dispersion is still much lesser than that of other industries for instance consumer IT. However, a large number of well-known IT providers have started launching big data solutions which are suitable for healthcare sector. Though, big data are used in all kinds of organizations, but its key implementations are seen in the healthcare industry. In the past few years, the trend of using big data has quickly increased particularly in the healthcare sector. It is expected that in the next year it will further grow from $30 billion to $34 billion predominantly due to increasing use in the healthcare sector. It is believed that this investment is more than counteract by the expected opportunities in minimizing healthcare operating cost, with organizational deficiencies and mistakes predictable to cost providers $100-$150 billion yearly. Additionally, the majority of healthcare firms are turning to IT providers for instance Microsoft, SAS, Oracle, Dell and IBM for hiring their data-mining proficiency. They believe that it will help them carry out detective work as well as improve the quality of health care services. In this scenario, by making “purposeful use” of information technology particularly latest IT supported tools and technologies, healthcare providers can qualify for getting the support of millions of dollars from the Obama administration’s health care funding program which they launched in 2009 to support digitization of healthcare data and medical records. There are many cases which can be acknowledged as the successful examples of information technology use to some quantifiable enhancements in the healthcare industry. For instance, in 2010, New York-Presbyterian implemented Microsoft technology to scan and keep track of patient records, which proved to be successful and reduced the pace of potentially lethal blood clots almost by a third (Robertson; Easterwood and Power) (Robertson, 2012; Easterwood & Power, 2012). There is one important example of practical implementation of big data in this example the largest healthcare provider in Massachusetts “Partners Health Care” made use of its huge volume of health data to implement a pilot program on electronic health record usage in post-market analysis of drugs. However, while analyzing system-wide EHRs, it was found that beginning in 2001 the baseline anticipated rate of heart attack admissions to two hospitals jumped approximately18 percent and returned back to regular rate in 2004 matching up with the initiation and termination of the medicine pain-reliever Vioxx. Additionally, Partners Healthcare is currently working to construct this model by making use of the latest developments in health IT (Chai; Fluckinger and Writer; Rooney). Dealing with Inefficiencies The research has shown that performing healthcare activities and implementing measures manually is a daunting, time-consuming and costly process that increases expenditures and overhead for any health care firm. In their paper, (Sumner et al., 2012; Thatcher & Oliver, 2001) discuss that it costs just about $200 to implement reference and background checks on each nurse recruited into a healthcare firm. They also show that the implementation of latest technologies such as cloud computing, big data, IT and analytics for quick data sharing improved the performance of organizations as well as minimized the expenditures by through the automation of organizational tasks (Sumner, Cantiello and Cortelyou-Ward). According to (Khoumbati et al., 2005) more than 850,000 incidents and medical errors occur every year. In the same way, more than 60 persons die daily in UK hospitals because of medical errors. The research has shown that the majority of the errors take place because of the limited capabilities of information technology structure in healthcare organizations. Some of the instances of these errors can be, doctors cannot make correct judgment or inappropriate medications are given to patients or, significant information cannot be delivered or retrieved. It all happens due to ineffective implementation of IT applications. In this scenario, big data analytics based solutions can be implemented to minimize the rate of errors (Khoumbati, Themistocleous and Irani). Other Implementations In addition, big data has the capability to support not only health care providers, but it also provides an excellent support for other industry stakeholders. One of the most important examples of this scenario is the implementation of an integrated health database by Aetna Healthcare, a national diversified healthcare benefits provider. This database is being used by the healthcare firm to enhance evidence-based medicine practices in the most affordable way. Additionally, Aetna has implemented big data in its newly coordinated CarePass and iTriage application to allow its customers to get access to a large collection of health resources on a centralized platform (Chai, 2012; Fluckinger & Writer, 2011; Rooney, 2012). Conclusion In the past few years, the use of data is growing for carrying out a variety of tasks. Almost all the organizations heavily rely on data they collect through different ways. In this scenario, big data is huge volume of data that is collected from a variety of source to perform a variety of tasks on it in order to derive some useful facts. This report has presented a detailed analysis of different aspects associated with big data. Basically, this report has mainly focused on big data in the context of the healthcare industry. This report has discussed various advantages of these technologies by supporting them through existing literature. It is clear from the discussion that big data analytics are already being extensively utilized in a number of industries and particularly in healthcare industry. The research has shown that their role will further grow in the coming years. However, the implementation of these technologies alone does not ensure the success of a healthcare firm as we have discussed many cases in which IT implementation caused deaths of many people due to errors. So in this scenario, effective knowledge and experience is required to make this implementation a success. Healthcare firms should consult literature and latest emerging trends to get insights of these technologies. Works Cited Ackerman, Michael J. "Big Data." The Journal of Medical Practice Management: MPM, Volume 28 Issue 2 (2012): 153-154. Print Arthur, Ed. "Big Data." Alaska Business Monthly, Volume 29 Issue 1 (2013): 72. 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