Introduction
‘Big data' has been a buzzword in several fields and as such is beginning to take root in the field of healthcare. It refers to vast quantities of data that have been arrived at owing to the digitalization of systems in healthcare, therefore, coming upon data that is too vast to be stored and analyzed by traditional means. Big data is currently a special subject in healthcare as it has created the promise for consolidation and analysis of large amounts of data to enable the experts in the field to monitor trends and make predictions. There are various benefits to be gained from the use of big data such as the availability of more precise treatments, prevention of errors in medical records and the practice of medicine itself, reducing costs in healthcare, identifying the high risk patients as well as interventions that work for them and also enhancing patient engagement outcomes (Murdoch & Detsky, 2013). This paper tries to dissect big data in the field of healthcare by looking at the ethics involved, the roles and benefits of big data, how big data can be used to an advantage and also the analytics of big data.
Background
As aforementioned, the term big data may be used to refer to large databases of information that is collected from various places, across time and distance. In healthcare, such data can be drawn from social media, wearable devices, smartphone applications, EHR, clinical trials data and administrative claims. The data is easy to collect because there has been the mass adoption of digital systems in healthcare which have simplified the process of data collection as well as the capacities for healthcare institutions to store information. Therefore big data can be characterized by an extremely large sample size, high heterogeneity, and high dimensionality which refer to a large number of variables available for each unit of observation (Zhang & Hernandez, 2017). Big data can serve many roles in health care. For instance, it can be used with predictive analytics to optimize the outcomes in healthcare. Predictive analytics refers to the statistical techniques that are used in the analysis of current and historical data to be able to predict events. Big data can reveal trends which are pivotal to the prediction of outcomes. By revealing trends in patient information, it could be possible for medical practitioners to know what to expect and perhaps be prepared for it (Stylianou & Talias, 2017). For the prediction of outcomes to be successful, there needs to be both human resources as well as technological requirements. Human resources such as data analysts and also outcome researchers in healthcare will be instrumental in dissecting the data. The storage and maintenance, on the other hand, will be catered for by the technological requirements. There shall be the creation of a dataset that is at patient level hence fully detailed. The human resources can male possible outcome predictions that are more accurate in with customized data.
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Also, another role of big data is that it helps to point out the patients that are at high risk or in deep need (Bates et al., 2014). The breadth of the data is vast hence it is more elaborate in terms on details such as the minorities and their interaction with healthcare. This data seems to be inclusive of vast variables thus enables to highlight various disparities in healthcare such as racial disparities in oncology practice and research. The knowledge that can be found from big data can help then to create specific interventions to address the highlighted disparities and also to find measures to understand and address the biases and limitations of the data sources that are used (Reeder-Hayes, 2017).
With the vast use and potential benefits that can be derived from big data, it is important that there be ethical standards set to oversee its use. Big data is meant to establish the unseen connection between different data points and as such presents various ethical issues in the field or practising medicine (Milton, 2017). The information used in big data is collected from various sources, most of it being from patients, clinics and hospital administration boards. There should be informed consent for the data to be used even though there is often hesitation about questions on how the data will be used. Issues of privacy are very integral because invasiveness is closely related to the big data analysis (Knoopers & Thorogood, 2017). In the process of sharing, aggregating and analyzing big data, there might be a lot of privacy violations and as such research and analysis must be ethical and justified.
Discussion
It could be possible that the use of big data in the field of health care shall enable to take hold of larger opportunities. The challenges of information handling have long been experienced in the medical field thus the advent of big data will help to change the challenge into an opportunity for transforming the medical field (Schultz, 2013). Collecting, translating and analyzing data in the medical field is complex owing to the many branches and departments which have different data sets and challenges. The existence of big data provides an opportunity for researchers in the medical field to partner with supporting business functions. There shall be big data-use cases in various pharmaceutical development lifestyles such as genomics, clinical monitoring and also pharmacovigilance. For instance, big data enables the advent of highly thought of sequencing methods that can be used by the researcher to study genetic across a large population with different variables (Belle et al. 2015).
Big data also opens the medical field to new opportunities and breakthroughs that can be looked at from different perspectives which include descriptive answers of medical conditions hence the right diagnosis and medication procedures and also predictive answers to give events that can be expected with the trends being witnessed in the medical field (Big Data Value Association, 2016). With big data, it is also easy and fast to extract information that is cost effective to the people's health. It is also expected that waste and inefficiency will be reduced in areas of research and development through the availability of information and coordination of researchers, clinical operation, and evidence-based medicine and also public health (Raghupathi & Raghupathi, 2014).
Summary
Big data is essentially characterized by vast amounts of data that expand rapidly and have a high dimensionality. The data has major roles in the field of medicine such as being able to predict the outcomes of medical care and also to identify the limitations and biases of various data sources and data therein to address disparities. There are many promises to be expected from the use of big data in healthcare. These include reduction of errors in the medical field, the prediction of events in medicine based on trends and also the avoidance of wastage and inefficiency. There are various opportunities presented by the use of big data such as the platform for collaboration of researchers and experts from different departments, the creation of data sets that are relevant to patients to make data analysis accurate and also the use of big data in cases of pharmaceutical development.
References
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