Raw Data and Data Analytics

480 SLP2
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Data Analytics
Data analytics refers to the science of analyzing raw data to make inferences about that information (Wang & Alexander, 2020). It is the collection and analysis of data to gain insights and support decision-making (Wang & Alexander, 2020).The techniques of data analytics can reveal trends and metrics that would be lost in big data. This information can then leverage processes to increase an organization's system (Reddy & Ramanadham, 2017). It is used to predict trends, improve outreach and manage disease transmission. This field covers a wide range of businesses and offers insight on micro and macro levels.
From primary areas like clinical data, medical costs, pharmaceuticals, and patient behavior, data analytics are used on micro and macro levels to shape operations, reduce overall costs and improve patient care (Pramanik et al., 2019). It can show progress in clinical data, diagnosis, patient care quality, and business management. When combined with data visualization tools and business intelligence suites, data analytics improve managers' operations by providing real-time information that can deliver actionable insights and support decisions (Craven & Page, 2015). For healthcare organization managers, data analytics provide administrative and financial data alongside information that can improve services, patient care efforts, and existing procedures.
Healthcare organizations can use data analytics to filter huge volumes of data for a short time to determine treatment options or solutions to various diseases (Alexandru et al., 2018). Doing so will provide accurate solutions based on the patient's history and customized solutions to patients' concerns. With data analytics, health care organizations can find it easier to gather clinical data and convert it into relevant insights that medical professionals can use to provide quality care (Craven & Page, 2015). With the transition from models of fee-for-service to value-based care, the need to enhance efficiency makes data analytics a key function of everyday operations.
The ingrained analytics and reporting solution help medical professionals improve performance through the delivery of data-based quality care; reduce wait-times; provide patients with more modified treatments and promote their experience; reduce readmission rates by comparing population health data with the personal patient data to predict at-risk patients; and improve patient satisfaction and quality care by streamlining monotonous processes associated with processing insurance, making appointments and providing referrals (Pramanik et al., 2019).
Opportunities to use Big Data
Big data presents significant opportunities for health care organizations. The three opportunities to use big data in the healthcare organization include analyzing Electronic Health Care Records, discovering a remedy for illness, and reducing healthcare costs (Alexandru et al., 2018).
Analyzing Electronic Records
Analyzing the massive electronic health record would enable a healthcare professional to understand the treatment trends, their impacts, and side effects (Alexandru et al., 2018). The bid data also allows for sharing of the patient’s updated data among physicians for their treatment. It also enables the exchange o medical cases among doctors. These opportunities prevent duplicate tests and redundant treatment procedures (Pramanik et al., 2019).
Discovering a Remedy for illness
When it comes to treatment, certain medications may work for some people but not for others. Before prescription, physicians must first discover new things in the patient to avoid generalization. Therefore, big data can help the doctor identify unrevealed secret information patterns by examining complex data sets. Through automat, big data can learn about human genomes and find out the best cancer remedy (Pramanik et al., 2019). It implies that big data can help fight cancer more effectively.
When deciding a remedy, it is crucial to determine historical information about symptoms, medication, and effects of drugs (Alexandru et al., 2018). In this case, big data is applied to realize a trend towards developing an individualized cure for patients based on their genomic information, lifestyle, reaction to certain pills, family background, and allergies (Pramaniket al., 2019). The appropriate use of genome information can establish a connection between DNA and a particular illness.
Reducing Healthcare Cost
Big data can also be used to provide cost-saving opportunities in healthcare institutions. These organizations can use big data to identify the treatment urgency for a patient. With this information, healthcare organizations can plan and allocate sufficient funds for staffing an...