Data analytics is termed as the process of evaluating various sets of data to draw and some inference based on the information provided. The analytic tools and solutions help in health care service as data analytics enables them to harness this information and to question the source before any information is relayed to the public. Indeed, data analytics helps health care providers to identify large patterns leading to a greater understanding of the population. This process is facilitated with the help of a specialized system and software. The system is connected through electronic health records that are available to the physicians which help to reduce cost through unnecessary care (Gandomi & Haider, 2015). Data analytics plays an essential role in ensuring the commercial industries can make informed choices.  Notably, data analytics is regarded as the assortment of applications from business intelligence to the manner in which a business increases its operational efficiency.  The current business environment can benefit from a favorable outcome while still maintaining the highest level of production.

There are many reasons as to why a company has to use data analytics. For company managers, it is difficult to ensure that all the payment is made.  Data analytics helps healthcare providers to support population health management, better financial success and improve the living standards for the community. Since one of the most significant costs that the healthcare industry incurs is the treatment of chronic diseases. On a population-wide level, data analytics will help cut the cost by predicting which of the patients are at higher risk and arrange for immediate intervention (Raghupathi & Raghupathi, 2014). Notably, data analytics continues to be better understood as it promises positive results based on patient experience and quality of health care. Through data analytics, the health care provider can create risk score based on patient-generated health data, lab tests and biometric data to help them get an insight on which patient need enhanced services.

References

Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: promise and potential. Health information science and systems, 2(1), 3.

Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137-144.