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Write 350 words APA standard: identify specific types of data (data sets, standards, examples of those data) that can be redeveloped into Big Data tools and used to address the management of population health initiatives. Explain why the two specific types of clinical and financial data you selected as your Big Data dataset would best affect behavior change in the type of co-morbid Medicare populations served in the scenario. Explain and assess how this Big Data dataset can change the behaviors of health care providers in the scenario. Assuming that your Big Data dataset is going to be shared in a regional health information exchange, explain how the Centers for Medicare and Medicaid Services and private payers might use these regional data sets to increase value in delivering services to co-morbid Medicare patient populations in the region

please include references






Subject Nursing Pages 3 Style APA


Big Data Tools

Advancement of technology and huge data has necessitated development of the concept of big data analytics in health care to improve management of healthcare and support decision making among many other functions. This paper identifies specific data sets that can be developed into big data tools, how they affect behaviour change among patients with chronic conditions among others.

The data sets are categorised into clinical and financial. Examples of clinical data sets include specific chronic conditions such as Alxheimer’s Diseases/Dementia and depression, age, and sex while financial data sets include, the per capita medical spending, cost of the treatment and medication etc.

These two data sets affect behaviour change in patients with co-morbid chronic conditions in various ways.  Clinical information provided such as the types of chronic condition will provide direction on the suitable medication.  Age and sex also will help define the kind of care and guide in the provision of appropriate medication. Similarly, financial data sets will help the service providers to plan on the appropriate care that the patient should be provided. It will also help in financial planning; identifying those eligible for the cover and those whose cover has expired (Lebied, 2017).

Big data datasets can as well change behaviours of health care providers. It will impact on the way they manage, analyse and leverage their data in their service provision initiatives. The health providers will easily access to this information helping them make decisive decisions about proper care and the financial situation (Raghupathi & Raghupathi, 2014). Furthermore, service managers will be able to sort various chronic condition cases based on different criteria such as the condition, the age and the sex, facilitating their analysis and interpretation of the data. This will help them in their planning, especially when administering care to patients. Furthermore, health care providers can use the information to make prediction on the number of patients likely to be at the health centre which enables them to schedule and plan in advance (Lebied, 2017).

In case the big data is shared with regional health information exchange Centers for Medicare and Medicaid Services and private payers will still have an opportunity to use the regional data set to increase value as they deliver services to the co-morbid chronic patients Medicare patients.  The regional health information will have to be linked with various health centers in the remote locations. However, it would be important that the information is input at a central location to avoid altercations and unnecessary interference with the same. Therefore, it means that the data bank will be maintained at a central point to ensure uniformity.  Furthermore, the system should have high security measures that would be able to trace any alterations or additions of the data to avoid any kind of data compromise and at the same time safeguarding the privacy and confidentiality of the information. Telemedicine and real time alerting concepts can be alternative ways of accessing to this information (Lebied, 2017).





Lebied, M. (2017). 9 Examples of Big Data Analytics in Healthcare That Can Save People            Retrieved from: http://www.datapine.com/blog/big-data-examples-in-healthcare/

Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: promise and   potential. Health Information Science and Systems2, 3. http://doi.org/10.1186/2047- 2501-2-3




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