Co-morbid Populations Assignment
Co-morbid Populations Assignment
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Managing the quality and cost of co-morbid populations is one of the most challenging aspects of health leadership. In this Discussion, you are challenged with selecting those data which will be most helpful in the management of Medicare populations. As health information exchanges (HIEs) progress at the state, federal, and nation level, health leaders are tasked to participate in the development of analytics tools that can be used to pull data and inform policy practice.
Scenario: Review the high volume Medicare Data Scenario located in the Learning Resources. In this scenario you are asked to work with a complex dataset of co-morbidity data of patients that have three concurrent co-morbid conditions (Chronic Condition Triads: Prevalence and Medicare Spending). How can data from HIT systems be used to formulate useful information to facilitate in the management of this population?
Using the health care information systems standards for clinical and financial data discussed in Week 6 (Chapter 11 of Health Care Information Systems: A Practical Approach for Health Care Management), 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.
Define a “Big Data” analysis dataset to include in a data warehouse by identifying two specific types of clinical and financial data from the Chronic Condition Triads: Prevalence and Medicare Spending dataset in your Learning Resources that you feel could be used to drive behavior change in the patient and provider populations. This Big Data dataset will become the focus of your Discussion.
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.
You must proofread your paper. But do not strictly rely on your computer’s spell-checker and grammar-checker; failure to do so indicates a lack of effort on your part and you can expect your grade to suffer accordingly. Papers with numerous misspelled words and grammatical mistakes will be penalized. Read over your paper – in silence and then aloud – before handing it in and make corrections as necessary. Often it is advantageous to have a friend proofread your paper for obvious errors. Handwritten corrections are preferable to uncorrected mistakes.
Use a standard 10 to 12 point (10 to 12 characters per inch) typeface. Smaller or compressed type and papers with small margins or single-spacing are hard to read. It is better to let your essay run over the recommended number of pages than to try to compress it into fewer pages.
Likewise, large type, large margins, large indentations, triple-spacing, increased leading (space between lines), increased kerning (space between letters), and any other such attempts at “padding” to increase the length of a paper are unacceptable, wasteful of trees, and will not fool your professor.
The paper must be neatly formatted, double-spaced with a one-inch margin on the top, bottom, and sides of each page. When submitting hard copy, be sure to use white paper and print out using dark ink. If it is hard to read your essay, it will also be hard to follow your argument.