Description
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.
Grading Rubric
| Discussion Posting Content |
Points: Points Range: 16 (53.33%) – 18 (60%) Discussion posting demonstrates an excellent understanding of all of the concepts and key points presented in the text/s and Learning Resources. Posting provides significant detail including multiple relevant examples, evidence from the readings and other scholarly sources, triangulation and discerning ideas. Feedback: |
Points: Points Range: 14 (46.67%) – 15 (50%) Discussion posting demonstrates a good understanding of most of the concepts and key points presented in the text/s and Learning Resources. Posting provides moderate detail (including at least one pertinent example), evidence from the readings and other scholarly sources, attempt at triangulation and discerning ideas. Feedback: |
Points: Points Range: 12 (40%) – 13 (43.33%) Discussion posting demonstrates a fair understanding of the concepts and key points as presented in the text/s and Learning Resources. Posting may be lacking or incorrect in some area, or in detail and specificity, and/or may not include sufficient pertinent examples or provide sufficient evidence from the readings or triangulation. Feedback: |
Points: Points Range: 0 (0%) – 11 (36.67%) Discussion posting demonstrates poor or no understanding of the concepts and key points of the text/s and Learning Resources. Posting is incorrect and/or shallow and/or does not include any pertinent examples or provide sufficient evidence from the readings. No attempt at triangulation was shown. Feedback: |
|---|---|---|---|---|
| Peer Feedback and Interaction |
Points: Points Range: 6 (20%) – 6 (20%) The feedback postings and responses to questions are excellent and fully contribute to the quality of interaction by offering constructive critique, suggestions, in-depth questions, additional resources, and stimulating thoughts and/or probes. Feedback: |
Points: Points Range: 5 (16.67%) – 5 (16.67%) The feedback postings and responses to questions are good but may not fully contribute to the quality of interaction by offering constructive critique, suggestions, in-depth questions, additional resources, and stimulating thoughts and/or probes. Feedback: |
Points: Points Range: 4 (13.33%) – 4 (13.33%) The feedback postings and responses to questions only partially contribute to the quality of interaction by offering insufficient constructive critique or suggestions, shallow questions, or providing poor quality additional resources. Feedback: |
Points: Points Range: 0 (0%) – 3 (10%) Student does not interact with peers (0 points) or the feedback postings and responses to questions do not contribute to the quality of interaction by offering any constructive critique, suggestions, questions, or additional resources. Feedback: |
| Writing |
Points: Points Range: 6 (20%) – 6 (20%) Postings are well organized, use scholarly tone, contain original writing and proper paraphrasing, follow APA style, contain very few or no writing and/or spelling errors, and are fully consistent with graduate level writing style. Feedback: |
Points: Points Range: 5 (16.67%) – 5 (16.67%) Postings are mostly consistent with graduate level writing style. Postings may have some small organization, scholarly tone, writing, or APA style issues, and/or may contain a few writing and spelling errors. Feedback: |
Points: Points Range: 4 (13.33%) – 4 (13.33%) Postings are somewhat below graduate level writing style. Postings may be lacking in organization, scholarly tone, APA style, and/or contain many writing and/or spelling errors, or show moderate reliance on quoting vs. original writing and paraphrasing. Feedback: |
Points: Points Range: 0 (0%) – 3 (10%) Postings are well below graduate level writing style expectations for organization, scholarly tone, APA style, and writing, or show heavy reliance on quoting |
Examine the CMS Chronic Conditions Triads: Prevalence and Medicare Spending
spreadsheet located in your Learning Resources. Familiarize yourself with CMS data
regarding chronic conditions and Medicare spending (CMS.gov), beginning with the first
tab in the spreadsheet, titled Overview, that summarizes the data sources, study
population chronic conditions, and socio-demographic variables involved in the data.
Note that the remainder of this data set presents five years of data on various triads of
chronic conditions that represent material co-morbidities studied by CMS.
With the CMS development of ACO’s (accountable care organizations) there is an
emphasis on managing certain chronic conditions to minimize hospital readmissions.
The pro-active medical management of heart failure, specifically CHF (congestive heart
failure), is a focus in trying to prevent unnecessary hospital admissions. In the medical
management of this condition and associated comorbidities such as diabetes chronic
kidney disease and hyperlipidemia, patients must manage both their fluid intake and
maintain a rigorous regime of medication such as beta-blockers. A lack of medication
compliance and or fluid management in these patients often results in repeated
emergency room visits and or hospital readmissions to stabilize physiologic parameters.
In this scenario assume you are an administrator of an integrated delivery network who
is working with CMS on developing an ACO. Using these historical, five year data on
CMS patients with comorbidities related to Heart Failure and per capita spending, you
are asked to work with an IT analyst to lead the design of the functional requirements
for the data warehouse. This business intelligence application will upload information
from your organization to CMS as a part of the ACO. Senior leaders want to understand
which HIT systems and which data within those HIT systems will be required to
contribute relevant information to CMS regarding comorbidities on heart failure patients.
They also want to understand the availability of those data and the level of quality of
those data in the organization, as they will be key to the financial parameters set within
the ACO agreement.
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