This project aims to examine the association between exposure to the Guided Care Model within primary care and the incidence of unplanned hospitalizations in 2009, among Illinois seniors (65+) with Multiple Chronic Conditions (MCC) who Medicare covers. Several primary care providers in Illinois have implemented the Guided Care Model, but not as part of a designed experiment, so this is a (fictional) observational study.
Overview: You are to conduct a thorough analysis, including descriptive analyses, evaluation of confounding and effect modification, and building a “final” multivariable model.
You do not have to become an expert in the content area for the analysis, but you can use the following resources (all posted to Blackboard) for background information:
• Quality measure documentation for unplanned hospitalizations (from Homework #2)
In Part 1, you will conduct the analysis and produce , complete 4 tables mentioned in Appendix 1 and a brief narrative write-up of your methods and results.
In Part 2, you will write an abstract as for a scientific conference, presenting your analysis and results.
Data: The following variables from the DE-SynPUF Medicare Claims Summary File and additional data sources should be used for this analysis. Data and codebooks can be found in Blackboard under “Datasets/Analysis Project Data Spring 2023”.
Main Outcome Variable: Any unplanned hospitalization in 2009 (yes/no) - UnplannedHosps2009.sas7bdat
Main Exposure Variable: Exposure to Guided Care Model in Primary Care (yes/no) - GuidedCare.sas7bdat
Effect Modifier: Diabetes to examine as an effect modifier.
Covariates: age, race/ethnicity, sex, and 2 additional covariates of your choice*
Inclusion Criteria: Illinois resident, Medicare beneficiary, age 65+, has MCC (according to definition from Homework #1), continuous enrollment in Medicare for 11 months in 2008, did not die by the end of 2009 (Note: these inclusion criteria have already been applied to the beneficiary summary file except for restriction to MCC)
Note: You have 3 conceptual confounders: age, race/ethnicity, and sex, which should be retained in your final model
****Document form Homework 1
1. Create a variable for multiple chronic conditions (yes=1 no=0), defined as two or more of the following conditions (with variable names in parentheses following each):
a. Acute myocardial infarction (SP_ISCHMCHT)
b. Alzheimer’s disease and related disorders or senile dementia (SP_ALZHDMTA)
c. Chronic kidney disease (SP_CHRNKIDN)
d. Chronic obstructive pulmonary disease (SP_COPD)
e. Depression (SP_DEPRESSN)
f. Heart failure (SP_CHF)
g. Stroke and transient ischemic attack (SP_STRKETIA)
SAS code excerpt should be shown, something like this:
/*Code MCC variables - sum of CCs and dichotomous*/
array cc {*} sp_ischmcht SP_ALZHDMTA SP_CHRNKIDN SP_COPD SP_DEPRESSN sp_strketia sp_chf;
/*recode values of 2 to 0*/
do i=1 to dim(cc);
if cc{i}=2 then cc{i}=0;
end;
NumCC=sum(sp_ischmcht, SP_ALZHDMTA, SP_CHRNKIDN, SP_COPD, SP_DEPRESSN, sp_strketia, sp_chf);
if NumCC ge 2 then MCC=1;
else if NumCC in (0,1) then MCC=0; ************
Part 1: Use the tables below (Appendix 1) as a template for your analysis write-up. The tables should be accompanied by a brief write-up of the methods and findings for each step of the analysis/table.
Your methods write-up should contain the following sections/content: data source, inclusion/exclusion criteria, data management and variable creation/definitions, and analytic methods. Analytic methods should describe/justify your choice of model type and model building strategy. The methods narrative write-up should be no more than one page double-spaced.
The results write-up up should be organized by table. For each table, you should state the purpose/aim/research question and analytic method(s) and then describe the key (not all) results in a few sentences. You should include quantitative results – effect estimates and confidence intervals – where appropriate. Key results should be those that address the research question and/or inform subsequent model building decisions. In your write-up for Tables 1 and 2, you should include a brief description of what each tables tells you about what to expect in a final model. For Table 3, include a brief description of your logic in arriving at your final model. Be careful to use precise epidemiologic language throughout your write-up. The results write up should be no more than two pages double-spaced.
Part 2: Please prepare a scientific abstract summarizing your research question, analysis and findings. Abstracts should be concise and formatted as for a scientific journal. Abstracts should be structured and include the following section headings: Background, Objective, Methods, Results, Conclusions. Abstracts should be limited to 300 words.
CS 340 Milestone One Guidelines and Rubric Overview: For this assignment, you will implement the fundamental operations of create, read, update,
Retail Transaction Programming Project Project Requirements: Develop a program to emulate a purchase transaction at a retail store. This
7COM1028 Secure Systems Programming Referral Coursework: Secure
Create a GUI program that:Accepts the following from a user:Item NameItem QuantityItem PriceAllows the user to create a file to store the sales receip
CS 340 Final Project Guidelines and Rubric Overview The final project will encompass developing a web service using a software stack and impleme
