knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) options(rmarkdown.html_vignette.check_title = FALSE)
This data structure is used in medicare 100 data standardization and analytic files creation. It's import to follow the data folder structure so the code can read and write data from valid paths.
Medicare 100 1. Full data 1.1. Selected vars csv 1.1.1. Denom_MBSF 1.1.2. MEDPAR 1.1.3. Carrier 1.2. Std 1.2.1. Fac_clm 1.2.2. Fac_clm_code 1.2.3. Fac_clm_hosp: only inpatient medpar claims 1.2.3.1 Fac_clm 1.2.3.2 Fac_clm_code 1.2.4. Prof_clm 1.2.5. Prof_clm_code 1.2.6. Membership 1.2.7. Professional 1.2.8. Original 5 1.3. Analytic 1.3.1. Fac_clm 1.3.2. Fac_clm_code 1.3.3. Prof_clm 1.3.4. Prof_clm_code 1.3.5. Membership 1.3.6. Professional 2. Sample data (same as full) 3. Analysis ready data 4. Raw sas 4.1. Sas code 5. Projects 6. Archived projects 7. Dump (to be cleaned regularly) Medicare 20 – same structure
The code we used to create working paths are below
medicareR::mk_data_dir_path(data_root = "sample", # "sample", "full_data" george_file = medicareR::find_maize_folder() # Brian George folder path on maize, eg. "/Volumes/George_Surgeon_Projects")) ) # for more input paths control, refer to ?medicareR::mk_data_dir_path
The code above will assisgn all paths needed as below in your environment.
# Note: you care also manually assign/overwirte all the values in the wd list as below wd$george_file = "/Volumes/George_Surgeon_Projects" wd$input_data = "/Volumes/George_Surgeon_Projects/standardized_medicare_data_using_R/input/" wd$src_data_root = "/Volumes/George_Surgeon_Projects/original_medicare_selected_vars/data/sample/" wd$std_data_root = "/Volumes/George_Surgeon_Projects/standardized_medicare_data_using_R/std/sample/" wd$std_analytic_root = "/Volumes/George_Surgeon_Projects/standardized_medicare_data_using_R/analytic/sample/"
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