Community driven, value based primary care for Medicare beneficiaries in Gainesville, FL

Click below for proposal presentation

https://www.youtube.com/watch?v=lje5HQw7pR4

This repository contains data, visuals, and documents to evaluate Opportunities for a Community driven, value based primary care clinic for Medicare patients using Direct Contracting payment models.

ffs_al.csv is a ready to use table with information related to the request.

ZIP = 5 digit Zip code in Alachua County, FL
POP_OVER_65 = Total population over 65 in Zip Code
POP_TOTAL = Total population in Zip Code
TOTAL_DAYS_OF_CARE = Total bed days from Medicare Part A/B beneficaries from all hopsitals for residents within that Zip Code
TOTAL_CHARGES = Total raw charges from Medicare Part A/B beneficaries from all hopsitals for residents within that Zip Code
TOTAL_CASES = Total hospital visits from Medicare Part A/B beneficaries from all hopsitals for residents within that Zip Code
DAYS_per 65 = TOTAL_DAYS_OF_CARE / POP_OVER_65
CHARGES_per 65 = TOTAL_CHARGES / POP_OVER_65
VISTIS_per 65 = TOTAL_CASES/ POP_OVER_65

• Population data was accessed from the 2018 American Community Survey. https://data.census.gov/cedsci/?g=0100000US&tid=ACSDP1Y2018.DP05
  
• Hospitalization data was accessed from the 2020 CMS Hospital Compare, Health Services Area File. https://data.cms.gov/Medicare-Inpatient/Hospital-Service-Area-File-2018/sgw2-6vb4
  
• The open source Healthy Neighborhoods Repository was used for this project. For Raw data files, documentation, and code visit https://github.com/andrewcistola/healthy-neighborhoods
  

ffs_al.csv Ready to use file
Income Statement.xlsx Draft of income statement for possible clinic
_data Data used for the request
_code Code used for the request
_fig Figures made in the request
LICENSE Generic MIT licenses for open source projects from DrewC!
.gitattributes File extensions marked for GH large file storage
environment.yml Conda environment with dependencies for use in development projects

The repository uses the following file organization.

_v#.# dependency files deployed for that specific release or version
_data staged data files related to the project
_fig graphs, images, and maps related to the project
_archive old files no longer used
_raw raw data files, documentation, and code used for staging data
project Files related to specifc project
README Description, directory, notes

topic_prefix_suffix.ext

Topics are assigned based on content and listed in the directory README

alpha_ First draft of script, continuting with greek alphabet omega_ Final draft of script `

_code Development code script for working in an IDE
_book Jupyter notebook
_stage Data files that have been modified from raw source
_2020-01-01 Text scripts with results output with date it was run
_map 2D geographic display
_graph 2D chart or graph representing numeric data

Code scripts use the following style:

Whenever possible code scripts follow PEP-8 standards.

Python and R code scripts use the following elective options:
= for variable defintions (no <-)
'' for all character strings or arguments (no "")
A single space is provided between each element ex. columns = 'COlA'

Python and R code scripts use the following variable naming conventions:

data frames: df_xx
list: l_xx
arrays: a_xx
feature tables: df_X
target tables: df_Y

While the author (Andrew Cistola) is a Florida DOH employee and a University of Florida PhD student, these are NOT official publications by the Florida DOH, the University of Florida, or any other agency. No information is included in this repository that is not available to any member of the public. All information in this repository is available for public review and dissemination but is not to be used for making medical decisions. All code and data inside this repository is available for open source use per the terms of the included license.

This repository is part of the larger allocativ project dedicated to prodiving analytical tools that are 'open source for public health.' Learn more at https://allocativ.com.