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This R package calculates CMS-HCC risk scores as an alternative to using SAS

Home Page: https://www.ValidateHealth.com

R 100.00%

cmshcc's Introduction

Based on presentation from: http://ase.uva.nl/binaries/content/assets/subsites/amsterdam-school-of-economics/r-in-insurance/webster-risk-adjustment-in-r.pdf

  1. install.packages("devtools") if not already installed
  2. install cmshcc package using: devtools::install_github("healthactuary/cmshcc")
  3. load the cmshcc package using library(cmshcc)
  4. generate a sample PERSON data frame or use your own with same format: PERSON <- generate_PERSON()
  5. load the CMS-HCC diagnosis code to HCC mapping: cmshcc_map <- load_cmshcc_map()
  6. create a diagnosis data frame using mapping or use your own data with same format: DIAG <- generate_DIAG(cmshcc_map)
  7. Evaluate the 2017 V22 CMS-HCC models: Community_NonDual_Aged = evaluate_v22_2017(PERSON, DIAG, "Community_NonDual_Aged") Community_NonDual_Disabled = evaluate_v22_2017(PERSON, DIAG, "Community_NonDual_Disabled") Community_FBDual_Aged = evaluate_v22_2017(PERSON, DIAG, "Community_FBDual_Aged") Community_FBDual_Disabled = evaluate_v22_2017(PERSON, DIAG, "Community_FBDual_Disabled") Community_PBDual_Aged = evaluate_v22_2017(PERSON, DIAG, "Community_PBDual_Aged") Community_PBDual_Disabled = evaluate_v22_2017(PERSON, DIAG, "Community_PBDual_Disabled") Institutional = evaluate_v22_2017(PERSON, DIAG, "Institutional")

Bind together results in one dataframe if preferable:

results <- cbind(Community_NonDual_Aged, Community_NonDual_Disabled, Community_FBDual_Aged, Community_FBDual_Disabled, Community_PBDual_Aged, Community_PBDual_Disabled, Institutional)

cmshcc's People

Contributors

healthactuary avatar npritzl avatar riazhedayati avatar

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