Introduction
The carecompare package is an R toolkit
built to enable US hospitals and health systems to access, explore, and
analyze performance in quality
measures and payment programs from the Centers for Medicare and Medicaid
Services (CMS).
Load
require(carecompare)
#> Loading required package: carecompareAccessing Data
Generic access to the CMS Provider Data Catalog.
# Extract the topics
topics <- pdc_topics()
topics
#> [1] "Helpful Contacts"
#> [2] "Dialysis facilities"
#> [3] "Home health services"
#> [4] "Hospice care"
#> [5] "Hospitals"
#> [6] "Inpatient rehabilitation facilities"
#> [7] "Long-term care hospitals"
#> [8] "Nursing homes including rehab services"
#> [9] "Physician office visit costs"
#> [10] "Doctors and clinicians"
#> [11] "Supplier directory"
#> [12] "Medicare plan finder"
# Examine the metadata for a given topic
hospital_data <- pdc_datasets("Hospitals")
hospital_data
#> # A tibble: 67 × 7
#> datasetid topic title description issued modified downloadurl
#> <chr> <chr> <chr> <chr> <date> <date> <chr>
#> 1 4jcv-atw7 Hospitals Ambulatory… A list of … 2022-01-07 2022-01-07 https://da…
#> 2 axe7-s95e Hospitals Ambulatory… This file … 2022-01-07 2022-01-07 https://da…
#> 3 wue8-3vwe Hospitals Ambulatory… This file … 2022-01-07 2022-01-07 https://da…
#> 4 muwa-iene Hospitals CMS Medica… This data … 2020-12-10 2022-01-07 https://da…
#> 5 ynj2-r877 Hospitals Complicati… Complicati… 2020-12-10 2022-01-07 https://da…
#> 6 qqw3-t4ie Hospitals Complicati… Complicati… 2020-12-10 2022-01-07 https://da…
#> 7 bs2r-24vh Hospitals Complicati… Complicati… 2020-12-10 2022-01-07 https://da…
#> 8 tqkv-mgxq Hospitals Comprehens… Comprehens… 2020-12-10 2021-06-15 https://da…
#> 9 bzsr-4my4 Hospitals Data Updat… Lists the … 2020-12-10 2022-03-21 https://da…
#> 10 y9us-9xdf Hospitals Footnote C… The footno… 2020-12-10 2021-09-22 https://da…
#> # … with 57 more rows
# Search for a dataset
hospital_data %>%
dplyr::filter(
title %>%
stringr::str_detect(
pattern = "(?i)readmission"
)
) %>%
knitr::kable(format = "pandoc")| datasetid | topic | title | description | issued | modified | downloadurl |
|---|---|---|---|---|---|---|
| 9n3s-kdb3 | Hospitals | Hospital Readmissions Reduction Program | In October 2012, CMS began reducing Medicare payments for subsection(d) hospitals with excess readmissions under the Hospital Readmissions Reduction Program (HRRP). Excess readmissions are measured by a ratio, calculated by dividing a hospital’s predicted rate of readmissions for heart attack (AMI), heart failure (HF), pneumonia, chronic obstructive pulmonary disease (COPD), hip/knee replacement (THA/TKA), and coronary artery bypass graft surgery (CABG) by the expected rate of readmissions, based on an average hospital with similar patients. | 2020-12-10 | 2022-01-19 | https://data.cms.gov/provider-data/sites/default/files/resources/6862887588c0e2d720f0c821f6ed8e76_1642665920/FY_2022_Hospital_Readmissions_Reduction_Program_Hospital.csv |
# Import the data for a given dataset
pdc_read(
datasetid = "9n3s-kdb3"
)
#> Rows: 19020 Columns: 12
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr (11): Facility Name, Facility ID, State, Measure Name, Number of Dischar...
#> dbl (1): Footnote
#>
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> # A tibble: 19,020 × 12
#> `Facility Name` `Facility ID` State `Measure Name` `Number of Dis…` Footnote
#> <chr> <chr> <chr> <chr> <chr> <dbl>
#> 1 SOUTHEAST HEALT… 010001 AL READM-30-HIP-… 165 NA
#> 2 SOUTHEAST HEALT… 010001 AL READM-30-CABG… 193 NA
#> 3 SOUTHEAST HEALT… 010001 AL READM-30-AMI-… 424 NA
#> 4 SOUTHEAST HEALT… 010001 AL READM-30-HF-H… 905 NA
#> 5 SOUTHEAST HEALT… 010001 AL READM-30-COPD… 310 NA
#> 6 SOUTHEAST HEALT… 010001 AL READM-30-PN-H… 504 NA
#> 7 MARSHALL MEDICA… 010005 AL READM-30-COPD… 378 NA
#> 8 MARSHALL MEDICA… 010005 AL READM-30-AMI-… N/A NA
#> 9 MARSHALL MEDICA… 010005 AL READM-30-HF-H… 223 NA
#> 10 MARSHALL MEDICA… 010005 AL READM-30-CABG… N/A 5
#> # … with 19,010 more rows, and 6 more variables:
#> # `Excess Readmission Ratio` <chr>, `Predicted Readmission Rate` <chr>,
#> # `Expected Readmission Rate` <chr>, `Number of Readmissions` <chr>,
#> # `Start Date` <chr>, `End Date` <chr>Formatted datasets
hospitals
#> # A tibble: 5,306 × 12
#> HospitalID Name Address City State Zip County Type Ownership FullAddress
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 010001 SOUT… 1108 R… DOTH… AL 36301 HOUST… Acut… Governme… 1108 ROSS …
#> 2 010005 MARS… 2505 U… BOAZ AL 35957 MARSH… Acut… Governme… 2505 U S H…
#> 3 010006 NORT… 1701 V… FLOR… AL 35630 LAUDE… Acut… Propriet… 1701 VETER…
#> 4 010007 MIZE… 702 N … OPP AL 36467 COVIN… Acut… Voluntar… 702 N MAIN…
#> 5 010008 CREN… 101 HO… LUVE… AL 36049 CRENS… Acut… Propriet… 101 HOSPIT…
#> 6 010011 ST. … 50 MED… BIRM… AL 35235 JEFFE… Acut… Voluntar… 50 MEDICAL…
#> 7 010012 DEKA… 200 ME… FORT… AL 35968 DE KA… Acut… Propriet… 200 MED CE…
#> 8 010016 SHEL… 1000 F… ALAB… AL 35007 SHELBY Acut… Voluntar… 1000 FIRST…
#> 9 010018 CALL… 1720 U… BIRM… AL 35233 JEFFE… Acut… Voluntar… 1720 UNIVE…
#> 10 010019 HELE… 1300 S… SHEF… AL 35660 COLBE… Acut… Governme… 1300 SOUTH…
#> # … with 5,296 more rows, and 2 more variables: Latitude <dbl>, Longitude <dbl>
cms_payments()
#> # A tibble: 188,806 × 6
#> HospitalID MSDRGCode Discharges AverageCoveredCharges AverageTotalPayment
#> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 010001 003 14 326515. 62788.
#> 2 010001 023 55 140875. 29767.
#> 3 010001 024 20 109788. 22780.
#> 4 010001 025 23 124579. 24107.
#> 5 010001 027 16 75029. 18216.
#> 6 010001 038 20 73875. 9721.
#> 7 010001 039 45 47281. 6985.
#> 8 010001 054 11 34797. 7782
#> 9 010001 056 15 66157. 11793.
#> 10 010001 057 38 27677. 7393.
#> # … with 188,796 more rows, and 1 more variable: AverageMedicarePayment <dbl>
cms_msdrg()
#> Rows: 767 Columns: 9
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: "\t"
#> chr (6): MS-DRG, FY 2022 Final Post-Acute DRG, FY 2022 Final Special Pay DRG...
#> dbl (3): Weights, Geometric mean LOS, Arithmetic mean LOS
#>
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
#> # A tibble: 767 × 7
#> MSDRGCode MSDRGDescription MSDRGType MajorDiagnostic… Weight GMLOS AMLOS
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 001 HEART TRANSPLANT OR … SURG PRE 28.9 30.1 39.1
#> 2 002 HEART TRANSPLANT OR … SURG PRE 15.0 15.4 18.2
#> 3 003 ECMO OR TRACHEOSTOMY… SURG PRE 19.1 22.4 30.2
#> 4 004 TRACHEOSTOMY WITH MV… SURG PRE 11.9 20 24.6
#> 5 005 LIVER TRANSPLANT WIT… SURG PRE 10.2 14.4 19.4
#> 6 006 LIVER TRANSPLANT WIT… SURG PRE 4.70 7.5 8.1
#> 7 007 LUNG TRANSPLANT SURG PRE 11.6 17.4 20.8
#> 8 008 SIMULTANEOUS PANCREA… SURG PRE 5.43 9 10.2
#> 9 010 PANCREAS TRANSPLANT SURG PRE 3.62 8 9.1
#> 10 011 TRACHEOSTOMY FOR FAC… SURG PRE 5.02 10.9 13.8
#> # … with 757 more rows