Two datasets from public data provided the Centers for Medicare & Medicaid Services, https://data.cms.gov.
cms_patient_experiencecontains some lightly cleaned data from "Hospice - Provider Data", which provides a list of hospice agencies along with some data on quality of patient care, https://data.cms.gov/provider-data/dataset/252m-zfp9.cms_patient_care"Doctors and Clinicians Quality Payment Program PY 2020 Virtual Group Public Reporting", https://data.cms.gov/provider-data/dataset/8c70-d353
Format
cms_patient_experience is a data frame with 500 observations and
five variables:
- org_pac_id,org_nm
Organisation ID and name
- measure_cd,measure_title
Measure code and title
- prf_rate
Measure performance rate
cms_patient_care is a data frame with 252 observations and
five variables:
- ccn,facility_name
Facility ID and name
- measure_abbr
Abbreviated measurement title, suitable for use as variable name
- score
Measure score
- type
Whether score refers to the rating out of 100 ("observed"), or the maximum possible value of the raw score ("denominator")
Examples
cms_patient_experience %>%
dplyr::distinct(measure_cd, measure_title)
#> # A tibble: 6 × 2
#> measure_cd measure_title
#> <chr> <chr>
#> 1 CAHPS_GRP_1 CAHPS for MIPS SSM: Getting Timely Care, Appointments, and…
#> 2 CAHPS_GRP_2 CAHPS for MIPS SSM: How Well Providers Communicate
#> 3 CAHPS_GRP_3 CAHPS for MIPS SSM: Patient's Rating of Provider
#> 4 CAHPS_GRP_5 CAHPS for MIPS SSM: Health Promotion and Education
#> 5 CAHPS_GRP_8 CAHPS for MIPS SSM: Courteous and Helpful Office Staff
#> 6 CAHPS_GRP_12 CAHPS for MIPS SSM: Stewardship of Patient Resources
cms_patient_experience %>%
pivot_wider(
id_cols = starts_with("org"),
names_from = measure_cd,
values_from = prf_rate
)
#> # A tibble: 95 × 8
#> org_pac_id org_nm CAHPS…¹ CAHPS…² CAHPS…³ CAHPS…⁴ CAHPS…⁵ CAHPS…⁶
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 0446157747 USC CARE ME… 63 87 86 57 85 24
#> 2 0446162697 ASSOCIATION… 59 85 83 63 88 22
#> 3 0547164295 BEAVER MEDI… 49 NA 75 44 73 12
#> 4 0749333730 CAPE PHYSIC… 67 84 85 65 82 24
#> 5 0840104360 ALLIANCE PH… 66 87 87 64 87 28
#> 6 0840109864 REX HOSPITA… 73 87 84 67 91 30
#> 7 0840513552 SCL HEALTH … 58 83 76 58 78 26
#> 8 0941545784 GRITMAN MED… 46 86 81 54 NA 25
#> 9 1052612785 COMMUNITY M… 65 84 80 58 87 29
#> 10 1254237779 OUR LADY OF… 61 NA NA 65 NA 17
#> # … with 85 more rows, and abbreviated variable names ¹CAHPS_GRP_1,
#> # ²CAHPS_GRP_2, ³CAHPS_GRP_3, ⁴CAHPS_GRP_5, ⁵CAHPS_GRP_8, ⁶CAHPS_GRP_12
cms_patient_care %>%
pivot_wider(
names_from = type,
values_from = score
)
#> # A tibble: 126 × 5
#> ccn facility_name measure_…¹ denom…² obser…³
#> <chr> <chr> <chr> <dbl> <dbl>
#> 1 011500 BAPTIST HOSPICE beliefs_a… 202 100
#> 2 011500 BAPTIST HOSPICE composite… 202 88.1
#> 3 011500 BAPTIST HOSPICE dyspena_t… 110 99.1
#> 4 011500 BAPTIST HOSPICE dyspnea_s… 202 100
#> 5 011500 BAPTIST HOSPICE opioid_bo… 61 100
#> 6 011500 BAPTIST HOSPICE pain_asse… 107 100
#> 7 011500 BAPTIST HOSPICE pain_scre… 202 88.6
#> 8 011500 BAPTIST HOSPICE treat_pref 202 100
#> 9 011500 BAPTIST HOSPICE visits_im… 232 96.1
#> 10 011501 SOUTHERNCARE NEW BEACON N. BIRMINGHAM beliefs_a… 525 100
#> # … with 116 more rows, and abbreviated variable names ¹measure_abbr,
#> # ²denominator, ³observed
cms_patient_care %>%
pivot_wider(
names_from = measure_abbr,
values_from = score
)
#> # A tibble: 28 × 12
#> ccn facility…¹ type belie…² compo…³ dyspe…⁴ dyspn…⁵ opioi…⁶ pain_…⁷
#> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 011500 BAPTIST H… deno… 202 202 110 202 61 107
#> 2 011500 BAPTIST H… obse… 100 88.1 99.1 100 100 100
#> 3 011501 SOUTHERNC… deno… 525 525 438 525 101 325
#> 4 011501 SOUTHERNC… obse… 100 100 100 100 100 100
#> 5 011502 COMFORT C… deno… 295 295 236 295 38 121
#> 6 011502 COMFORT C… obse… 100 99.3 99.2 100 100 100
#> 7 011503 SAAD HOSP… deno… 694 694 555 694 37 677
#> 8 011503 SAAD HOSP… obse… 99.9 96 99.6 98.3 100 99
#> 9 011505 HOSPICE F… deno… 600 600 308 600 151 308
#> 10 011505 HOSPICE F… obse… 97.8 92 97.7 99.8 98.7 92.5
#> # … with 18 more rows, 3 more variables: pain_screening <dbl>,
#> # treat_pref <dbl>, visits_imminent <dbl>, and abbreviated variable
#> # names ¹facility_name, ²beliefs_addressed, ³composite_process,
#> # ⁴dyspena_treatment, ⁵dyspnea_screening, ⁶opioid_bowel,
#> # ⁷pain_assessment
cms_patient_care %>%
pivot_wider(
names_from = c(measure_abbr, type),
values_from = score
)
#> # A tibble: 14 × 20
#> ccn facili…¹ belie…² belie…³ compo…⁴ compo…⁵ dyspe…⁶ dyspe…⁷ dyspn…⁸
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 011500 BAPTIST… 202 100 202 88.1 110 99.1 202
#> 2 011501 SOUTHER… 525 100 525 100 438 100 525
#> 3 011502 COMFORT… 295 100 295 99.3 236 99.2 295
#> 4 011503 SAAD HO… 694 99.9 694 96 555 99.6 694
#> 5 011505 HOSPICE… 600 97.8 600 92 308 97.7 600
#> 6 011506 SOUTHER… 589 100 589 99.7 477 100 589
#> 7 011508 SOUTHER… 420 100 420 99.5 347 100 420
#> 8 011510 CULLMAN… 54 100 54 90.7 27 100 54
#> 9 011511 HOSPICE… 179 100 179 99.4 123 99.2 179
#> 10 011512 SOUTHER… 396 100 396 99.5 241 100 396
#> 11 011513 SHEPHER… 335 99.1 335 87.2 154 90.9 335
#> 12 011514 ST VINC… 210 100 210 97.6 137 100 210
#> 13 011516 HOSPICE… 103 100 103 97.1 75 98.7 103
#> 14 011517 HOSPICE… 400 99.8 400 95.8 182 99.5 400
#> # … with 11 more variables: dyspnea_screening_observed <dbl>,
#> # opioid_bowel_denominator <dbl>, opioid_bowel_observed <dbl>,
#> # pain_assessment_denominator <dbl>, pain_assessment_observed <dbl>,
#> # pain_screening_denominator <dbl>, pain_screening_observed <dbl>,
#> # treat_pref_denominator <dbl>, treat_pref_observed <dbl>,
#> # visits_imminent_denominator <dbl>, visits_imminent_observed <dbl>,
#> # and abbreviated variable names ¹facility_name, …