Quality Payment Program
Examples
qpp_metrics <- quality_metrics(year = 2018:2025)
qpp_eligible <- quality_eligibility(
year = 2018:2024,
npi = c(1144544834, 1043477615, 1932365699, 1225701881))
qpp_experience <- build(
endpoint("qppe"),
query(npi = any_of(1144544834, 1043477615, 1932365699, 1225701881)))
#> Found 22 ▶ Total 5.7 M ▶ Pages 7
qpp_exp <- qpp_experience@string |>
providertwo:::gremove("/stats") |>
providertwo:::greplace("size=1", "size=5000") |>
providertwo:::map_perform_parallel() |>
providertwo:::set_clean(qpp_experience@year) |>
purrr::list_rbind(names_to = "prog_year") |>
providertwo:::map_na_if() |>
fastplyr::as_tbl()
list(
experience = providertwo:::set_clean(qpp_exp, names(qpp_exp)),
eligibility = qpp_eligible,
metrics = qpp_metrics)
#> $experience
#> # A tibble: 22 × 230
#> prog_year provider_key practice_state_or_us_te…¹ practice_size clinician_type
#> <chr> <chr> <chr> <chr> <chr>
#> 1 2023 000131692 MD 1572 Doctor of Med…
#> 2 2023 000475122 GA 14 Physician Ass…
#> 3 2022 000021992 PA 1518 Doctor of Med…
#> 4 2022 000212248 GA 11 Physician Ass…
#> 5 2021 000066744 PA 1940 NA
#> 6 2021 000183263 GA 11 NA
#> 7 2021 000493218 CO 3 NA
#> 8 2020 000402699 PA 1440 NA
#> 9 2020 000000310 GA 13 NA
#> 10 2020 000434064 CO 2 NA
#> # ℹ 12 more rows
#> # ℹ abbreviated name: ¹practice_state_or_us_territory
#> # ℹ 225 more variables: clinician_specialty <chr>, years_in_medicare <chr>,
#> # npi <chr>, non_reporting <chr>, reporting_option <chr>,
#> # participation_option <chr>, mips_value_pathway_id <chr>,
#> # mips_value_pathway_title <chr>, medicare_patients <chr>,
#> # allowed_charges <chr>, services <chr>, opted_into_mips <chr>, …
#>
#> $eligibility
#> # A tibble: 28 × 16
#> prog_year npi entity last_name first_name middle_name specialty
#> <int> <chr> <int> <chr> <chr> <chr> <chr>
#> 1 2024 1043477615 1 HUSSAIN SARAH K Clinical/Cardia…
#> 2 2023 1043477615 1 HUSSAIN SARAH K Clinical/Cardia…
#> 3 2022 1043477615 1 HUSSAIN SARAH K Clinical/Cardia…
#> 4 2021 1043477615 1 HUSSAIN SARAH K Clinical/Cardia…
#> 5 2020 1043477615 1 HUSSAIN SARAH K Clinical/Cardia…
#> 6 2019 1043477615 1 HUSSAIN SARAH K Clinical/Cardia…
#> 7 2018 1043477615 1 HUSSAIN SARAH K Clinical/Cardia…
#> 8 2024 1144544834 1 MANLEY EMILY T Physician Assis…
#> 9 2023 1144544834 1 MANLEY EMILY T Physician Assis…
#> 10 2022 1144544834 1 MANLEY EMILY T Physician Assis…
#> # ℹ 18 more rows
#> # ℹ 9 more variables: date_enrolled <date>, is_new <lgl>, is_maqi <lgl>,
#> # yearsInMedicare <int>, pecosEnrollmentDate <int>, ORGS <list>,
#> # qpStatus <lgl>, amsMipsEligibleClinician <lgl>, qpScoreType <lgl>
#>
#> $metrics
#> # A tibble: 32 × 4
#> year category metric mean
#> <int> <fct> <fct> <dbl>
#> 1 2018 Group Dual Eligibility Ratio 0.230
#> 2 2019 Group Dual Eligibility Ratio 0.216
#> 3 2020 Group Dual Eligibility Ratio 0.210
#> 4 2021 Group Dual Eligibility Ratio 0.499
#> 5 2022 Group Dual Eligibility Ratio 0.499
#> 6 2023 Group Dual Eligibility Ratio 0.499
#> 7 2024 Group Dual Eligibility Ratio 0.499
#> 8 2025 Group Dual Eligibility Ratio 0.499
#> 9 2018 Individual Dual Eligibility Ratio 0.288
#> 10 2019 Individual Dual Eligibility Ratio 0.269
#> # ℹ 22 more rows
#>