[ROWS] 90
[FIELDS] 10
22 Summary Dashboard
Metadata
Data
# A tibble: 90 × 10
dashboard_row_number data_metrics py_2017 py_2018 py_2019 py_2020
, py_2022 , py_2023 ,
# total Tidyup
x <- resp |>
mtt(
metric = data_metrics,
type = case(
grepl("^Total Number of", metric, perl = TRUE) ~ "count",
grepl("^Total Dollar Amount of", metric, perl = TRUE) ~ "dollar",
grepl("^Total Dollar Amount Invested", metric, perl = TRUE) ~ "invest",
grepl("^Total value of interest", metric, perl = TRUE) ~ "value"),
data_metrics = NULL,
dashboard_row_number = NULL) |>
rsplit(~ type)
x$count <- mtt(
x$count,
metric = gsub("^Total Number of ", "", metric, perl = TRUE),
metric = gsub("^all ", "", metric, perl = TRUE),
type = cheapr_if_else(grepl("^Payment Records", metric, perl = TRUE), "record", "entity")) |>
rsplit( ~ type)
x$count$entity <- rnm(
x$count$entity,
`2017` = py_2017,
`2018` = py_2018,
`2019` = py_2019,
`2020` = py_2020,
`2021` = py_2021,
`2022` = py_2022,
`2023` = py_2023,
ALL = total) |>
mtt(
metric = gsub("Companies Making Payments \\(AM/GPO Making Payment\\)",
"Companies [AM/GPO] Making Payments", metric, perl = TRUE),
metric = gsub("Physician Covered Recipients with associated payment records",
"Physicians with Payment Records", metric, perl = TRUE),
metric = gsub("Non-Physician Practitioner Covered Recipients with associated payment records",
"NPPs with Payment Records", metric, perl = TRUE),
metric = gsub("Teaching Hospitals with associated payment records",
"Teaching Hospitals with Payment Records", metric, perl = TRUE)) |>
pivot(ids = "metric", names = list("year", "count")) |>
roworder(metric, -year) |>
colorder(year) |>
mtt(count = as.integer(count)) |>
as_tbl()
x$count$record <- rnm(
x$count$record,
`2017` = py_2017,
`2018` = py_2018,
`2019` = py_2019,
`2020` = py_2020,
`2021` = py_2021,
`2022` = py_2022,
`2023` = py_2023,
ALL = total
) |>
mtt(
type = case(
grepl("General Payments", metric, perl = TRUE) ~ "General",
grepl("Research Payments", metric, perl = TRUE) ~ "Research",
grepl("Ownership Payments", metric, perl = TRUE) ~ "Ownership",
.default = "All"
),
status = case(
grepl("Disputed", metric, perl = TRUE) ~ "Disputed",
grepl("Undisputed", metric, perl = TRUE) ~ "Undisputed"
),
entity = case(
grepl("- Covered Recipient", metric, perl = TRUE) ~ "Covered Recipient",
grepl("- Non-Covered Recipient", metric, perl = TRUE) ~ "Non-Covered Recipient",
grepl("- Physician or Non-Covered Recipient", metric, perl = TRUE) ~ "Physician or Non-Covered Recipient",
grepl(
"- Non-Physician Practitioner or Non-Covered Recipient",
metric,
perl = TRUE
) ~ "Non-Physician Practitioner or Non-Covered Recipient",
grepl(" to Physicians", metric, perl = TRUE) ~ "Physician",
grepl(" to Non-Physician Practitioners", metric, perl = TRUE) ~ "Non-Physician Practitioner",
grepl(" to Teaching Hospitals", metric, perl = TRUE) ~ "Teaching Hospital",
grepl(" - Non-Covered Recipient Entity", metric, perl = TRUE) ~ "Non-Covered Recipient Entity",
grepl(" - Non-Covered Recipient Individual", metric, perl = TRUE) ~ "Non-Covered Recipient Individual"
),
metric = NULL
) |>
pivot(ids = c("type", "status", "entity"),
names = list("year", "count")) |>
roworder(type, -year) |>
colorder(year, type, entity) |>
mtt(count = as.integer(count)) |>
as_tbl()
x$invest <- mtt(
x$invest,
metric = gsub("^Total Dollar Amount Invested of all Payment Records ", "", metric, perl = TRUE),
metric = gsub("^-\\s", "", metric, perl = TRUE))
x$value <- mtt(
x$value,
metric = gsub("^Total value of interest of all Payment Records ", "", metric, perl = TRUE),
metric = gsub("^-\\s", "", metric, perl = TRUE))
x$dollar <- mtt(
x$dollar,
metric = gsub("^Total Dollar Amount of ", "", metric, perl = TRUE),
metric = gsub("^all ", "", metric, perl = TRUE))
x$count
$count$entity
# A tibble: 32 × 3
year metric count
Overview
cheapr::overview(x$count$entity)obs: 32
cols: 3
----- Numeric -----
col n_missng p_complt n_unique mean p0 p25 p50 p75
1 count 0 1 29 203911 0 1224 1788 433972
p100 iqr sd hist
1 1118817 432747 300335 ▇▂▃▁▁
----- Categorical -----
col n_missng p_complt n_unique n_levels
1 year 0 1 8 8
2 metric 0 1 4 NA
min
1 2017
2 Companies [AM/GPO] Making Payments
max
1 ALL
2 Teaching Hospitals with Payment Records
cheapr::overview(x$count$record)obs: 320
cols: 5
----- Numeric -----
col n_missng p_complt n_unique mean p0 p25 p50 p75
1 count 0 1 238 3189547 0 178 33321 849287
p100 iqr sd hist
1 84035057 849109 10387247 ▇▁▁▁▁
----- Categorical -----
col n_missng p_complt n_unique n_levels min
1 year 0 1 8 8 2017
2 type 0 1 4 NA All
3 entity 80 0.75 7 NA Covered Recipient
4 status 160 0.5 2 NA Disputed
max
1 ALL
2 Research
3 Teaching Hospital
4 Undisputed
cheapr::overview(x$dollar)obs: 35
cols: 9
----- Categorical -----
col n_missng p_complt n_unique n_levels min
1 py_2017 0 1 28 NA 0.00
2 py_2018 0 1 28 NA 0.00
3 py_2019 0 1 28 NA 0.00
4 py_2020 0 1 26 NA 0.00
5 py_2021 0 1 34 NA 0.00
6 py_2022 0 1 34 NA 0.00
7 py_2023 0 1 34 NA 0.00
8 total 0 1 34 NA 0.00
9 metric 0 1 35 NA Payment Records
max
1 9983443884.20
2 851039610.78
3 99869144.61
4 8358438.80
5 976017659.44
6 884.79
7 913407.55
8 72430213436.63
9 Payment Records to Teaching Hospitals - Research Payments - Undisputed
cheapr::overview(x$value)obs: 6
cols: 9
----- Categorical -----
col n_missng p_complt n_unique n_levels min
1 py_2017 0 1 3 NA 1045340199.31
2 py_2018 0 1 3 NA 1649109621.92
3 py_2019 0 1 2 NA 0.00
4 py_2020 0 1 2 NA 0.00
5 py_2021 0 1 2 NA 0.00
6 py_2022 0 1 3 NA 1149781801.49
7 py_2023 0 1 3 NA 1339619652.59
8 total 0 1 3 NA 1339619652.59
9 metric 0 1 6 NA Ownership Payments
max
1 27902592.00
2 265936.00
3 1621023068.27
4 1383815859.42
5 1548506879.01
6 99992.65
7 160592.65
8 160592.65
9 to Physicians - Ownership Payments - Undisputed
cheapr::overview(x$invest)obs: 5
cols: 9
----- Categorical -----
col n_missng p_complt n_unique n_levels min
1 py_2017 0 1 3 NA 23232.00
2 py_2018 0 1 3 NA 542359793.14
3 py_2019 0 1 2 NA 0.00
4 py_2020 0 1 2 NA 0.00
5 py_2021 0 1 2 NA 0.00
6 py_2022 0 1 2 NA 0.00
7 py_2023 0 1 3 NA 11600.00
8 total 0 1 3 NA 2679961689.06
9 metric 0 1 5 NA Ownership Payments
max
1 268224163.55
2 64837.50
3 526403105.28
4 420228142.68
5 416271283.34
6 287661921.26
7 218848111.81
8 99669.50
9 to Physicians - Ownership Payments - Disputed