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Published
20 hours ago •
andrewallenbruce
andrewallenbruce
Feature: CCN validator
Code
short <- dplyr::tibble(
range = vctrs::vec_c(paste0("000", as.character(1:9)),
paste0("00", as.character(10:99)),
paste0("0", as.character(100:879))),
type = "Short-term (General and Specialty) Hospital"
)
ord <- dplyr::tibble(
range = paste0("0", as.character(880:899)),
type = "Hospital participating in ORD demonstration project"
)
fqhc <- dplyr::tibble(
range = vctrs::vec_c(as.character(1000:1199), as.character(1800:1989)),
type = "Federally Qualified Health Center"
)
maf <- dplyr::tibble(
range = as.character(1225:1299),
type = "Medical Assistance Facility"
)
cah <- dplyr::tibble(
range = as.character(1300:1399),
type = "Critical Access Hospital"
)
cmhc <- dplyr::tibble(
range = as.character(1400:1499),
type = "Community Mental Health Center"
)
hospice <- dplyr::tibble(
range = as.character(1500:1799),
type = "Hospice"
)
rnmhci <- dplyr::tibble(
range = as.character(1990:1999),
type = "Religious Non-medical Health Care Institution (formerly Christian Science Sanatoria Hospital Services)"
)
ltch <- dplyr::tibble(
range = as.character(2000:2299),
type = "Long-Term Care Hospital"
)
hbrdf <- dplyr::tibble(
range = as.character(2300:2499),
type = "Hospital-based Renal Dialysis Facility"
)
irdf <- dplyr::tibble(
range = as.character(2500:2899),
type = "Independent Renal Dialysis Facility"
)
isprdf <- dplyr::tibble(
range = as.character(2900:2999),
type = "Independent Special Purpose Renal Dialysis Facility"
)
rehosp <- dplyr::tibble(
range = as.character(3025:3099),
type = "Rehabilitation Hospital"
)
hha <- dplyr::tibble(
range = vctrs::vec_c(as.character(3100:3199),
as.character(7000:8499),
as.character(9000:9799)),
type = "Home Health Agency"
)
child <- dplyr::tibble(
range = as.character(3300:3399),
type = "Children's Hospital"
)
rhcp <- dplyr::tibble(
range = vctrs::vec_c(as.character(3400:3499),
as.character(3975:3999),
as.character(8500:8899)),
type = "Rural Health Clinic (Provider-based)"
)
rhcf <- dplyr::tibble(
range = vctrs::vec_c(as.character(3800:3974),
as.character(8900:8999)),
type = "Rural Health Clinic (Free-standing)"
)
hbsrdf <- dplyr::tibble(
range = as.character(3500:3699),
type = "Hospital-based Satellite Renal Dialysis Facility"
)
hbsprdf <- dplyr::tibble(
range = as.character(3700:3799),
type = "Hospital-based Special Purpose Renal Dialysis Facility"
)
psych <- dplyr::tibble(
range = as.character(4000:4499),
type = "Psychiatric Hospital"
)
corf <- dplyr::tibble(
range = vctrs::vec_c(as.character(3200:3299),
as.character(4500:4599),
as.character(4800:4899)),
type = "Comprehensive Outpatient Rehabilitation Facility"
)
cmhc2 <- dplyr::tibble(
range = vctrs::vec_c(as.character(4600:4799),
as.character(4900:4999)),
type = "Community Mental Health Center"
)
snf <- dplyr::tibble(
range = as.character(5000:6499),
type = "Skilled Nursing Facility"
)
outpts <- dplyr::tibble(
range = as.character(6500:6989),
type = "Outpatient Physical Therapy Services"
)
tplant <- dplyr::tibble(
range = as.character(9800:9899),
type = "Transplant Center"
)
numrsrv <- dplyr::tibble(
range = as.character(6990:6999),
type = "Number Reserved (formerly Christian Science Sanatoria Skilled Nursing Services)"
)
futrsrv <- dplyr::tibble(
range = as.character(9900:9999),
type = "Reserved for Future Use"
)
mhcmc <- dplyr::tibble(
range = paste0("0", as.character(900:999)),
type = "Multiple Hospital Component in a Medical Complex (Number Retired)"
)
adhret <- dplyr::tibble(
range = as.character(1200:1224),
type = "Alcohol/Drug Hospital (Number Retired)"
)
tubret <- dplyr::tibble(
range = as.character(3000:3024),
type = "Tuberculosis Hospital (Number Retired)"
)
facility_ranges <- dplyr::bind_rows(short, ord, fqhc, maf, cah, cmhc, hospice, rnmhci, ltch, hbrdf,
irdf, isprdf, rehosp, hha, child, rhcp, rhcf, hbsrdf, hbsprdf,
psych, corf, cmhc2, snf, outpts, tplant, numrsrv, futrsrv, mhcmc,
adhret, tubret)
facility_ranges |> count(type, sort = TRUE)
#> # A tibble: 29 × 2
#> type n
#> <chr> <int>
#> 1 Home Health Agency 2400
#> 2 Skilled Nursing Facility 1500
#> 3 Short-term (General and Specialty) Hospital 879
#> 4 Rural Health Clinic (Provider-based) 525
#> 5 Psychiatric Hospital 500
#> 6 Outpatient Physical Therapy Services 490
#> 7 Community Mental Health Center 400
#> 8 Independent Renal Dialysis Facility 400
#> 9 Federally Qualified Health Center 390
#> 10 Comprehensive Outpatient Rehabilitation Facility 300
#> 11 Hospice 300
#> 12 Long-Term Care Hospital 300
#> 13 Rural Health Clinic (Free-standing) 275
#> 14 Hospital-based Renal Dialysis Facility 200
#> 15 Hospital-based Satellite Renal Dialysis Facility 200
#> 16 Children's Hospital 100
#> 17 Critical Access Hospital 100
#> 18 Hospital-based Special Purpose Renal Dialysis Facility 100
#> 19 Independent Special Purpose Renal Dialysis Facility 100
#> 20 Multiple Hospital Component in a Medical Complex (Number Retired) 100
#> 21 Reserved for Future Use 100
#> 22 Transplant Center 100
#> 23 Medical Assistance Facility 75
#> 24 Rehabilitation Hospital 75
#> 25 Alcohol/Drug Hospital (Number Retired) 25
#> 26 Tuberculosis Hospital (Number Retired) 25
#> 27 Hospital participating in ORD demonstration project 20
#> 28 Number Reserved (formerly Christian Science Sanatoria Skilled Nursing … 10
#> 29 Religious Non-medical Health Care Institution (formerly Christian Scie… 10
Created on 2023-11-29 with reprex v2.0.2
Using {ivs}:
Code
short <- dplyr::tibble(
type = "Short-term (General and Specialty) Hospital",
start = 1L,
end = 880L
)
ord <- dplyr::tibble(
type = "Hospital participating in ORD demonstration project",
start = 880L,
end = 900L
)
fqhc <- dplyr::tibble(
type = c("Federally Qualified Health Center", "Federally Qualified Health Center"),
start = c(1000L, 1800L),
end = c(1200L, 1990L),
)
maf <- dplyr::tibble(
type = "Medical Assistance Facility",
start = 1225L,
end = 1300L
)
cah <- dplyr::tibble(
type = "Critical Access Hospital",
start = 1300L,
end = 1400L
)
cmhc <- dplyr::tibble(
type = c("Community Mental Health Center",
"Community Mental Health Center",
"Community Mental Health Center"),
start = c(1400L, 4600L, 4900L),
end = c(1500L, 4800L, 5000L)
)
hospice <- dplyr::tibble(
type = "Hospice",
start = 1500L,
end = 1800L
)
rnmhci <- dplyr::tibble(
type = "Religious Non-medical Health Care Institution (formerly Christian Science Sanatoria Hospital Services)",
start = 1990L,
end = 2000L
)
ltch <- dplyr::tibble(
type = "Long-Term Care Hospital",
start = 2000L,
end = 2300L
)
hbrdf <- dplyr::tibble(
type = "Hospital-based Renal Dialysis Facility",
start = 2300L,
end = 2500L
)
irdf <- dplyr::tibble(
type = "Independent Renal Dialysis Facility",
start = 2500L,
end = 2900L
)
isprdf <- dplyr::tibble(
type = "Independent Special Purpose Renal Dialysis Facility",
start = 2900L,
end = 3000L
)
rehosp <- dplyr::tibble(
type = "Rehabilitation Hospital",
start = 3025L,
end = 3100L
)
hha <- dplyr::tibble(
type = c("Home Health Agency",
"Home Health Agency",
"Home Health Agency"),
start = c(3100L, 7000L, 9000L),
end = c(3200L, 8500L, 9800L)
)
child <- dplyr::tibble(
type = "Children's Hospital",
start = 3300L,
end = 3400L
)
rhcp <- dplyr::tibble(
type = c("Rural Health Clinic (Provider-based)",
"Rural Health Clinic (Provider-based)",
"Rural Health Clinic (Provider-based)"),
start = c(3400L, 3975L, 8500L),
end = c(3500L, 4000L, 8900L)
)
rhcf <- dplyr::tibble(
type = c("Rural Health Clinic (Free-standing)",
"Rural Health Clinic (Free-standing)"),
start = c(3800L, 8900L),
end = c(3975L, 9000L)
)
hbsrdf <- dplyr::tibble(
type = "Hospital-based Satellite Renal Dialysis Facility",
start = 3500L,
end = 3700L
)
hbsprdf <- dplyr::tibble(
type = "Hospital-based Special Purpose Renal Dialysis Facility",
start = 3700L,
end = 3800L
)
psych <- dplyr::tibble(
type = "Psychiatric Hospital",
start = 4000L,
end = 4500L
)
corf <- dplyr::tibble(
type = c("Comprehensive Outpatient Rehabilitation Facility",
"Comprehensive Outpatient Rehabilitation Facility",
"Comprehensive Outpatient Rehabilitation Facility"),
start = c(3200L, 4500L, 4800L),
end = c(3300L, 4600L, 4900L)
)
snf <- dplyr::tibble(
type = "Skilled Nursing Facility",
start = 5000L,
end = 6500L
)
outpts <- dplyr::tibble(
type = "Outpatient Physical Therapy Services",
start = 6500L,
end = 6990L
)
tplant <- dplyr::tibble(
type = "Transplant Center",
start = 9800L,
end = 9900L
)
numrsrv <- dplyr::tibble(
type = "Number Reserved (formerly Christian Science Sanatoria Skilled Nursing Services)",
start = 6990L,
end = 7000L
)
futrsrv <- dplyr::tibble(
type = "Reserved for Future Use",
start = 9900L,
end = 10000L
)
mhcmc <- dplyr::tibble(
type = "Multiple Hospital Component in a Medical Complex (Number Retired)",
start = 900L,
end = 1000L
)
adhret <- dplyr::tibble(
type = "Alcohol/Drug Hospital (Number Retired)",
start = 1200L,
end = 1225L
)
tubret <- dplyr::tibble(
type = "Tuberculosis Hospital (Number Retired)",
start = 3000L,
end = 3025L
)
ranges <- dplyr::bind_rows(adhret, cah, child, cmhc, corf, fqhc,
futrsrv, hbrdf, hha, hospice, hbsprdf,
hbsrdf, irdf, isprdf, ltch, maf, mhcmc,
numrsrv, ord, outpts, psych, rehosp, rhcf,
rhcp, rnmhci, short, snf, tplant, tubret)
range_test <- ranges |>
dplyr::arrange(start) |>
dplyr::mutate(range = ivs::iv(start, end), .keep = "unused")
range_test
#> # A tibble: 39 × 2
#> type range
#> <chr> <iv<int>>
#> 1 Short-term (General and Specialty) Hospital [1, 880)
#> 2 Hospital participating in ORD demonstration project [880, 900)
#> 3 Multiple Hospital Component in a Medical Complex (Number Retir… [900, 1000)
#> 4 Federally Qualified Health Center [1000, 1200)
#> 5 Alcohol/Drug Hospital (Number Retired) [1200, 1225)
#> 6 Medical Assistance Facility [1225, 1300)
#> 7 Critical Access Hospital [1300, 1400)
#> 8 Community Mental Health Center [1400, 1500)
#> 9 Hospice [1500, 1800)
#> 10 Federally Qualified Health Center [1800, 1990)
#> 11 Religious Non-medical Health Care Institution (formerly Christ… [1990, 2000)
#> 12 Long-Term Care Hospital [2000, 2300)
#> 13 Hospital-based Renal Dialysis Facility [2300, 2500)
#> 14 Independent Renal Dialysis Facility [2500, 2900)
#> 15 Independent Special Purpose Renal Dialysis Facility [2900, 3000)
#> 16 Tuberculosis Hospital (Number Retired) [3000, 3025)
#> 17 Rehabilitation Hospital [3025, 3100)
#> 18 Home Health Agency [3100, 3200)
#> 19 Comprehensive Outpatient Rehabilitation Facility [3200, 3300)
#> 20 Children's Hospital [3300, 3400)
#> 21 Rural Health Clinic (Provider-based) [3400, 3500)
#> 22 Hospital-based Satellite Renal Dialysis Facility [3500, 3700)
#> 23 Hospital-based Special Purpose Renal Dialysis Facility [3700, 3800)
#> 24 Rural Health Clinic (Free-standing) [3800, 3975)
#> 25 Rural Health Clinic (Provider-based) [3975, 4000)
#> 26 Psychiatric Hospital [4000, 4500)
#> 27 Comprehensive Outpatient Rehabilitation Facility [4500, 4600)
#> 28 Community Mental Health Center [4600, 4800)
#> 29 Comprehensive Outpatient Rehabilitation Facility [4800, 4900)
#> 30 Community Mental Health Center [4900, 5000)
#> 31 Skilled Nursing Facility [5000, 6500)
#> 32 Outpatient Physical Therapy Services [6500, 6990)
#> 33 Number Reserved (formerly Christian Science Sanatoria Skilled … [6990, 7000)
#> 34 Home Health Agency [7000, 8500)
#> 35 Rural Health Clinic (Provider-based) [8500, 8900)
#> 36 Rural Health Clinic (Free-standing) [8900, 9000)
#> 37 Home Health Agency [9000, 9800)
#> 38 Transplant Center [9800, 9900)
#> 39 Reserved for Future Use [9900, 10000)
facility_code <- 3000L
range_test |>
dplyr::mutate(is_between = ivs::iv_includes(range, facility_code)) |>
dplyr::filter(is_between == TRUE) |>
dplyr::pull(type)
#> [1] "Tuberculosis Hospital (Number Retired)"
Created on 2023-11-29 with reprex v2.0.2