R/munge_p3.R
In mhealyd/vchdr:
.readP3001 <- function () {
P3001 <- readr::read_csv("phi/unprocessed/P3001.csv",
col_types = readr::cols()) %>%
tidyr::unite("name_pcg", c("last_pcg", "first_pcg"), sep = ", ") %>%
tidyr::unite("visitor", c("last_visitor", "first_visitor"), sep = ", ") %>%
dplyr::mutate_at(dplyr::vars(
dplyr::one_of(c("visit_date", "dob_pcg", "edd", "ldd",
"pnc_date", "folic_acid_date", "review_date"))),
dplyr::funs(lubridate::as_date(.))) %>%
dplyr::mutate(status = "PI-00",
id_pcg = stringr::str_pad(as.character(id_pcg), 5, "left", "0"),
age_pcg = lubridate::year(lubridate::as.period(
lubridate::interval(dob_pcg, visit_date))),
primigravida = ifelse(as.numeric(childbirths) == 0, 1, 0),
gest_age_mother = round(as.numeric(lubridate::as.duration(
lubridate::interval(edd - lubridate::weeks(40),
visit_date))) / 604800, digits = 1),
trimester = dplyr::case_when(
gest_age_mother < 14 ~ 1,
dplyr::between(gest_age_mother, 14, 27.9) ~ 2,
dplyr::between(gest_age_mother, 28, 43) ~ 3
),
race_pcg = ifelse(hispanic_pcg == 1, 5, race_pcg),
bmi_pre = (wt_pre_mother / ht_mother^2) * 703,
spacing = round(as.numeric(lubridate::as.duration(
lubridate::interval(ldd, edd - lubridate::weeks(40)))) / 2628288,
digits = 1),
lead_mother = ifelse(
lead_mother_01 == 1 | lead_mother_02 == 1 | lead_mother_03 == 1 |
lead_mother_04 == 1 | lead_mother_05 == 1 | lead_mother_06 == 1 |
lead_mother_07 == 1 | lead_mother_08 == 1 | lead_mother_09 == 1,
1, 0),
proc_days = lubridate::day(lubridate::as.period(
lubridate::interval(visit_date, review_date)))) %>%
dplyr::mutate_at(dplyr::vars(snap:tanf, food_barrier_01:food_barrier_05,
depression:mental_illness_othr,
diabetes:chr_dz_othr, gdm:sb),
dplyr::funs(replace(., . == "Off", NA))) %>%
dplyr::mutate_at(dplyr::vars(dcs, uninsured_pcg:private_pcg,
dplyr::ends_with("_opt")),
dplyr::funs(replace(., . == "Off", 0)))
P3001 <- P3001 %>%
dplyr::full_join(.vars2ListCol(P3001, id_pcg,
snap:tanf, "gov_benefits"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3001, id_pcg,
depression:mental_illness_othr, "psych_do"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3001, id_pcg,
diabetes:chr_dz_othr, "chr_dz"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3001, id_pcg,
gdm:preg_cx_othr, "preg_cx"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3001, id_pcg,
gdm_hx:preg_cx_othr_hx, "preg_cx_hx"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3001, id_pcg,
ptb:sb, "preg_outcome_hx"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3001, id_pcg,
food_barrier_01:food_barrier_05, "food_barriers"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol2(P3001, id_pcg,
bf_ed:toxo_ed, "ed_neg", "NEG"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol2(P3001, id_pcg,
bf_ed:toxo_ed, "ed_pos", "POS"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol2(P3001, id_pcg,
baby_me_ref:wic_ref, "ref_d", "D"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol2(P3001, id_pcg,
baby_me_ref:wic_ref, "ref_a", "A"),
by = "id_pcg") %>%
dplyr::select(suppressWarnings(dplyr::one_of(p3_variables)))
save(P3001, file = "phi/temp/P3001.rda")
}
.readP3002 <- function () {
P3002 <- readr::read_csv("phi/unprocessed/P3002.csv",
col_types = readr::cols()) %>%
tidyr::unite("name_pcg", c("last_pcg", "first_pcg"), sep = ", ") %>%
tidyr::unite("visitor", c("last_visitor", "first_visitor"), sep = ", ") %>%
dplyr::mutate(review_date = ifelse(exists("review_date"), review_date, NA)) %>%
dplyr::mutate_at(dplyr::vars(
dplyr::one_of(c("visit_date", "dob_pcg", "edd", "pnc_date",
"folic_acid_date", "review_date"))),
dplyr::funs(lubridate::as_date(.))) %>%
dplyr::mutate(id_pcg = stringr::str_pad(as.character(id_pcg), 5, "left", "0"),
proc_days = lubridate::day(lubridate::as.period(
lubridate::interval(visit_date, review_date)))) %>%
dplyr::mutate_at(dplyr::vars(snap:tanf, gdm:preg_cx_othr,
food_barrier_01:food_barrier_05),
dplyr::funs(replace(., . == "Off", NA))) %>%
dplyr::mutate_at(dplyr::vars(dcs, uninsured_pcg:private_pcg,
dplyr::ends_with("_opt")),
dplyr::funs(replace(., . == "Off", 0)))
P3002 <- P3002 %>%
dplyr::full_join(.vars2ListCol(P3002, id_pcg,
snap:tanf, "gov_benefits"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3002, id_pcg,
gdm:preg_cx_othr, "preg_cx"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3002, id_pcg,
food_barrier_01:food_barrier_05, "food_barriers"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol2(P3002, id_pcg,
bf_ed:toxo_ed, "ed_neg", "NEG"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol2(P3002, id_pcg,
bf_ed:toxo_ed, "ed_pos", "POS"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol2(P3002, id_pcg,
baby_me_ref:wic_ref, "ref_d", "D"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol2(P3002, id_pcg,
baby_me_ref:wic_ref, "ref_a", "A"),
by = "id_pcg") %>%
dplyr::select(suppressWarnings(dplyr::one_of(p3_variables)))
save(P3002, file = "phi/temp/P3002.rda")
}
.readP3003 <- function () {
P3003 <- readr::read_csv("phi/unprocessed/P3003.csv",
col_types = readr::cols()) %>%
tidyr::unite("name_child", c("last_child", "first_child"), sep = ", ") %>%
tidyr::unite("name_pcg", c("last_pcg", "first_pcg"), sep = ", ") %>%
tidyr::unite("visitor", c("last_visitor", "first_visitor"), sep = ", ") %>%
dplyr::mutate(ldd = ifelse(exists("ldd"), ldd, NA),
pnc_date = ifelse(exists("pnc_date"), pnc_date, NA),
folic_acid_date = ifelse(exists("folic_acid_date"), folic_acid_date, NA),
wcv_01mo = ifelse(exists("wcv_01mo"), wcv_01mo, NA),
wcv_02mo = ifelse(exists("wcv_02mo"), wcv_02mo, NA),
childbirths = ifelse(exists("childbirths"), childbirths, NA),
wt_pre_mother = ifelse(exists("wt_pre_mother"), wt_pre_mother, NA)) %>%
dplyr::mutate_at(dplyr::vars(
dplyr::one_of(c("visit_date", "dob_child", "dob_pcg", "edd", "ldd",
"pnc_date", "folic_acid_date", "review_date"))),
dplyr::funs(lubridate::as_date(.))) %>%
dplyr::mutate(status = "CI-00",
id_child = stringr::str_pad(as.character(id_child), 5, "left", "0"),
id_pcg = stringr::str_pad(as.character(id_pcg), 5, "left", "0"),
age_child = lubridate::month(lubridate::as.period(
lubridate::interval(dob_child, visit_date))),
age_pcg = lubridate::year(lubridate::as.period(
lubridate::interval(dob_pcg, visit_date))),
primigravida = ifelse(as.numeric(childbirths) == 0, 1, 0),
race_pcg = ifelse(hispanic_pcg == 1, 5, race_pcg),
bmi_pre = (wt_pre_mother / ht_mother^2) * 703,
bmi = (wt_mother / ht_mother^2) * 703,
diabetes_risk = ifelse(
diabetes_screen_02 == 1 | diabetes_screen_03 == 1, 1, 0),
spacing = ifelse(ldd == lubridate::as_date("1900-01-01"), NA,
round(as.numeric(lubridate::as.duration(
lubridate::interval(ldd, edd - lubridate::weeks(40)))) / 2628288,
digits = 1)),
lead_mother = ifelse(
lead_mother_01 == 1 | lead_mother_02 == 1 | lead_mother_03 == 1 |
lead_mother_04 == 1 | lead_mother_05 == 1 | lead_mother_06 == 1 |
lead_mother_07 == 1 | lead_mother_08 == 1 | lead_mother_09 == 1,
1, 0),
wt_child = round(
ifelse(is.na(wt_child_oz), wt_child_lbs * 453.59237,
(wt_child_lbs + wt_child_oz / 16) * 453.59237), 0),
race_child = ifelse(hispanic_child == 1, 5, race_child),
proc_days = lubridate::day(lubridate::as.period(
lubridate::interval(visit_date, review_date)))) %>%
dplyr::mutate_at(dplyr::vars(snap:tanf, food_barrier_01:food_barrier_05,
depression:other_mental_illness,
diabetes:chr_dz_othr, gdm:sb),
dplyr::funs(replace(., . == "Off", NA))) %>%
dplyr::mutate_at(dplyr::vars(dcs, uninsured_pcg:private_pcg,
uninsured_child:private_child,
dplyr::ends_with("_opt")),
dplyr::funs(replace(., . == "Off", 0)))
P3003 <- P3003 %>%
dplyr::full_join(.vars2ListCol(P3003, id_pcg,
snap:tanf, "gov_benefits"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3003, id_pcg,
depression:other_mental_illness, "psych_do"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3003, id_pcg,
diabetes:chr_dz_othr, "chr_dz"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3003, id_pcg,
gdm:preg_cx_othr, "preg_cx"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3003, id_pcg,
gdm_hx:preg_cx_othr_hx, "preg_cx_hx"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3003, id_pcg,
ptb:sb, "preg_outcome_hx"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3003, id_pcg,
food_barrier_01:food_barrier_05, "food_barriers"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3003, id_child,
wcv_01mo:wcv_02mo, "well_child"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3003, id_child,
bf_ed:toxo_ed, "ed_neg", "NEG"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3003, id_child,
bf_ed:toxo_ed, "ed_pos", "POS"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3003, id_child,
baby_me_ref:wic_ref, "ref_d", "D"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3003, id_child,
baby_me_ref:wic_ref, "ref_a", "A"),
by = "id_child") %>%
dplyr::select(suppressWarnings(dplyr::one_of(p3_variables)))
save(P3003, file = "phi/temp/P3003.rda")
}
.readP3004a <- function () {
P3004a <- readr::read_csv("phi/unprocessed/P3004a.csv",
col_types = readr::cols()) %>%
tidyr::unite("name_child", c("last_child", "first_child"), sep = ", ") %>%
tidyr::unite("name_pcg", c("last_pcg", "first_pcg"), sep = ", ") %>%
tidyr::unite("visitor", c("last_visitor", "first_visitor"), sep = ", ") %>%
dplyr::mutate(wcv_01mo = ifelse(exists("wcv_01mo"), wcv_01mo, NA),
wcv_02mo = ifelse(exists("wcv_02mo"), wcv_02mo, NA),
wcv_04mo = ifelse(exists("wcv_04mo"), wcv_04mo, NA),
wcv_06mo = ifelse(exists("wcv_06mo"), wcv_06mo, NA),
review_date = ifelse(exists("review_date"), review_date, NA)) %>%
dplyr::mutate_at(dplyr::vars(
dplyr::one_of(c("visit_date", "dob_child", "dob_pcg", "review_date"))),
dplyr::funs(lubridate::as_date(.))) %>%
dplyr::mutate(id_child = stringr::str_pad(as.character(id_child), 5, "left", "0"),
id_pcg = stringr::str_pad(as.character(id_pcg), 5, "left", "0"),
proc_days = lubridate::day(lubridate::as.period(
lubridate::interval(visit_date, review_date)))) %>%
dplyr::mutate_at(dplyr::vars(snap:tanf, food_barrier_01:food_barrier_05),
dplyr::funs(replace(., . == "Off", NA))) %>%
dplyr::mutate_at(dplyr::vars(dcs, uninsured_pcg:private_pcg,
uninsured_child:private_child,
dplyr::ends_with("_opt")),
dplyr::funs(replace(., . == "Off", 0)))
P3004a <- P3004a %>%
dplyr::full_join(.vars2ListCol(P3004a, id_pcg,
snap:tanf, "gov_benefits"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3004a, id_pcg,
food_barrier_01:food_barrier_05, "food_barriers"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3004a, id_child,
wcv_01mo:wcv_06mo, "well_child"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3004a, id_child,
bf_ed:toxo_ed, "ed_neg", "NEG"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3004a, id_child,
bf_ed:toxo_ed, "ed_pos", "POS"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3004a, id_child,
baby_me_ref:wic_ref, "ref_d", "D"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3004a, id_child,
baby_me_ref:wic_ref, "ref_a", "A"),
by = "id_child") %>%
dplyr::select(suppressWarnings(dplyr::one_of(p3_variables)))
save(P3004a, file = "phi/temp/P3004a.rda")
}
.readP3004b <- function () {
P3004b <- readr::read_csv("phi/unprocessed/P3004b.csv",
col_types = readr::cols()) %>%
tidyr::unite("name_child", c("last_child", "first_child"), sep = ", ") %>%
tidyr::unite("name_pcg", c("last_pcg", "first_pcg"), sep = ", ") %>%
tidyr::unite("visitor", c("last_visitor", "first_visitor"), sep = ", ") %>%
dplyr::mutate(wcv_09mo = ifelse(exists("wcv_09mo"), wcv_09mo, NA),
wcv_12mo = ifelse(exists("wcv_12mo"), wcv_12mo, NA),
wcv_15mo = ifelse(exists("wcv_15mo"), wcv_15mo, NA),
wcv_18mo = ifelse(exists("wcv_18mo"), wcv_18mo, NA),
lead_child_01 = ifelse(exists("lead_child_01"), lead_child_01, NA),
lead_child_02 = ifelse(exists("lead_child_02"), lead_child_02, NA),
lead_child_03 = ifelse(exists("lead_child_03"), lead_child_03, NA),
lead_child_04 = ifelse(exists("lead_child_04"), lead_child_04, NA),
lead_child_05 = ifelse(exists("lead_child_05"), lead_child_05, NA),
lead_child_06 = ifelse(exists("lead_child_06"), lead_child_06, NA),
lead_child_07 = ifelse(exists("lead_child_07"), lead_child_07, NA),
lead_child_08 = ifelse(exists("lead_child_08"), lead_child_08, NA),
lead_child_09 = ifelse(exists("lead_child_09"), lead_child_09, NA),
review_date = ifelse(exists("review_date"), review_date, NA)) %>%
dplyr::mutate_at(dplyr::vars(
dplyr::one_of(c("visit_date", "dob_child", "dob_pcg", "review_date"))),
dplyr::funs(lubridate::as_date(.))) %>%
dplyr::mutate(id_child = stringr::str_pad(as.character(id_child), 5, "left", "0"),
id_pcg = stringr::str_pad(as.character(id_pcg), 5, "left", "0"),
lead_child = ifelse(
lead_child_01 == 1 | lead_child_02 == 1 | lead_child_03 == 1 |
lead_child_04 == 1 | lead_child_05 == 1 | lead_child_06 == 1 |
lead_child_07 == 1 | lead_child_08 == 1 | lead_child_09 == 1,
1, 0),
proc_days = lubridate::day(lubridate::as.period(
lubridate::interval(visit_date, review_date)))) %>%
dplyr::mutate_at(dplyr::vars(snap:tanf, food_barrier_01:food_barrier_05),
dplyr::funs(replace(., . == "Off", NA))) %>%
dplyr::mutate_at(dplyr::vars(dcs, uninsured_pcg:private_pcg,
uninsured_child:private_child,
dplyr::ends_with("_opt")),
dplyr::funs(replace(., . == "Off", 0)))
P3004b <- P3004b %>%
dplyr::full_join(.vars2ListCol(P3004b, id_pcg,
snap:tanf, "gov_benefits"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3004b, id_pcg,
food_barrier_01:food_barrier_05, "food_barriers"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3004b, id_child,
wcv_09mo:wcv_18mo, "well_child"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3004b, id_child,
bf_ed:toxo_ed, "ed_neg", "NEG"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3004b, id_child,
bf_ed:toxo_ed, "ed_pos", "POS"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3004b, id_child,
baby_me_ref:wic_ref, "ref_d", "D"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3004b, id_child,
baby_me_ref:wic_ref, "ref_a", "A"),
by = "id_child") %>%
dplyr::select(suppressWarnings(dplyr::one_of(p3_variables)))
save(P3004b, file = "phi/temp/P3004b.rda")
}
mhealyd/vchdr documentation built on May 21, 2019, 2:06 p.m.
R Package Documentation
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.readP3001 <- function () {
P3001 <- readr::read_csv("phi/unprocessed/P3001.csv",
col_types = readr::cols()) %>%
tidyr::unite("name_pcg", c("last_pcg", "first_pcg"), sep = ", ") %>%
tidyr::unite("visitor", c("last_visitor", "first_visitor"), sep = ", ") %>%
dplyr::mutate_at(dplyr::vars(
dplyr::one_of(c("visit_date", "dob_pcg", "edd", "ldd",
"pnc_date", "folic_acid_date", "review_date"))),
dplyr::funs(lubridate::as_date(.))) %>%
dplyr::mutate(status = "PI-00",
id_pcg = stringr::str_pad(as.character(id_pcg), 5, "left", "0"),
age_pcg = lubridate::year(lubridate::as.period(
lubridate::interval(dob_pcg, visit_date))),
primigravida = ifelse(as.numeric(childbirths) == 0, 1, 0),
gest_age_mother = round(as.numeric(lubridate::as.duration(
lubridate::interval(edd - lubridate::weeks(40),
visit_date))) / 604800, digits = 1),
trimester = dplyr::case_when(
gest_age_mother < 14 ~ 1,
dplyr::between(gest_age_mother, 14, 27.9) ~ 2,
dplyr::between(gest_age_mother, 28, 43) ~ 3
),
race_pcg = ifelse(hispanic_pcg == 1, 5, race_pcg),
bmi_pre = (wt_pre_mother / ht_mother^2) * 703,
spacing = round(as.numeric(lubridate::as.duration(
lubridate::interval(ldd, edd - lubridate::weeks(40)))) / 2628288,
digits = 1),
lead_mother = ifelse(
lead_mother_01 == 1 | lead_mother_02 == 1 | lead_mother_03 == 1 |
lead_mother_04 == 1 | lead_mother_05 == 1 | lead_mother_06 == 1 |
lead_mother_07 == 1 | lead_mother_08 == 1 | lead_mother_09 == 1,
1, 0),
proc_days = lubridate::day(lubridate::as.period(
lubridate::interval(visit_date, review_date)))) %>%
dplyr::mutate_at(dplyr::vars(snap:tanf, food_barrier_01:food_barrier_05,
depression:mental_illness_othr,
diabetes:chr_dz_othr, gdm:sb),
dplyr::funs(replace(., . == "Off", NA))) %>%
dplyr::mutate_at(dplyr::vars(dcs, uninsured_pcg:private_pcg,
dplyr::ends_with("_opt")),
dplyr::funs(replace(., . == "Off", 0)))
P3001 <- P3001 %>%
dplyr::full_join(.vars2ListCol(P3001, id_pcg,
snap:tanf, "gov_benefits"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3001, id_pcg,
depression:mental_illness_othr, "psych_do"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3001, id_pcg,
diabetes:chr_dz_othr, "chr_dz"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3001, id_pcg,
gdm:preg_cx_othr, "preg_cx"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3001, id_pcg,
gdm_hx:preg_cx_othr_hx, "preg_cx_hx"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3001, id_pcg,
ptb:sb, "preg_outcome_hx"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3001, id_pcg,
food_barrier_01:food_barrier_05, "food_barriers"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol2(P3001, id_pcg,
bf_ed:toxo_ed, "ed_neg", "NEG"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol2(P3001, id_pcg,
bf_ed:toxo_ed, "ed_pos", "POS"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol2(P3001, id_pcg,
baby_me_ref:wic_ref, "ref_d", "D"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol2(P3001, id_pcg,
baby_me_ref:wic_ref, "ref_a", "A"),
by = "id_pcg") %>%
dplyr::select(suppressWarnings(dplyr::one_of(p3_variables)))
save(P3001, file = "phi/temp/P3001.rda")
}
.readP3002 <- function () {
P3002 <- readr::read_csv("phi/unprocessed/P3002.csv",
col_types = readr::cols()) %>%
tidyr::unite("name_pcg", c("last_pcg", "first_pcg"), sep = ", ") %>%
tidyr::unite("visitor", c("last_visitor", "first_visitor"), sep = ", ") %>%
dplyr::mutate(review_date = ifelse(exists("review_date"), review_date, NA)) %>%
dplyr::mutate_at(dplyr::vars(
dplyr::one_of(c("visit_date", "dob_pcg", "edd", "pnc_date",
"folic_acid_date", "review_date"))),
dplyr::funs(lubridate::as_date(.))) %>%
dplyr::mutate(id_pcg = stringr::str_pad(as.character(id_pcg), 5, "left", "0"),
proc_days = lubridate::day(lubridate::as.period(
lubridate::interval(visit_date, review_date)))) %>%
dplyr::mutate_at(dplyr::vars(snap:tanf, gdm:preg_cx_othr,
food_barrier_01:food_barrier_05),
dplyr::funs(replace(., . == "Off", NA))) %>%
dplyr::mutate_at(dplyr::vars(dcs, uninsured_pcg:private_pcg,
dplyr::ends_with("_opt")),
dplyr::funs(replace(., . == "Off", 0)))
P3002 <- P3002 %>%
dplyr::full_join(.vars2ListCol(P3002, id_pcg,
snap:tanf, "gov_benefits"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3002, id_pcg,
gdm:preg_cx_othr, "preg_cx"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3002, id_pcg,
food_barrier_01:food_barrier_05, "food_barriers"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol2(P3002, id_pcg,
bf_ed:toxo_ed, "ed_neg", "NEG"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol2(P3002, id_pcg,
bf_ed:toxo_ed, "ed_pos", "POS"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol2(P3002, id_pcg,
baby_me_ref:wic_ref, "ref_d", "D"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol2(P3002, id_pcg,
baby_me_ref:wic_ref, "ref_a", "A"),
by = "id_pcg") %>%
dplyr::select(suppressWarnings(dplyr::one_of(p3_variables)))
save(P3002, file = "phi/temp/P3002.rda")
}
.readP3003 <- function () {
P3003 <- readr::read_csv("phi/unprocessed/P3003.csv",
col_types = readr::cols()) %>%
tidyr::unite("name_child", c("last_child", "first_child"), sep = ", ") %>%
tidyr::unite("name_pcg", c("last_pcg", "first_pcg"), sep = ", ") %>%
tidyr::unite("visitor", c("last_visitor", "first_visitor"), sep = ", ") %>%
dplyr::mutate(ldd = ifelse(exists("ldd"), ldd, NA),
pnc_date = ifelse(exists("pnc_date"), pnc_date, NA),
folic_acid_date = ifelse(exists("folic_acid_date"), folic_acid_date, NA),
wcv_01mo = ifelse(exists("wcv_01mo"), wcv_01mo, NA),
wcv_02mo = ifelse(exists("wcv_02mo"), wcv_02mo, NA),
childbirths = ifelse(exists("childbirths"), childbirths, NA),
wt_pre_mother = ifelse(exists("wt_pre_mother"), wt_pre_mother, NA)) %>%
dplyr::mutate_at(dplyr::vars(
dplyr::one_of(c("visit_date", "dob_child", "dob_pcg", "edd", "ldd",
"pnc_date", "folic_acid_date", "review_date"))),
dplyr::funs(lubridate::as_date(.))) %>%
dplyr::mutate(status = "CI-00",
id_child = stringr::str_pad(as.character(id_child), 5, "left", "0"),
id_pcg = stringr::str_pad(as.character(id_pcg), 5, "left", "0"),
age_child = lubridate::month(lubridate::as.period(
lubridate::interval(dob_child, visit_date))),
age_pcg = lubridate::year(lubridate::as.period(
lubridate::interval(dob_pcg, visit_date))),
primigravida = ifelse(as.numeric(childbirths) == 0, 1, 0),
race_pcg = ifelse(hispanic_pcg == 1, 5, race_pcg),
bmi_pre = (wt_pre_mother / ht_mother^2) * 703,
bmi = (wt_mother / ht_mother^2) * 703,
diabetes_risk = ifelse(
diabetes_screen_02 == 1 | diabetes_screen_03 == 1, 1, 0),
spacing = ifelse(ldd == lubridate::as_date("1900-01-01"), NA,
round(as.numeric(lubridate::as.duration(
lubridate::interval(ldd, edd - lubridate::weeks(40)))) / 2628288,
digits = 1)),
lead_mother = ifelse(
lead_mother_01 == 1 | lead_mother_02 == 1 | lead_mother_03 == 1 |
lead_mother_04 == 1 | lead_mother_05 == 1 | lead_mother_06 == 1 |
lead_mother_07 == 1 | lead_mother_08 == 1 | lead_mother_09 == 1,
1, 0),
wt_child = round(
ifelse(is.na(wt_child_oz), wt_child_lbs * 453.59237,
(wt_child_lbs + wt_child_oz / 16) * 453.59237), 0),
race_child = ifelse(hispanic_child == 1, 5, race_child),
proc_days = lubridate::day(lubridate::as.period(
lubridate::interval(visit_date, review_date)))) %>%
dplyr::mutate_at(dplyr::vars(snap:tanf, food_barrier_01:food_barrier_05,
depression:other_mental_illness,
diabetes:chr_dz_othr, gdm:sb),
dplyr::funs(replace(., . == "Off", NA))) %>%
dplyr::mutate_at(dplyr::vars(dcs, uninsured_pcg:private_pcg,
uninsured_child:private_child,
dplyr::ends_with("_opt")),
dplyr::funs(replace(., . == "Off", 0)))
P3003 <- P3003 %>%
dplyr::full_join(.vars2ListCol(P3003, id_pcg,
snap:tanf, "gov_benefits"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3003, id_pcg,
depression:other_mental_illness, "psych_do"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3003, id_pcg,
diabetes:chr_dz_othr, "chr_dz"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3003, id_pcg,
gdm:preg_cx_othr, "preg_cx"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3003, id_pcg,
gdm_hx:preg_cx_othr_hx, "preg_cx_hx"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3003, id_pcg,
ptb:sb, "preg_outcome_hx"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3003, id_pcg,
food_barrier_01:food_barrier_05, "food_barriers"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3003, id_child,
wcv_01mo:wcv_02mo, "well_child"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3003, id_child,
bf_ed:toxo_ed, "ed_neg", "NEG"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3003, id_child,
bf_ed:toxo_ed, "ed_pos", "POS"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3003, id_child,
baby_me_ref:wic_ref, "ref_d", "D"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3003, id_child,
baby_me_ref:wic_ref, "ref_a", "A"),
by = "id_child") %>%
dplyr::select(suppressWarnings(dplyr::one_of(p3_variables)))
save(P3003, file = "phi/temp/P3003.rda")
}
.readP3004a <- function () {
P3004a <- readr::read_csv("phi/unprocessed/P3004a.csv",
col_types = readr::cols()) %>%
tidyr::unite("name_child", c("last_child", "first_child"), sep = ", ") %>%
tidyr::unite("name_pcg", c("last_pcg", "first_pcg"), sep = ", ") %>%
tidyr::unite("visitor", c("last_visitor", "first_visitor"), sep = ", ") %>%
dplyr::mutate(wcv_01mo = ifelse(exists("wcv_01mo"), wcv_01mo, NA),
wcv_02mo = ifelse(exists("wcv_02mo"), wcv_02mo, NA),
wcv_04mo = ifelse(exists("wcv_04mo"), wcv_04mo, NA),
wcv_06mo = ifelse(exists("wcv_06mo"), wcv_06mo, NA),
review_date = ifelse(exists("review_date"), review_date, NA)) %>%
dplyr::mutate_at(dplyr::vars(
dplyr::one_of(c("visit_date", "dob_child", "dob_pcg", "review_date"))),
dplyr::funs(lubridate::as_date(.))) %>%
dplyr::mutate(id_child = stringr::str_pad(as.character(id_child), 5, "left", "0"),
id_pcg = stringr::str_pad(as.character(id_pcg), 5, "left", "0"),
proc_days = lubridate::day(lubridate::as.period(
lubridate::interval(visit_date, review_date)))) %>%
dplyr::mutate_at(dplyr::vars(snap:tanf, food_barrier_01:food_barrier_05),
dplyr::funs(replace(., . == "Off", NA))) %>%
dplyr::mutate_at(dplyr::vars(dcs, uninsured_pcg:private_pcg,
uninsured_child:private_child,
dplyr::ends_with("_opt")),
dplyr::funs(replace(., . == "Off", 0)))
P3004a <- P3004a %>%
dplyr::full_join(.vars2ListCol(P3004a, id_pcg,
snap:tanf, "gov_benefits"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3004a, id_pcg,
food_barrier_01:food_barrier_05, "food_barriers"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3004a, id_child,
wcv_01mo:wcv_06mo, "well_child"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3004a, id_child,
bf_ed:toxo_ed, "ed_neg", "NEG"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3004a, id_child,
bf_ed:toxo_ed, "ed_pos", "POS"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3004a, id_child,
baby_me_ref:wic_ref, "ref_d", "D"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3004a, id_child,
baby_me_ref:wic_ref, "ref_a", "A"),
by = "id_child") %>%
dplyr::select(suppressWarnings(dplyr::one_of(p3_variables)))
save(P3004a, file = "phi/temp/P3004a.rda")
}
.readP3004b <- function () {
P3004b <- readr::read_csv("phi/unprocessed/P3004b.csv",
col_types = readr::cols()) %>%
tidyr::unite("name_child", c("last_child", "first_child"), sep = ", ") %>%
tidyr::unite("name_pcg", c("last_pcg", "first_pcg"), sep = ", ") %>%
tidyr::unite("visitor", c("last_visitor", "first_visitor"), sep = ", ") %>%
dplyr::mutate(wcv_09mo = ifelse(exists("wcv_09mo"), wcv_09mo, NA),
wcv_12mo = ifelse(exists("wcv_12mo"), wcv_12mo, NA),
wcv_15mo = ifelse(exists("wcv_15mo"), wcv_15mo, NA),
wcv_18mo = ifelse(exists("wcv_18mo"), wcv_18mo, NA),
lead_child_01 = ifelse(exists("lead_child_01"), lead_child_01, NA),
lead_child_02 = ifelse(exists("lead_child_02"), lead_child_02, NA),
lead_child_03 = ifelse(exists("lead_child_03"), lead_child_03, NA),
lead_child_04 = ifelse(exists("lead_child_04"), lead_child_04, NA),
lead_child_05 = ifelse(exists("lead_child_05"), lead_child_05, NA),
lead_child_06 = ifelse(exists("lead_child_06"), lead_child_06, NA),
lead_child_07 = ifelse(exists("lead_child_07"), lead_child_07, NA),
lead_child_08 = ifelse(exists("lead_child_08"), lead_child_08, NA),
lead_child_09 = ifelse(exists("lead_child_09"), lead_child_09, NA),
review_date = ifelse(exists("review_date"), review_date, NA)) %>%
dplyr::mutate_at(dplyr::vars(
dplyr::one_of(c("visit_date", "dob_child", "dob_pcg", "review_date"))),
dplyr::funs(lubridate::as_date(.))) %>%
dplyr::mutate(id_child = stringr::str_pad(as.character(id_child), 5, "left", "0"),
id_pcg = stringr::str_pad(as.character(id_pcg), 5, "left", "0"),
lead_child = ifelse(
lead_child_01 == 1 | lead_child_02 == 1 | lead_child_03 == 1 |
lead_child_04 == 1 | lead_child_05 == 1 | lead_child_06 == 1 |
lead_child_07 == 1 | lead_child_08 == 1 | lead_child_09 == 1,
1, 0),
proc_days = lubridate::day(lubridate::as.period(
lubridate::interval(visit_date, review_date)))) %>%
dplyr::mutate_at(dplyr::vars(snap:tanf, food_barrier_01:food_barrier_05),
dplyr::funs(replace(., . == "Off", NA))) %>%
dplyr::mutate_at(dplyr::vars(dcs, uninsured_pcg:private_pcg,
uninsured_child:private_child,
dplyr::ends_with("_opt")),
dplyr::funs(replace(., . == "Off", 0)))
P3004b <- P3004b %>%
dplyr::full_join(.vars2ListCol(P3004b, id_pcg,
snap:tanf, "gov_benefits"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3004b, id_pcg,
food_barrier_01:food_barrier_05, "food_barriers"),
by = "id_pcg") %>%
dplyr::full_join(.vars2ListCol(P3004b, id_child,
wcv_09mo:wcv_18mo, "well_child"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3004b, id_child,
bf_ed:toxo_ed, "ed_neg", "NEG"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3004b, id_child,
bf_ed:toxo_ed, "ed_pos", "POS"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3004b, id_child,
baby_me_ref:wic_ref, "ref_d", "D"),
by = "id_child") %>%
dplyr::full_join(.vars2ListCol2(P3004b, id_child,
baby_me_ref:wic_ref, "ref_a", "A"),
by = "id_child") %>%
dplyr::select(suppressWarnings(dplyr::one_of(p3_variables)))
save(P3004b, file = "phi/temp/P3004b.rda")
}
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