data-raw/testdata-hcv_monthly_report.R
In JayAchar/hisreportr: hisreportr: Automating MSF OCA EMR reporting
# generate test data for HCV monthly report
set.seed(9912)
# number of patients
n_patients <- 1000
# number of days in current month
days_current_month <- lubridate::day(Sys.Date()) - 1
# momth proportion
p_month <- 0.3
# year proportion
p_year <- 0.3
# current Sys.time()
ctime <- Sys.time()
# initiate data list
data_hcv_monthly <- list()
data_hcv_monthly$"2_treatment_initiation_début_de_traitement" <- data.frame(
patient_id = 1:n_patients,
start_hepc_treatment = sample(c("Yes", "No", NA_character_), n_patients,
replace = TRUE,
prob = c(0.90, 0.05, 0.05)),
hepc_treatment_start_date = c(Sys.Date() - sample(0:days_current_month, n_patients * p_month, replace = TRUE),
Sys.Date() - sample((days_current_month+1):365, n_patients * p_year, replace = TRUE),
Sys.Date() - months(12) + sample(-45:45, n_patients - (n_patients * p_month) - (n_patients * p_year),
replace = TRUE)),
date_initiation_consulations = rep(Sys.Date(), n_patients),
stringsAsFactors = FALSE
)
data_hcv_monthly$"person_details_default" <- data.frame(
person_id = 1:n_patients,
gender = sample(c("M", "F", "U", NA_character_), n_patients, replace = TRUE,
prob = c(0.48, 0.48, 0.01, 0.01)),
age = as.character(sample(1:99, n_patients, replace = TRUE)),
stringsAsFactors = FALSE
)
data_hcv_monthly$"person_attributes" <-
data.frame(
person_id = 1:n_patients,
Admission_date_Date_d_admission =
format(data_hcv_monthly$"2_treatment_initiation_début_de_traitement"$hepc_treatment_start_date
- lubridate::days(sample(
700:-7, n_patients, replace = TRUE)),
format = "%Y-%m-%dT%H:%M:%OS3%z"),
stringsAsFactors = FALSE
)
# Form 4 Weight and height ----
data_hcv_monthly$"4_weight_assessment_évaluation_du_poids" <- data.frame(
patient_id = 1:n_patients,
assessment_date = data_hcv_monthly$"2_treatment_initiation_début_de_traitement"$hepc_treatment_start_date -
floor(rbeta(n_patients, 2, 5) * 15),
weight = abs(rnorm(n_patients, mean = 80, sd = 30)),
height = abs(rnorm(n_patients, mean = 170, sd = 70)),
stringsAsFactors = FALSE
)
data_hcv_monthly$"4_clin_assess_treat_hcv_éval_clin_trait_vhc" <-
data.frame(
patient_id = 1:n_patients,
obs_datetime = ctime,
visit_date = c(data_hcv_monthly$"2_treatment_initiation_début_de_traitement"$hepc_treatment_start_date +
sample(-5:30, n_patients, replace = TRUE)),
treatment_status_today = sample(c("Not assessed / Pending Results",
"Eligible / Already under treatment",
"Not eligible",
"Follow up after treatment",
"Not specified",
NA_character_), n_patients, replace = TRUE,
prob = c(0.05, 0.80, 0.03, 0.10, 0.01, 0.01)),
decision_on_treatment_care = sample(c("Waiting List",
"Initiation/ Re-initiation",
"Continuation same dose",
"Modification due to adverse event",
"Modification due to other reasons",
"Discontinuation due to adverse event",
"Discontinuation (Stop) for other reasons",
"Treatment finished",
"Not specified",
NA_character_), n_patients, replace = TRUE,
prob = c(0.05, 0.60, 0.10, 0.10, 0.05, 0.01, 0.01, 0.07, 0.01, 0)),
stringsAsFactors = FALSE
)
data_hcv_monthly$"4_performance_status_statut_de_performance" <-
data.frame(
patient_id = 1:n_patients,
assessment_date = c(data_hcv_monthly$"2_treatment_initiation_début_de_traitement"$hepc_treatment_start_date -
sample(0:90, n_patients, replace = TRUE)),
performance_status_ecog = sample(c("0=Fully active",
"1=Ambulatory",
"2=Capable of self care",
"3=Limited self care",
"4=Completely disabled",
NA_character_), n_patients, replace = TRUE,
prob = c(rep(0.19, 5), 0.05)),
stringsAsFactors = FALSE
)
data_hcv_monthly$"3_lab_virology_lab_virologie" <-
data.frame(
patient_id = 1:n_patients,
date_sample_examination = c(data_hcv_monthly$"2_treatment_initiation_début_de_traitement"$hepc_treatment_start_date -
sample(0:90, n_patients, replace = TRUE)),
hcv_genotype_done = sample(c("Yes",
"No",
NA_character_), n_patients, replace = TRUE,
prob = c(0.9, 0.08, 0.02)),
fibroscan_staging_category = sample(c("F0 no fibrosis",
"F1 mild fibrosis",
"F2 moderate fibrosis",
"F3 severe fibrosis",
"F4 cirrhosis",
"Not specified",
NA_character_), n_patients, replace = TRUE,
prob = c(rep(0.18, 5), 0.07, 0.03)),
child_pugh_score = sample(5:15, n_patients, replace = TRUE),
stringsAsFactors = FALSE
)
data_hcv_monthly$hcv_genotype <-
data.frame(
patient_id = 1:n_patients,
hcv_genotype = sample(c("Genotype 1",
"Genotype 2",
"Genotype 3",
"Genotype 4",
"Genotype 5",
"Genotype 6",
"Indeterminate",
"Not specified",
NA_character_), n_patients, replace = TRUE,
prob = c(0.7, 0.01, 0.2, 0.01, 0.01, 0.07, 0, 0, 0)),
stringsAsFactors = FALSE
)
data_hcv_monthly$hcv_genotype_sub_type <-
data.frame(
patient_id = 1:n_patients,
hcv_genotype_sub_type = sample(c("Subtype a",
"Subtype b",
"Subtype c",
"Subtype d",
"Subtype e",
"Subtype other",
"Not specified",
NA_character_), n_patients, replace = TRUE,
prob = c(0.7, 0.1, 0.1, 0.05, 0.05, 0, 0, 0)),
stringsAsFactors = FALSE
)
data_hcv_monthly$hcv_treatment_prescribed <-
data.frame(
patient_id = 1:n_patients,
obs_datetime = ctime,
hcv_treatment_prescribed = sample(c("Sofosbuvir (SOF)",
"Daclatasvir (DCV)",
"Ribavirin (RBV)",
"LDP/SOF (FDC)",
"SOF/VEL (FDC)",
"SOF/VEL/VOX (FDC)",
"SOF/DCV (FDC)",
"GLE/PIB (FDC)",
"Other",
NA_character_), n_patients, replace = TRUE,
prob = c(0.01, 0.01, 0.01, 0.02, 0.02, 0.07, 0.8, 0.1, 0.06, 0)),
stringsAsFactors = FALSE
)
data_hcv_monthly$"6_treatment_outcome_hcv_issue_du_traitement_vhc" <-
data.frame(
patient_id = 1:n_patients,
end_of_treatment_date = data_hcv_monthly$"2_treatment_initiation_début_de_traitement"$hepc_treatment_start_date +
c(floor(rnorm(n_patients * 0.75, 180, 20)),
floor(rnorm(n_patients * 0.25, 270, 30))),
outcome_this_course = sample(c("Cured",
"Failed",
"Died",
"LTFU during treatment",
"Completed, post treatment VL not done",
"Other",
NA_character_), n_patients, replace = TRUE,
prob = c(0.87, 0.03, 0.03, 0.05, 0.02, 0.01, 0)),
final_end_of_followup = sample(c("Yes",
"No",
"Unknown",
NA_character_), n_patients, replace = TRUE,
prob = c(0.85, 0.10, 0.04, 0.01)),
reason_end_of_followup = sample(c("Cured",
"Death",
"Transfer out",
"Loss of Follow up",
"Medical decision to stop HCV Follow up",
NA_character_), n_patients, replace = TRUE,
prob = c(0.75, 0.08, 0.01, 0.14, 0.02, 0)),
stringsAsFactors = FALSE
)
# save tb_month raw data for SQL testing db
saveRDS(data_hcv_monthly, "inst/testdata/data_hcv_monthly.rds", version = 2)
JayAchar/hisreportr documentation built on March 18, 2020, 5:57 a.m.
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# generate test data for HCV monthly report
set.seed(9912)
# number of patients
n_patients <- 1000
# number of days in current month
days_current_month <- lubridate::day(Sys.Date()) - 1
# momth proportion
p_month <- 0.3
# year proportion
p_year <- 0.3
# current Sys.time()
ctime <- Sys.time()
# initiate data list
data_hcv_monthly <- list()
data_hcv_monthly$"2_treatment_initiation_début_de_traitement" <- data.frame(
patient_id = 1:n_patients,
start_hepc_treatment = sample(c("Yes", "No", NA_character_), n_patients,
replace = TRUE,
prob = c(0.90, 0.05, 0.05)),
hepc_treatment_start_date = c(Sys.Date() - sample(0:days_current_month, n_patients * p_month, replace = TRUE),
Sys.Date() - sample((days_current_month+1):365, n_patients * p_year, replace = TRUE),
Sys.Date() - months(12) + sample(-45:45, n_patients - (n_patients * p_month) - (n_patients * p_year),
replace = TRUE)),
date_initiation_consulations = rep(Sys.Date(), n_patients),
stringsAsFactors = FALSE
)
data_hcv_monthly$"person_details_default" <- data.frame(
person_id = 1:n_patients,
gender = sample(c("M", "F", "U", NA_character_), n_patients, replace = TRUE,
prob = c(0.48, 0.48, 0.01, 0.01)),
age = as.character(sample(1:99, n_patients, replace = TRUE)),
stringsAsFactors = FALSE
)
data_hcv_monthly$"person_attributes" <-
data.frame(
person_id = 1:n_patients,
Admission_date_Date_d_admission =
format(data_hcv_monthly$"2_treatment_initiation_début_de_traitement"$hepc_treatment_start_date
- lubridate::days(sample(
700:-7, n_patients, replace = TRUE)),
format = "%Y-%m-%dT%H:%M:%OS3%z"),
stringsAsFactors = FALSE
)
# Form 4 Weight and height ----
data_hcv_monthly$"4_weight_assessment_évaluation_du_poids" <- data.frame(
patient_id = 1:n_patients,
assessment_date = data_hcv_monthly$"2_treatment_initiation_début_de_traitement"$hepc_treatment_start_date -
floor(rbeta(n_patients, 2, 5) * 15),
weight = abs(rnorm(n_patients, mean = 80, sd = 30)),
height = abs(rnorm(n_patients, mean = 170, sd = 70)),
stringsAsFactors = FALSE
)
data_hcv_monthly$"4_clin_assess_treat_hcv_éval_clin_trait_vhc" <-
data.frame(
patient_id = 1:n_patients,
obs_datetime = ctime,
visit_date = c(data_hcv_monthly$"2_treatment_initiation_début_de_traitement"$hepc_treatment_start_date +
sample(-5:30, n_patients, replace = TRUE)),
treatment_status_today = sample(c("Not assessed / Pending Results",
"Eligible / Already under treatment",
"Not eligible",
"Follow up after treatment",
"Not specified",
NA_character_), n_patients, replace = TRUE,
prob = c(0.05, 0.80, 0.03, 0.10, 0.01, 0.01)),
decision_on_treatment_care = sample(c("Waiting List",
"Initiation/ Re-initiation",
"Continuation same dose",
"Modification due to adverse event",
"Modification due to other reasons",
"Discontinuation due to adverse event",
"Discontinuation (Stop) for other reasons",
"Treatment finished",
"Not specified",
NA_character_), n_patients, replace = TRUE,
prob = c(0.05, 0.60, 0.10, 0.10, 0.05, 0.01, 0.01, 0.07, 0.01, 0)),
stringsAsFactors = FALSE
)
data_hcv_monthly$"4_performance_status_statut_de_performance" <-
data.frame(
patient_id = 1:n_patients,
assessment_date = c(data_hcv_monthly$"2_treatment_initiation_début_de_traitement"$hepc_treatment_start_date -
sample(0:90, n_patients, replace = TRUE)),
performance_status_ecog = sample(c("0=Fully active",
"1=Ambulatory",
"2=Capable of self care",
"3=Limited self care",
"4=Completely disabled",
NA_character_), n_patients, replace = TRUE,
prob = c(rep(0.19, 5), 0.05)),
stringsAsFactors = FALSE
)
data_hcv_monthly$"3_lab_virology_lab_virologie" <-
data.frame(
patient_id = 1:n_patients,
date_sample_examination = c(data_hcv_monthly$"2_treatment_initiation_début_de_traitement"$hepc_treatment_start_date -
sample(0:90, n_patients, replace = TRUE)),
hcv_genotype_done = sample(c("Yes",
"No",
NA_character_), n_patients, replace = TRUE,
prob = c(0.9, 0.08, 0.02)),
fibroscan_staging_category = sample(c("F0 no fibrosis",
"F1 mild fibrosis",
"F2 moderate fibrosis",
"F3 severe fibrosis",
"F4 cirrhosis",
"Not specified",
NA_character_), n_patients, replace = TRUE,
prob = c(rep(0.18, 5), 0.07, 0.03)),
child_pugh_score = sample(5:15, n_patients, replace = TRUE),
stringsAsFactors = FALSE
)
data_hcv_monthly$hcv_genotype <-
data.frame(
patient_id = 1:n_patients,
hcv_genotype = sample(c("Genotype 1",
"Genotype 2",
"Genotype 3",
"Genotype 4",
"Genotype 5",
"Genotype 6",
"Indeterminate",
"Not specified",
NA_character_), n_patients, replace = TRUE,
prob = c(0.7, 0.01, 0.2, 0.01, 0.01, 0.07, 0, 0, 0)),
stringsAsFactors = FALSE
)
data_hcv_monthly$hcv_genotype_sub_type <-
data.frame(
patient_id = 1:n_patients,
hcv_genotype_sub_type = sample(c("Subtype a",
"Subtype b",
"Subtype c",
"Subtype d",
"Subtype e",
"Subtype other",
"Not specified",
NA_character_), n_patients, replace = TRUE,
prob = c(0.7, 0.1, 0.1, 0.05, 0.05, 0, 0, 0)),
stringsAsFactors = FALSE
)
data_hcv_monthly$hcv_treatment_prescribed <-
data.frame(
patient_id = 1:n_patients,
obs_datetime = ctime,
hcv_treatment_prescribed = sample(c("Sofosbuvir (SOF)",
"Daclatasvir (DCV)",
"Ribavirin (RBV)",
"LDP/SOF (FDC)",
"SOF/VEL (FDC)",
"SOF/VEL/VOX (FDC)",
"SOF/DCV (FDC)",
"GLE/PIB (FDC)",
"Other",
NA_character_), n_patients, replace = TRUE,
prob = c(0.01, 0.01, 0.01, 0.02, 0.02, 0.07, 0.8, 0.1, 0.06, 0)),
stringsAsFactors = FALSE
)
data_hcv_monthly$"6_treatment_outcome_hcv_issue_du_traitement_vhc" <-
data.frame(
patient_id = 1:n_patients,
end_of_treatment_date = data_hcv_monthly$"2_treatment_initiation_début_de_traitement"$hepc_treatment_start_date +
c(floor(rnorm(n_patients * 0.75, 180, 20)),
floor(rnorm(n_patients * 0.25, 270, 30))),
outcome_this_course = sample(c("Cured",
"Failed",
"Died",
"LTFU during treatment",
"Completed, post treatment VL not done",
"Other",
NA_character_), n_patients, replace = TRUE,
prob = c(0.87, 0.03, 0.03, 0.05, 0.02, 0.01, 0)),
final_end_of_followup = sample(c("Yes",
"No",
"Unknown",
NA_character_), n_patients, replace = TRUE,
prob = c(0.85, 0.10, 0.04, 0.01)),
reason_end_of_followup = sample(c("Cured",
"Death",
"Transfer out",
"Loss of Follow up",
"Medical decision to stop HCV Follow up",
NA_character_), n_patients, replace = TRUE,
prob = c(0.75, 0.08, 0.01, 0.14, 0.02, 0)),
stringsAsFactors = FALSE
)
# save tb_month raw data for SQL testing db
saveRDS(data_hcv_monthly, "inst/testdata/data_hcv_monthly.rds", version = 2)
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