summaryTableRF: summaryTableRF

In n8thangreen/HESmanip: Hospital length of stay data preprocessing and analysis

Usage

summaryTableRF(survData)

Arguments

survData

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (survData) 
{
    out <- NULL
    out <- rbind(out, c(NA, NA, NA, NA))
    x <- as.data.frame(with(survData, table(infstatus, cancer)))
    y <- as.data.frame(prop.table(with(survData, table(infstatus, 
        cancer)), 1))
    out <- rbind(out, c(x[x$cancer == T, "Freq"], format(y[y$cancer == 
        T, "Freq"], digits = 2)))
    x <- as.data.frame(with(survData, table(infstatus, prem)))
    y <- as.data.frame(prop.table(with(survData, table(infstatus, 
        prem)), 1))
    out <- rbind(out, c(x[x$prem == T, "Freq"], format(y[y$prem == 
        T, "Freq"], digits = 2)))
    x <- as.data.frame(with(survData, table(infstatus, cong)))
    y <- as.data.frame(prop.table(with(survData, table(infstatus, 
        cong)), 1))
    out <- rbind(out, c(x[x$cong == T, "Freq"], format(y[y$cong == 
        T, "Freq"], digits = 2)))
    x <- as.data.frame(with(survData, table(infstatus, surgical)))
    y <- as.data.frame(prop.table(with(survData, table(infstatus, 
        surgical)), 1))
    out <- rbind(out, c(x[x$surgical == T, "Freq"], format(y[y$surgical == 
        T, "Freq"], digits = 2)))
    x <- as.data.frame(with(survData, table(infstatus, cath)))
    y <- as.data.frame(prop.table(with(survData, table(infstatus, 
        cath)), 1))
    out <- rbind(out, c(x[x$cath == T, "Freq"], format(y[y$cath == 
        T, "Freq"], digits = 2)))
    x <- as.data.frame(with(survData, table(infstatus, highRisk)))
    y <- as.data.frame(prop.table(with(survData, table(infstatus, 
        highRisk)), 1))
    out <- rbind(out, c(x[x$highRisk == T, "Freq"], format(y[y$highRisk == 
        T, "Freq"], digits = 2)))
    out <- rbind(out, c(NA, NA, NA, NA))
    elective <- c("Elective - booked", "Elective - planned", 
        "Elective - from waiting list")
    x <- as.data.frame(with(survData, table(infstatus, hes_admimethdescription %in% 
        elective)))
    y <- as.data.frame(prop.table(with(survData, table(infstatus, 
        hes_admimethdescription %in% elective)), 1))
    out <- rbind(out, c(x[x$Var2 == T, "Freq"], format(y[y$Var2 == 
        T, "Freq"], digits = 2)))
    emergency <- c("Emergency - other means, including patients who arrive via A&E department of another HC provider", 
        "Emergency - via A&E services, including casualty department of provider", 
        "Emergency - via General Practitioner (GP)", "Emergency - via Bed Bureau, including Central Bureau", 
        "Emergency - via consultant out-patient clinic")
    x <- as.data.frame(with(survData, table(infstatus, hes_admimethdescription %in% 
        emergency)))
    y <- as.data.frame(prop.table(with(survData, table(infstatus, 
        hes_admimethdescription %in% emergency)), 1))
    out <- rbind(out, c(x[x$Var2 == T, "Freq"], format(y[y$Var2 == 
        T, "Freq"], digits = 2)))
    out <- rbind(out, aggregate(as.numeric(tail(out, 2)), by = list(c(1, 
        1, 2, 2, 3, 3, 4, 4)), sum)$x)
    neocare <- c("Level 1 intensive care", "Level 2 intensive care")
    x <- as.data.frame(with(survData, table(infstatus, hes_neocaredescription %in% 
        neocare)))
    y <- as.data.frame(prop.table(with(survData, table(infstatus, 
        hes_neocaredescription %in% neocare)), 1))
    out <- rbind(out, c(x[x$Var2 == T, "Freq"], format(y[y$Var2 == 
        T, "Freq"], digits = 2)))
    out <- rbind(out, c(NA, NA, NA, NA))
    x <- as.data.frame(with(survData, table(infstatus, hes_admimethdescription == 
        "Transfer of any admitted patient from another hospital provider")))
    y <- as.data.frame(prop.table(with(survData, table(infstatus, 
        hes_admimethdescription == "Transfer of any admitted patient from another hospital provider")), 
        1))
    out <- rbind(out, c(x[x$Var2 == T, "Freq"], format(y[y$Var2 == 
        T, "Freq"], digits = 2)))
    residence <- c("The usual place of residence, including no fixed abode", 
        "Temporary place of residence when usually resident elsewhere")
    x <- as.data.frame(with(survData, table(infstatus, hes_admisorcdescription %in% 
        residence)))
    y <- as.data.frame(prop.table(with(survData, table(infstatus, 
        hes_admisorcdescription %in% residence)), 1))
    out <- rbind(out, c(x[x$Var2 == T, "Freq"], format(y[y$Var2 == 
        T, "Freq"], digits = 2)))
    out <- rbind(out, aggregate(as.numeric(tail(out, 2)), by = list(c(1, 
        1, 2, 2, 3, 3, 4, 4)), sum)$x)
    if (ncol(out) == 4) {
        colnames(out) <- c("Non-HA-BSI", "HA-BSI", "%", "%")
        out <- out[, c(1, 3, 2, 4)]
    }
    else {
        colnames(out) <- c("Non-HA-BSI", "%")
    }
    rownames(out) <- c("Risk Factors", "Cancer", "Premature birth", 
        "Congenital disorder", "Surgical", "In-dwelling catheter", 
        "At least one", "Type of Admission", "Elective", "Emergency", 
        "TOTAL", "Intensive neonatal care", "Origin of patient", 
        "Another hospital", "Residence", "TOTAL")
    return(out)
  }

n8thangreen/HESmanip documentation built on March 21, 2020, 12:20 a.m.