mimic-iii-los.rmd

---
title: "Length of stay in the ICU"
author: "tom pollard"
description: "Length of stay in the ICU for patients in MIMIC-III"
output: pdf_document
date: "10/10/2017"
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(echo = TRUE)
# install.packages("ggplot2")
# install.packages("bigrquery")
library("ggplot2")
library("bigrquery")
```


```{r dbconnect, include=FALSE}
# Load configuration settings
project_id <- "sccm-datathon"
options(httr_oauth_cache=TRUE)
run_query <- function(query){
    data <- query_exec(query, project=project_id, use_legacy_sql = FALSE)
    return(data)
}
```


```{r load_data, include=FALSE}
sql_query <- "SELECT i.subject_id, i.hadm_id, i.los
              FROM `physionet-data.mimiciii_demo.icustays` i;"
data <- run_query(sql_query)
head(data)
```

This document shows how RMarkdown can be used to create a reproducible analysis using MIMIC-III (version 1.4). Let's calculate the median length of stay in the ICU and then include this value in our document.

```{r calculate_mean_los, include=FALSE}
avg_los <- median(data$los, na.rm=TRUE)
rounded_avg_los <- round(avg_los, digits = 2)
```

So the median length of stay in the ICU is `r avg_los` days. Rounded to two decimal places, this is `r rounded_avg_los` days. We can plot the distribution of length of stay using the qplot function:   
   
   
```{r plot_los, echo=FALSE, include=TRUE,  warning = FALSE}
qplot(data$los, geom="histogram",xlim=c(0,25), binwidth = 1,
      xlab = "Length of stay in the ICU, days.",fill=I("#FF9999"), col=I("white"))
```