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presentation_support_code.Rmd
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---
title: "Supporting Code"
subtitle: "for R/Medicine 2022 Presentation"
author: ""
resource_files:
- config.yml
runtime: html
output:
# prettydoc::html_pretty:
# theme: tactile
# highlight: github
html_document:
css: "unmc-rmarkdown-html-template.css"
code_folding: hide
number_sections: TRUE
# toc: TRUE
# toc_float: TRUE
---
***
```{r options, echo=FALSE}
library(knitr)
knitr::opts_chunk$set(tidy='formatR', size='tiny',
fig.width=10, fig.height=6, fig.align='center',
fig.retina = 1, # needs to be explicitly defined for some reason
tidy.opts=list(comment = FALSE, blank=FALSE, width.cutoff=60)
)
## Send warnings and messages to an external file called 'messages.txt'
unlink('messages.txt') # Start fresh with each run
hook_log = function(x, options) cat(x, file='messages.txt', append=TRUE)
knit_hooks$set(warning = hook_log, message = hook_log)
```
```{r retrieve-current-git-commit, echo=FALSE}
gitCommit <- paste0("This document built from git commit ",system("git rev-parse --short HEAD", intern = TRUE),".")
```
```{r setup,results='hide', warning=FALSE, message=FALSE}
library(tidyverse)
library(plotly)
library(shiny)
library(scales) # empirical cumulative density function and other distributions
library(hrbrthemes) # nice ggplot theme
library(showtext) # Better font handling
library(gt) # Grammar of Tables
library(lubridate)
library(runcharter)
theme_set(hrbrthemes::theme_ipsum_rc())
font_add_google("Roboto Condensed")
showtext_auto()
```
```{r}
ponv_data <- read_rds("ponv_prophylaxis_success_rates_AY2021-2022.rds")
ponv_data_baseline <- ponv_data %>%
filter(surgery_month < "2021-04-30")
ponv_data_initial <- ponv_data %>%
filter(surgery_month < "2021-07-31")
ponv_data_intermed <- ponv_data %>%
filter(surgery_month < "2021-10-31")
ponv_data_complete <- ponv_data %>%
mutate(animate_order = as.numeric(as.factor(surgery_month)))
```
# Concept Figure
```{r}
library(ggpomological)
library(dplyr)
font_add_google("Homemade Apple")
fig_data <- tribble(~time, ~outcome,
1, 20,
2, 23,
3, 22,
4, 20,
5, 19,
6, 21,
7, 23,
8, 20,
9, 24,
10, 21,)
p <- fig_data %>%
filter(time <= 10) %>%
ggplot(aes(x = time, y = outcome)) +
geom_point(color = "#828585", size = 3) +
geom_line(color = "#828585", size = 1) +
theme_pomological_fancy()+
labs(x = "Time Interval",
y = "Outcome") +
theme(panel.grid.minor = element_blank()) #+
# transition_reveal(time)
# ggsave("images/concept_run_chart.png", height = 4, width = 9, units = "cm")
paint_pomological(p, height = 472, width = 1062) %>%
magick::image_write( "images/concept_run_chart.png")
# gganimate::animate(p, end_pause = 20)
# gganimate::anim_save("concept_runchart.gif")
```
# Basic Figure
```{r}
fig_data <- tribble(~time, ~outcome,
1, 20,
2, 23,
3, 22,
4, 20,
5, 19,
6, 21,
7, 23,
8, 20,
9, 24,
10, 21,
11, 31,
12, 34,
13, 29,
14, 33,
15, 31)
median1 <- fig_data %>%
filter(time <= 10) %>%
dplyr::summarize(value = median(outcome))
median2 <- fig_data %>%
filter(time > 10) %>%
dplyr::summarize(value = median(outcome))
fig_data %>%
filter(time <= 10) %>%
ggplot(aes(x = time, y = outcome)) +
geom_line() +
geom_point() +
geom_line(aes(y = median1$value, x = c(1:10)),
color = "#AD122A", size = 1) +
theme_ipsum_rc() +
scale_x_continuous(breaks = c(1:15), limits = c(1,15)) +
scale_y_continuous(n.breaks = 9, limits = c(19, 34)) +
labs(x = "Time Interval",
y = "Outcome",
family = "Roboto Condensed") +
annotate("label", x = 11, y = median1$value,
label = "Median", color = "#AD122A",
family = "Roboto Condensed") +
theme(panel.grid.minor = element_blank())
ggsave("basic_run_chart.png", height = 8, width = 18, units = "cm")
```
# Supporting Figures Demonstrating Variation
```{r}
fig_data_variation <- tribble(~time, ~outcome,
1, 20,
2, 23,
3, 22,
4, 20,
5, 19,
6, 21,
7, 23,
8, 20,
9, 24,
10, 21.2,
11, 21.5,
12, 20.3,
13, 21,
14, 20.5,
15, 21.5)
median1 <- fig_data_variation %>%
filter(time <= 10) %>%
dplyr::summarize(value = median(outcome))
fig_data_variation %>%
ggplot(aes(x = time, y = outcome)) +
geom_line() +
geom_point() +
theme_ipsum_rc() +
scale_x_continuous(breaks = c(1:15), limits = c(1,15)) +
scale_y_continuous(n.breaks = 9, limits = c(19, 34)) +
labs(x = "Time Interval",
y = "Outcome",
family = "Roboto Condensed") +
geom_segment(aes(y = median1$value, yend = median1$value,
x = 1, xend = 10),
color = "black", size = 1) +
geom_segment(aes(y = median1$value, yend = median1$value,
x = 11, xend = 15),
color = "#AD122A", size = 1) +
annotate("label", x = 5, y = 26,
label = "Original Process\nModerate Variation", color = "black",
family = "Roboto Condensed") +
annotate("label", x = 13, y = 26,
label = "Improved Process\nReduced Variation\nSame Median", color = "#AD122A",
family = "Roboto Condensed") +
theme(panel.grid.minor = element_blank())
ggsave("basic_run_chart_lower_variation.png", height = 8, width = 18, units = "cm")
```
```{r}
fig_data_variation %>%
ggplot(aes(x = time, y = outcome)) +
geom_line() +
geom_point() +
theme_ipsum_rc() +
scale_x_continuous(breaks = c(1:15), limits = c(1,15)) +
scale_y_continuous(n.breaks = 9, limits = c(19, 34)) +
labs(x = "Time Interval",
y = "Outcome",
family = "Roboto Condensed") +
geom_segment(aes(y = median1$value, yend = median1$value,
x = 1, xend = 10),
color = "black", size = 1) +
geom_segment(aes(y = median1$value, yend = median1$value,
x = 11, xend = 15),
color = "#AD122A", size = 1) +
annotate("label", x = 5, y = 26,
label = "Original Process\nModerate Variation", color = "black",
family = "Roboto Condensed") +
annotate("label", x = 13, y = 26,
label = "Reduced Variation\nSame Median", color = "#AD122A",
family = "Roboto Condensed") +
theme(panel.grid.minor = element_blank())
ggsave("images/basic_run_chart_lower_variation_example.png", height = 8, width = 18, units = "cm")
```
# Supporting Figures Demonstrating Run
```{r}
fig_data %>%
ggplot(aes(x = time, y = outcome)) +
geom_line() +
geom_point() +
theme_ipsum_rc() +
scale_x_continuous(breaks = c(1:15), limits = c(1,15)) +
scale_y_continuous(n.breaks = 9, limits = c(19, 34)) +
labs(x = "Time Interval",
y = "Outcome",
family = "Roboto Condensed") +
geom_segment(aes(y = median1$value, yend = median1$value,
x = 1, xend = 10),
color = "black", size = 1) +
geom_segment(aes(y = median2$value, yend = median2$value,
x = 11, xend = 15),
color = "#AD122A", size = 1) +
annotate("label", x = 9.5, y = median2$value,
label = "New Median", color = "#AD122A",
family = "Roboto Condensed") +
theme(panel.grid.minor = element_blank())
ggsave("basic_run_chart_with_shift.png", height = 8, width = 18, units = "cm")
```
# gganimate
```{r}
library(gganimate)
runchart_output_complete <- ponv_data_complete %>%
runcharter(
datecol = surgery_month,
yval = success_rate,
grpvar = plot_group,
med_rows = 9,
runlength = 3,
direction = "both",
highlight_fill = "#005EB8",
highlight_point_size = 0,
line_colr = "black"
)
p<- runchart_output_complete$runchart +
facet_null() +
theme_ipsum_rc() +
scale_y_continuous(labels = scales::percent_format(accuracy = 1),
limits = c(0.88, NA)) +
scale_x_date(date_labels = "%b %Y") +
theme(panel.grid.minor = element_blank(),
panel.grid.major = element_blank(),
plot.background = element_rect(colour = "black", fill=NA, size=1),
plot.margin=unit(c(5,0,0,0),"mm")) +
labs(title = "MIPS 430 Success Rate by Month",
subtitle = "Prevention of PONV - Combination Therapy") +
annotate("rect", xmin = ymd("2020-07-01"), xmax = ymd("2021-04-05"),
ymin = -Inf, ymax = Inf, alpha = 0.15) +
geom_vline(xintercept = ymd("2021-04-05")) +
annotate("text", x = ymd("2020-11-15"), y = 0.88,
label = "Historical Data", family = "Roboto Condensed") +
annotate("text", x = ymd("2021-04-10"), y = 0.88,
hjust = 0, parse=TRUE,
label = "bold('Start of QI Project')", family = "Roboto Condensed") +
geom_vline(xintercept = ymd("2021-10-05")) +
annotate("text", x = ymd("2021-10-10"), y = 0.88,
hjust = 0, color = "#AD122A", parse=TRUE,
label = "bold('Monthly Metric Reviews\nIndividual Performance Reports')", family = "Roboto Condensed") +
transition_reveal(animate_order)
# gganimate::animate(p, end_pause = 20, height = 472, width = 1062, units = "px")
gganimate::animate(p, end_pause = 20, width = 1062, height = 480, units = "px")
gganimate::anim_save("images/final_runchart_wide.gif")
```
***
`r gitCommit`