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Katheterzahl pro Operateur im lfd. Jahr eingefügt.

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daniel 2019-01-01 11:18:07 +01:00
parent 87a63bc472
commit 6b3df60e4c
1 changed files with 45 additions and 9 deletions
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vhk.Rmd
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@ -11,15 +11,18 @@ output:
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE, warning = FALSE)
library(tidyverse)
library(lubridate)
raw_data = read_csv('vhk.csv') %>%
mutate(Year = lubridate::year(Date))
mutate(Year = year(Date))
cath_by_year = raw_data %>% count(Year)
first_year = min(raw_data$Year)
last_year = max(raw_data$Year)
max_y_break = ((max(cath_by_year$n) %/% 10) + 1) * 10
reference_year = year(today()) - (today() < make_date(year(today()), 1, 31))
```
## Katheterimplantationen pro Jahr
@ -32,10 +35,24 @@ cath_by_year %>%
labs(x = NULL, y = "Anzahl Katheter")
```
## Katheterimplantationen pro Operateur im Jahr `r reference_year`
```{r}
raw_data %>% mutate(Year = year(Date)) %>% filter(Year == reference_year) %>%
count(Surgeon) %>%
arrange(n) %>%
mutate(Surgeon = factor(Surgeon, levels = Surgeon)) %>%
ggplot(aes(x = Surgeon, y = n)) +
geom_col() +
coord_flip() +
labs(x = NULL, y = stringr::str_c("Anzahl Katheter im Jahr ", reference_year))
```
<!--
## Katheterimplantationen im Jahresverlauf
```{r cath_by_month}
raw_data %>% mutate(Month = lubridate::month(Date)) %>%
raw_data %>% mutate(Month = month(Date)) %>%
group_by(Year) %>%
count(Month) %>%
ggplot(aes(x = Month, y = n, group = Year, alpha = Year)) +
@ -47,7 +64,7 @@ raw_data %>% mutate(Month = lubridate::month(Date)) %>%
## Katheterexplantationen pro Jahr
```{r expl_by_year}
raw_data %>% mutate(ExplYear = lubridate::year(RemovalDate)) %>%
raw_data %>% mutate(ExplYear = year(RemovalDate)) %>%
# group_by(InsertionSite, Side) %>%
count(ExplYear) %>%
ggplot(aes(x = ExplYear, y = n)) +
@ -59,7 +76,7 @@ raw_data %>% mutate(ExplYear = lubridate::year(RemovalDate)) %>%
## Explantationen pro Implantation pro Jahr
```{r expl_by_cath_by_year}
raw_data %>% mutate(ImplYear = lubridate::year(Date), ExplYear = lubridate::year(RemovalDate)) %>%
raw_data %>% mutate(ImplYear = year(Date), ExplYear = year(RemovalDate)) %>%
group_by(ImplYear) %>%
summarise(ExplByImpl = sum(!is.na(ExplYear)) / n()) %>%
ggplot(aes(x = ImplYear, y = ExplByImpl)) +
@ -70,7 +87,7 @@ raw_data %>% mutate(ImplYear = lubridate::year(Date), ExplYear = lubridate::year
## Verweildauern der Katheter
```{r durations, message=FALSE}
raw_data %>% mutate(Year = lubridate::year(Date), Duration = RemovalDate - Date) %>%
raw_data %>% mutate(Year = year(Date), Duration = RemovalDate - Date) %>%
group_by(Year) %>%
summarize(MedianDuration = median(Duration, na.rm = TRUE)) %>%
ggplot(aes(x = Year, y = MedianDuration)) +
@ -83,7 +100,7 @@ raw_data %>% mutate(Year = lubridate::year(Date), Duration = RemovalDate - Date)
### Variante A: Absolute Zahlen
```{r removal_reasons, message=FALSE}
raw_data %>% filter(!is.na(RemovalDate), !is.na(RemovalReason)) %>%
mutate(ExplYear = lubridate::year(RemovalDate) %% 100) %>%
mutate(ExplYear = year(RemovalDate) %% 100) %>%
group_by(ExplYear) %>%
count(RemovalReason) %>%
ggplot(aes(x = ExplYear, y = n)) +
@ -98,11 +115,11 @@ raw_data %>% filter(!is.na(RemovalDate), !is.na(RemovalReason)) %>%
```{r removal_reasons_normalized, message=FALSE}
# Zur Berechnung dieses Index muß man zunächst für jeden explantierten Katheter
# berechnen, wie viele Katheter im *ex*plantationsjahr *im*plantiert wurden.
impl_per_year = raw_data %>% mutate(ImplYear = lubridate::year(Date)) %>% count(ImplYear)
impl_per_year = raw_data %>% mutate(ImplYear = year(Date)) %>% count(ImplYear)
raw_data %>%
select(Date, RemovalDate, RemovalReason) %>%
mutate(ImplYear = lubridate::year(Date) %% 100, ExplYear = lubridate::year(RemovalDate)) %>%
mutate(ImplYear = year(Date) %% 100, ExplYear = year(RemovalDate)) %>%
left_join(impl_per_year, by = c("ExplYear" = "ImplYear")) %>% # creates column "n"
filter(!is.na(RemovalDate), !is.na(RemovalReason)) %>%
group_by(ExplYear) %>%
@ -121,6 +138,21 @@ raw_data %>%
labs(x = NULL, y = "Anzahl entfernter Katheter / gelegter Katheter")
```
<!--
## Explantationsgründe je Implanteur
```{r removal_reasons_by_surgeon, message=FALSE}
raw_data %>% filter(!is.na(RemovalDate)) %>%
mutate(ExplYear = year(RemovalDate)) %>%
filter(ExplYear > year(today()) - 4) %>%
group_by(ExplYear, Surgeon) %>%
count(RemovalReason) %>%
ggplot(aes(x = ExplYear, y = n)) +
geom_point() + geom_line() +
facet_grid(rows = vars(Surgeon), cols = vars(RemovalReason)) +
labs(x = NULL, y = "Anzahl expl. Katheter")
```
-->
## Alter der Patienten
```{r patient_age}
@ -190,8 +222,11 @@ raw_data %>%
Nur Operateure der letzten 4 Jahre
```{r individual_fluoroscopy, message=FALSE}
raw_data %>% filter(Year > lubridate::year(lubridate::today()) - 4, !is.na(InsertionFluoroscopyDuration)) %>%
to_year = year(today()) %% 100
from_year = to_year - 3
raw_data %>%
mutate(Year = Year %% 100) %>%
filter(Year >= from_year, !is.na(InsertionFluoroscopyDuration)) %>%
group_by(Surgeon, Year) %>%
summarize(FluoroscopyIndex = median(InsertionFluoroscopyDuration, na.rm = TRUE)) %>%
ungroup() %>%
@ -199,6 +234,7 @@ raw_data %>% filter(Year > lubridate::year(lubridate::today()) - 4, !is.na(Inser
ggplot(aes(x = Year, y = FluoroscopyIndex)) +
geom_point() +
geom_line() +
scale_x_continuous(breaks = seq(from = from_year, to = to_year, by = 1 )) +
facet_wrap(vars(Surgeon)) +
labs(x = NULL, y = "Median der Durchleuchtungsdauer [s]")
```