# summarise_gaps

0th

Percentile

##### Summarise Gaps in Therapy

This function serves as a convenience wrapper of dplyr::summarise(), which takes the grouped variables and summarises their gaps in therapy. This function is to be used after propagate_date().

##### Usage
summarise_gaps(.data)
##### Arguments
.data

Data to be piped into the function

##### Value

A summary of gaps in therapy

##### Note

This function relies an adjusted_date column to identify gaps in therapy. So, if you don't want to use propagate_date() beforehand, you'll need to rename the date variable you wish to use to adjusted_date.

##### Aliases
• summarise_gaps
##### Examples
# NOT RUN {
library(dplyr)

toy_claims %>%
filter(ID == "D") %>%
propagate_date(.date_var = date, .days_supply_var = days_supply) %>%
summarise_gaps()

# }