How to change all values within group following lag(value) > 1 - r

Question

Someone named Tarqon on Reddits /r/Rlanguage solved the problem. 1 + cumsum(days_between >= 45 instead of the if_else.
group_by(DMHID) %>%
arrange(DMHID, DateOfService) %>%
mutate(days_between = as.numeric(DateOfService - lag(DateOfService, default = DateOfService[1]))) %>%
mutate(eoc_45dco = 1 + cumsum(days_between >= 45)) %>%
mutate(id_eoc = as.integer(paste0(DMHID, eoc_45dco))) %>%
ORIGINAL QUESTION
So I am trying to split cases based on the amount of days (> 45) between one visit and the next. It works for the individual instance when there is more than 45 days between one visit and the next, but I need each visit after that to be part of the second group. For example, Participant 1234 has 362 visits, but between visit 105 (2016-12-26) and 106 (2017-02-23) there was a 59 day gap so i want all cases after that to be labeled 2. Rather All cases leading up to and including 105 are 12341 and after that 12342, so I can group by this variable for later analyses. Problem is that I can only seem to get the 106th visit to be labeled 12342 and everything before and after are 12341. I created a stripped down dataset and script that does reproduce the problem.
https://www.dropbox.com/s/k6gvo8igvbhpgti/reprex.zip?dl=0
EDIT: I just thought of another way to say it. I basically need to figure out how to group/subset data for each person, with the dividing line being the first time there is a gap of 45 days or more. I might be going down the wrong road with my current implementation, so if you can suggest alternative ways to split the data the way I want let me know. In the example I only have one persons visits, so the full dataset has a few thousand people with similar issues.
barometer <- df_pdencs_orig %>%
select(-EncID, -SiteName, -EOCKey, -ProgramLevel, -ProgramLevelCode, -ProcedureDesc, -MedicationValue, -CheckDate, -PdAmount, -PayerType) %>%
mutate_at(vars(contains("Date")), funs(ymd)) %>%
filter(DMHID %in% valid_diag$DMHID & DateOfService >= ymd(open_date)) %>%
group_by(DMHID) %>%
arrange(DMHID, DateOfService) %>%
mutate(days_between = DateOfService - lag(DateOfService, n = 1, default = DateOfService[1])) %>%
mutate(eoc_45dco = 1) %>%
mutate(eoc_45dco = if_else(days_between >= 45, lag(eoc_45dco) + 1, eoc_45dco)) %>%
mutate(eoc_45dco2 = if_else(lag(eoc_45dco) > 1, eoc_45dco + 1, eoc_45dco)) %>%
mutate(id_eoc = as.integer(paste0(DMHID, eoc_45dco))) %>%
...
The reprex below works just fine so I don't think that helps.
library(tidyverse)
library(lubridate)
#>
#> Attaching package: 'lubridate'
#> The following object is masked from 'package:base':
#>
#> date
df <- data.frame(
date = sample(seq(as.Date('2016/06/01'), as.Date('2017/03/01'), by="day"), 11),
days = as.difftime(c(40:50), units = "days")
)
df %>%
mutate(id = 1234) %>%
arrange(days) %>%
mutate(Z = 1) %>%
mutate(Z = if_else(days >= 45, lag(Z) + 1, Z)) %>%
mutate(id_eoc = as.integer(paste0(id, Z)))
#> date days id Z id_eoc
#> 1 2016-06-30 40 days 1234 1 12341
#> 2 2016-11-25 41 days 1234 1 12341
#> 3 2016-09-09 42 days 1234 1 12341
#> 4 2017-01-16 43 days 1234 1 12341
#> 5 2016-08-16 44 days 1234 1 12341
#> 6 2016-09-23 45 days 1234 2 12342
#> 7 2016-09-05 46 days 1234 2 12342
#> 8 2016-08-29 47 days 1234 2 12342
#> 9 2016-07-08 48 days 1234 2 12342
#> 10 2017-01-11 49 days 1234 2 12342
#> 11 2017-02-22 50 days 1234 2 12342
Created on 2018-04-17 by the reprex package (v0.2.0).
As such I think the issue is with the dates maybe since subtracting dates gives a time variable and not an integer.