The goal of processcheckR is to support rule-based conformance checking. Currently the following declarative rules can be checked:
Cardinality rules:
contains: activity occurs n times or morecontains_exactly: activity occurs exactly n timescontains_between: activity occures between min and max
number of timesabsent: activity does not occur more than n - 1
timesOrdering rules:
starts: case starts with activityends: case ends with activitysuccession: if activity A happens, B should happen
after. If B happens, A should have happened before.response: if activity A happens, B should happen
afterprecedence: if activity B happens, A should have
happend beforeresponded_existence: if activity A happens, B should
also (have) happen(ed) (i.e. before or after A)Exclusiveness:
and: two activities always exist togetherxor: two activities are not allowed to exist
togetherRules can be checked using the check_rule function (see
example below). It will create a new logical variable to indicate for
which cases the rule holds. The name of the variable can be configured
using the label argument in check_rule.
You can install processcheckR from github with:
library(bupaR)
#> 
#> Attaching package: 'bupaR'
#> The following object is masked from 'package:stats':
#> 
#>     filter
#> The following object is masked from 'package:utils':
#> 
#>     timestamp
library(processcheckR)
#> 
#> Attaching package: 'processcheckR'
#> The following object is masked from 'package:base':
#> 
#>     xor
sepsis %>%
  # check if cases starts with "ER Registration"
  check_rule(starts("ER Registration"), label = "r1") %>%
  # check if activities "CRP" and "LacticAcid" occur together
  check_rule(and("CRP","LacticAcid"), label = "r2") %>%
  group_by(r1, r2) %>%
  n_cases() 
#> # A tibble: 4 × 3
#>   r1    r2    n_cases
#>   <lgl> <lgl>   <int>
#> 1 FALSE FALSE      10
#> 2 FALSE TRUE       45
#> 3 TRUE  FALSE     137
#> 4 TRUE  TRUE      858