case_crossover: Case-crossover analysis

In jomuller/ITCARES: an Interactive Tool for Case-crossover Analyses of electronic medical REcords for patient Safety

Description

Performs case-crossover analysis

Usage

case_crossover(case_stay, data, exposure_diagnoses, exposure_procedures,
  screening_index_stay, unique_exposure, interval_length, number_of_interval,
  wash_out, los_max)

Arguments

case_stay	The data.table generated with age_study_period_restrictions() function.
data	A data.table of electronic medical records (EMRs): the same is used in first_case().
exposure_diagnoses	A character vector containing codes to identify exposure diagnoses in stays.
exposure_procedures	A character vector containing codes to identify exposure procedures in stays.
screening_index_stay	A Boolean. If TRUE, the case stay is also screened for exposure. If FALSE, the case stay is ignored.
unique_exposure	A Boolean. If TRUE, patients with multiple stays with exposures are excluded.
interval_length	A scalar giving the duration of each interval.
number_of_interval	A scalar giving the number of intervals to compute.
wash_out	A scalar giving the wash-out period (defaut = 365 days).
los_max	A scalar giving the maximum possible length for an episode with exposure.

Details

The exposure is defined as a combination of diagnoses AND medical procedures which is sought on the one hand during the case period and on the other hand during the control period (one year earlier). The case period and hence the control period were split into several intervals. A paired-matched interval approach was used, as described by Mittleman. Conditional logistic regression was used to compare the likelihood of exposure during each interval of the case period with that during the control period. An OR and its 95 the risk of onset of the primary outcome compared to the basal risk. He/she also defined the maximum possible length for an episode with exposure. The case stay was excluded from the exposure screening period, if required. A patient presenting the exposure in multiple episodes was excluded, if required.

Value

A list

Examples

data(ep)
obj0 <- ep

obj1 <- first_case(
  data = obj0,
  diagnoses_case =  'PE',
  diagnoses_exclusion = 'EXCLUSION',
  exclude_in_case_stay = FALSE,
  n_of_stays_max = 20
)

obj1 

obj2 <- age_study_period_restrictions(
  data = obj0,
  cases = obj1,
  starting_year = 2007,
  final_year = 2013,
  age_min = 0,
  age_max = 120
)

obj2

obj3 <- case_crossover(
  case_stay = obj2,
  data = obj0,
  exposure_diagnoses = '',
  exposure_procedures = 'THR',
  screening_index_stay = FALSE,
  unique_exposure = TRUE,
  interval_length = 42,
  number_of_interval = 8,
  wash_out = 365,
  los_max = 42
)
obj3 
obj3$graph

jomuller/ITCARES documentation built on May 19, 2019, 7:26 p.m.