cusum {cusum}

Non-risk-adjusted CUSUM Charts

Description

Calculate non-risk-adjusted CUSUM charts for performance data

Provides functions for constructing and evaluating CUSUM charts and RA-CUSUM charts with focus on false signal probability in health care processes.

Usage

cusum(failure_probability, patient_outcomes, limit, weights = NULL,
  odds_multiplier = 2, reset = TRUE)

Arguments

failure_probability

Double. Baseline failure probability

patient_outcomes

Integer. Vector of binary patient outcomes (0,1)

limit

Double. Control limit for signalling performance change

weights

Double. Optional vector of weights, if empty, standard CUSUM weights are calculated with weights_t

odds_multiplier

Double. Odds multiplier of adverse event under the alternative hypothesis (<1 looks for decreases)

reset

Logical. Reset the CUSUM after a signal to 0; defaults to TRUE

Author(s)

Lena Hubig

Examples

# control limit can be obtained with cusum_limit_sim(),
# here it is set to an arbitrary value (2.96)

# CUSUM of in-control process
# simulate patient outcomes
set.seed(2046)
patient_outcomes <- as.logical(rbinom(n = 100, size = 1, prob = 0.05))


cs_ic <- cusum(
  failure_probability = 0.05,
  patient_outcomes,
  limit = 2.96
)

# CUSUM of out-of-control process
# simulate patient outcome
set.seed(2046)
patient_outcomes <- as.logical(rbinom(n = 100, size = 1, prob = 0.2))

cs_oc <- cusum(
  failure_probability = 0.05,
  patient_outcomes,
  limit = 2.96
)