cusum: Non-risk-adjusted CUSUM Charts

In cusum: Cumulative Sum (CUSUM) Charts for Monitoring of Hospital Performance

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
)

cusum documentation built on Oct. 2, 2019, 5:03 p.m.