funnel_plot: Risk-adjusted funnel plot

In d-gomon/cgrcusum: Quality control charts for survival outcomes

Risk-adjusted funnel plot

Description

This function allows to construct a risk-adjusted funnel plot for comparing survival proportion between instances.

Usage

funnel_plot(data, ctime, p0, glmmod, followup, conflev = c(0.95, 0.99))

Arguments

data	A data.frame with rows representing subjects and the following named columns: entrytime: time of entry into study (numeric); survtime: time from entry until event (numeric); censorid: censoring indicator (0 = right censored, 1 = observed), (integer); instance: integer or character indicating which instance (f.e. hospital) the observation belongs to. and optionally additional covariates used for risk-adjustment.
ctime	Construction time at which the funnel plot should be determined. Maximum possible time used when not specified.
p0	The baseline failure probability at entrytime + followup for individuals. If not specified, average failure proportion over whole data is used instead.
glmmod	A generalized linear regression model as produced by the function glm(). Recommended: glm(as.formula("(survtime <= followup) & (censorid == 1) ~ covariates"), data = data). Alternatively, a list with the following elements: formula: a formula() in the form ~ covariates; coefficients: a named vector specifying risk adjustment coefficients for covariates. Names must be the same as in formula and colnames of data.
followup	The followup time for every individual. At what time after subject entry do we consider the outcome?
conflev	A vector of confidence levels of interest. Default is c(0.95, 0.99).

Value

An object of class "funnelplot" containing:

• data: A data.frame containing:

  instance:

  instance number/name;

  observed:

  observed number of failures at instance;

  expected:

  expected (risk-adjusted) number of failures at instance;

  numtotal

  total number of individuals considered at this instance;

  p:

  (risk-adjusted) proportion of failure at instance;

  conflevels:

  worse/normal/better performance than expected at specified confidence levels.

• call: the call used to obtain output

• plotdata: data used for plotting confidence intervals

• conflev: specified confidence level(s)

• p0: (Estimated) baseline failure probability

Author(s)

Daniel Gomon

See Also

plot.funnelplot, summary.funnelplot

Other quality control charts: bernoulli_cusum(), bk_cusum(), cgr_cusum()

Examples

#Determine a risk-adjustment model using a generalized linear model.
#Outcome (survival in first 100 days) is regressed on the available covariates:
exprfitfunnel <- as.formula("(survtime <= 100) & (censorid == 1)~ age + sex + BMI")
surgerydat$instance <- surgerydat$hosp_num
glmmodfun <- glm(exprfitfunnel, data = surgerydat, family = binomial(link = "logit"))
#Determine the necessary values to produce a funnel plot
funnel <- funnel_plot(data = surgerydat, ctime = 3*365, glmmod = glmmodfun, followup = 100)
#Produce a funnel plot!
plot(funnel)

d-gomon/cgrcusum documentation built on May 3, 2022, 9:40 p.m.