sepsis: Artificial data.frame of 7 characteristics of patients...

In ICEinfer: Incremental Cost-Effectiveness Inference using Two Unbiased Samples

Description

These simulated data describe the characteristics of 94 pseudo-patients treated for sepsis by two alternative Intensive Care Units.

Usage

data(sepsis)

Format

A data frame of 7 characteristics of 94 sepsis patients; no NAs.

patid

Unique patient I.D. number; 1 through 94.

icu

Intensive Care Unit type: 1 is type "new", and 0 is type "std".

qalypres

Quality Adjusted Life Years preserved by treatment for sepsis.

totcost

Total Cost of Resources Utilized in treatment for sepsis.

age

Patient Age in years (integer).

apache

Apache II score (integer).

orgfails

Number of Organ Failures experienced (integer).

Details

Since only 47 patients from each of 2 Intensive Care Units are provided, this example illustrates how the Law of Large Numbers can fail to apply to ICE inferences. Unlike the 3 other "ICEinfer" example data.frames provided, the "sepsis" data.frame contains 3 additional patient charcteristics (confounders) for potential use in covariate-adjustment via linear models.

References

Obenchain RL, Sacristan JA. In reply to: The negative side of cost-effectiveness ratios. JAMA 1997; 277: 1931–1933.

Hoch JS, Briggs AH, Willan AR. Something old, something new, something borrowed, something blue: a framework for the marriage of health econometrics and cost effectiveness analysis. Health Economics 2002; 11: 415-430.

Examples

    data(sepsis)
    ICEscale(sepsis, icu, qalypres, totcost, lambda = 50000)
    ## Not run:  demo(sepsis) 

ICEinfer documentation built on Oct. 23, 2020, 8:31 p.m.