surgerydat {success}

Simulated data set with data of surgery procedures performed at multiple hospitals.

Description

Data about patients and their surgery procedure from 45 simulated hospitals with patient arrivals in the first 400 days after the start of the study.
Patient survival times were determined using a risk-adjusted Cox proportional hazards model with coefficients age = 0.003, BMI = 0.02 and sexmale = 0.2 and exponential baseline hazard rate h_0(t, \lambda = 0.01) e^\mu. The increase in hazard rate is sampled from a normal distribution for all hospitals:

• \theta \sim N(log(1), sd = 0.4)

This means that the average failure rate of hospitals in the data set should be baseline (\theta = 0), with some hospitals experiencing higher and lower failure rates. True failure rate can be found in the column exptheta.
The arrival rate \psi of patients at a hospital differs. The arrival rates are:

• Hospitals 1-5 & 16-20: 0.5 patients per day (small hospitals)

• Hospitals 6-10 & 21-25: 1 patient per day (medium sized hospitals)

• Hospitals 11-15 & 26-30: 1.5 patients per day (large hospitals)

These are then respectively small, medium and large hospitals.

Usage

surgerydat

Format

A data.frame with 12010 rows and 9 variables:

entrytime

Time of entry of patient into study (numeric)

survtime

Time from entry until failure of patient (numeric)

censorid

Censoring indicator (0 - right censored, 1 - observed) (integer)

unit

Hospital number at which patient received treatment (integer)

exptheta

True excess hazard used for generating patient survival (numeric)

psival

Poisson arrival rate at hospital which the patient was at (numeric)

age

Age of the patient (numeric)

sex

Sex of the patient (factor)

BMI

Body mass index of the patient (numeric)