Case Mix Programme Database
The Case Mix Programme (CMP) is a national comparative audit of adult, general ICUs
(including intensive care units and combined intensive care and high dependency units,
but not coronary care units) in England, Wales and Northern Ireland co-ordinated by
ICNARC. The CMP has received approval from the Patient Information Advisory Group
to hold patient identifiable information without consent (approval number PIAG 2-10(f)/2005).
Approval by a research ethics committee was not required. Details of the data collection
and validation have been reported previously 12].
We undertook a prospectively defined, retrospective analysis of the ICNARC CMPD for
the period 1 January 2004 to 31 December 2014. Admissions, mechanically ventilated
in the first 24 hours in the critical care unit and admitted following CPR, defined
as the delivery of chest compressions in the 24 hours before admission, were identified.
Patients sustaining a cardiac arrest in ICU (but not before admission) were excluded
from the analysis.
The admissions that were identified were then grouped in the following way:
Out-of-hospital cardiac arrest: location immediately prior to source of admission to the unit as ‘clinic or home’
and source of admission to the unit is ‘AE, same hospital’.
In-hospital cardiac arrest: location immediately prior to source of admission to the unit is not ‘clinic or home’
and source of admission to the unit is not ‘AE, same hospital’.
Case mix
Age, gender, year of admission and past medical history were extracted. Severity of
illness was measured by the ICNARC model 13]. The ICNARC model encompasses a weighting for acute physiology (the ICNARC physiology
score, defined by derangement from the normal range for twelve physiological variables
in the first 24 hours following admission to ICU) and additionally a weighting for
age, diagnostic category coefficients and interactions with the physiology score,
cardiopulmonary resuscitation within 24 hours prior to admission, and source of admission.
Treatment
Data were extracted on the proportion of people that had the following:
lowest temperature of???34 °C in the first 24 h (as a surrogate marker for treatment
with therapeutic hypothermia);
treatment withdrawn;
timing of treatment withdrawn.
Outcome
Survival data were extracted at discharge from the CMP unit and at ultimate discharge
from an acute hospital. The proportion of survivors discharged to home was documented.
In those who died, the proportion who became solid organ donors was collected.
Activity
Length of stay in the CMP unit was calculated in fractions of days from the dates
and times of admission and discharge. Length of stay in hospital was calculated in
days from the dates of original admission and ultimate discharge. Readmissions to
the unit within the same hospital stay were identified from the postcode, date of
birth and sex, and confirmed by the participating units.
Statistical analyses
A statistical analysis plan was agreed a priori. The analyses performed were as follows.
Descriptive statistics
Case mix, withdrawal, outcome and activity were described annually for all admissions
identified as post-cardiac arrest admissions, and separately for out-of-hospital cardiac
arrest and in-hospital cardiac arrest. Readmissions were included in the descriptive
statistics but were removed from the outcomes. To evaluate changes in study variables
by calendar year we used logistic regression for categorical variables and linear
regression for continuous, using the year of admission as the predictor variable.
For non-normally distributed data, we used the Jonckheere-Terpstra trend test.
Multivariable analyses
A multivariable logistic regression was performed to analyse the impact on outcome
of year of admission. To assess whether in-hospital mortality had improved over time,
hierarchical multivariate logistic regression models were then constructed, with in-hospital
mortality as the dependent variable, year of admission as the main exposure variable
(modelled as continuous variable ranging from year 2004 to 2014), and ICU as a random
effect. Models were adjusted for illness severity and potential confounding variables,
including age, reason for admission and source for admission. This model estimated
the adjusted probability of in-hospital mortality per incremental year over the study
period. Separated models were developed for out-of-hospital CPR admissions and in-hospital
CPR admissions.
All analyses were repeated using only the data from those ICUs contributing data throughout
the study period.
All analyses were performed using Stata 13.0 (Stata Corporation, College Station,
TX, USA).