Method of Measuring Comorbidity and Time-point to Predict Readmission and Mortality of Intensive Care Patients: an Observational Study Using Linked Data From National Registers of Hospital Care and Cause of Death

In this study the investigators will validate the impact of comorbidity on readmission to intensive care unit (ICU) and mortality after ICU and which method of measuring comorbidity and in which time-point it is most predictive.

The study population includes all critical care patients' registries in Swedish intensive care registry (SIR) during the years 2005 to 2012 with valid personal identity number. SIR delivers the population to Statistics Sweden directly or via the client for further delivery to Statistics Sweden. For all individuals in the population, data are collected from registers at Statistics Sweden. Statistics Sweden supplies social security numbers and serial numbers to the National Board of Health for further data collection there. The National Board of Health and Welfare delivers the data sample to the client who sends it to Statistics Sweden for collaboration and anonymous. All data material is stored unidentified in the MONA database where only persons connected to the project have access to the material.

The data set containing 293 342 observations and 223 495 unique individuals. Observations which is totally covered in time by another observation are excluded. Two consecutive observations with less than 24 hours between them consider as the same visit. The final set of dates consists of 273 741 observations (223 495 individuals).

Patients with recurrent ICU stays during the study period were considered as recurrent events that are not independent of each other. The interval between ICU discharge and readmission was used both as an outcome variable and to characterize the patient at the time to admission. In the analyzes the dependency between multiple admissions for the same individual was handled using a robust sandwich estimator. Every ICU stay was included in the study but handled as a time-updated exposure.

A composite outcome of death and readmission will be analyzed. Death and readmission will also be analyzed separately. Follow-up starts at admission. A binary status variable (no/yes) is created reflecting if the outcome has happened or not together with a corresponding time variable. For each admission the follow-up ends with readmission, death or end of study (2016-12-31) whichever comes first.