Comparison of three different timeframes for pediatric index of mortality data collection in transported intensive care admissions*.

Objective: To identify the most appropriate timeframe for Pediatric Index of Mortality-2 data collection in patients transported to PICUs by specialist teams.

Methods: Retrospective cohort study. Methods: A regional PICU transport team in London, United Kingdom. Methods: Children admitted for intensive care to a tertiary children's hospital PICU following transport by a PICU transport team between January 1, 2007, and December 31, 2008. Methods: None.

Results: Data on case mix and outcome from children transferred to the tertiary PICU during the study period were analyzed. The "standard" timeframe used in calculating Pediatric Index of Mortality-2 was compared with Pediatric Index of Mortality-2 calculated using data from two other 1-hour timeframes (during "retrieval" and during "admission"). A total of 759 transported admissions were studied. Eighty-three children died (mortality rate, 10.9%). Data were missing in up to 42.7% of admissions for some Pediatric Index of Mortality-2 variables from transport. However, missing data persisted even after the first hour of PICU admission in most cases. There was significant improvement in some physiological variables following transport (p < 0.01), but Pediatric Index of Mortality-2 did not change significantly. Pediatric Index of Mortality-2 from all three timeframes exhibited good discrimination (area under the receiver-operating characteristic curve ≥ 0.77). Calibration across deciles of mortality risk was poor for the "admission" Pediatric Index of Mortality-2 (Hosmer-Lemeshow goodness-of-fit test p = 0.04) but good for the other two calculated Pediatric Index of Mortality-2 models (p > 0.20).

Conclusions: The findings of our single-center study do not support the need for different timeframes for Pediatric Index of Mortality-2 data collection in transported and direct PICU admissions. Uniformity in scoring procedure may simplify data collection and improve data quality.