Why the study?
Does strict interpretation of APACHE II criteria change predicted mortality and mortality ratios compared to original database entries in intensive care patients?
Does strict interpretation of APACHE II criteria change predicted mortality and mortality ratios compared to original database entries in intensive care patients?
Inaccuracy in APACHE II data collection can significantly alter predicted mortality and mortality ratios, highlighting the need for rigorous data validation in intensive care units.
Strict APACHE II interpretation may bias predicted mortality and ratios in ICU cohorts; leaves open effects on benchmarking and requires validation studies.
From review of 122 intensive care charts, Acute Physiology and Chronic Health Evaluation (APACHE) II points were determined for eight physiological values. Using a strict interpretation of APACHE II criteria, an average of 20.6% of these points were higher and 6.7% lower than the points entered originally into an intensive care database. The resulting 1.73 points mean increase in APACHE II score increased predicted mortality from 24.8% to 27.8% and decreased the mortality ratio (observed hospital deaths devided by predicted deaths) from 1.52 (95% confidence interval: 1.11-2.03) to 1.35 (95% confidence interval: 0.99-1.81). There were few errors entering the data recorded on the audit form into the intensive care unit database with an optical mark reader and keyboard. Inaccuracy and inconsistency in data collection must be excluded before differences in mortality ratios are ascribed to intensive care unit performance.
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Goldhill et al. (1998) studied this question.
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