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Related Experiment Videos

APACHE II, data accuracy and outcome prediction

D R Goldhill1, A Sumner

  • 1Anaesthetics Unit, St Bartholomew's, London, UK.

Anaesthesia
|January 20, 1999
PubMed
Summary

Strict application of Acute Physiology and Chronic Health Evaluation (APACHE) II criteria revealed data collection inconsistencies. These scoring variations impacted predicted mortality, highlighting the need for accurate data before assessing intensive care unit performance.

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Area of Science:

  • Critical Care Medicine
  • Health Informatics
  • Biostatistics

Background:

  • The Acute Physiology and Chronic Health Evaluation (APACHE) II score is a widely used severity of illness scoring system in intensive care units (ICUs).
  • Accurate scoring is crucial for predicting patient outcomes and evaluating ICU performance.
  • Inconsistencies in data collection can lead to inaccurate APACHE II scores and potentially flawed performance assessments.

Purpose of the Study:

  • To evaluate the impact of strict adherence to APACHE II criteria on scoring accuracy compared to existing database entries.
  • To determine how variations in APACHE II scores affect predicted mortality and mortality ratios.
  • To assess the reliability of data entry methods in an ICU database.

Main Methods:

  • Review of 122 intensive care unit charts to determine APACHE II scores based on eight physiological values.
  • Comparison of strictly interpreted APACHE II scores with originally entered scores in the ICU database.
  • Analysis of the impact of score discrepancies on predicted mortality and mortality ratios.

Main Results:

  • A strict interpretation of APACHE II criteria resulted in an average of 20.6% higher and 6.7% lower scores compared to database entries.
  • The mean increase in APACHE II score was 1.73 points, raising predicted mortality from 24.8% to 27.8%.
  • The mortality ratio decreased from 1.52 to 1.35, with the 95% confidence interval shifting from (1.11-2.03) to (0.99-1.81).

Conclusions:

  • Inconsistencies in applying APACHE II criteria can significantly alter predicted patient mortality.
  • Data collection accuracy is paramount; discrepancies must be resolved before attributing performance variations to ICU quality.
  • Standardized data collection protocols are essential for reliable ICU performance evaluation.

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