Detection of Adverse Events With the Austrian Inpatient Quality Indicators

J Patient Saf. 2024 Sep 1;20(6):426-433. doi: 10.1097/PTS.0000000000001235. Epub 2024 May 22.

Abstract

Objectives: Indicators based on routine data are considered a readily available and cost-effective method for assessing health care quality and safety. The Austrian Inpatient Quality Indicators (A-IQI) have been introduced in all Austrian public hospitals as a mandatory quality measurement. The purpose of this study was to assess the value of conspicuous A-IQI in predicting the presence of adverse events (AEs).

Methods: We conducted an exploratory study comparing all indicator-positive patient cases contributing to 18 conspicuous A-IQI indicators to randomly selected indicator-negative control cases regarding the prevalence and severity of AEs. Structured medical record review using the Institute for Healthcare Improvement Global Trigger Tool was used as the gold standard.

Results: In 421 chart reviews, we identified 158 AEs. 70.9% (n = 112) of the AEs were found in cases with a positive indicator. The relative risk of an AE occurring was 3.47 (95% confidence interval: 2.30, 5.24) in indicator-positive cases compared to indicator-negatives. The proportion of severe events (National Coordination Council for Medication Error Reporting and Prevention Index categories H and I) was 54.5% (n = 61) in indicator-positive cases and only 15.3% (n = 7) in indicator-negative cases. Overall sensitivity of the A-IQI was 68.2%, specificity 69.4%, positive predictive value 36.0%, and negative predictive value 89.6%.

Conclusions: Our study shows that significantly more AEs and more severe AEs were found in cases with positive A-IQI than in indicator-negative control cases. However, studies with larger numbers of cases and with larger numbers of conspicuous indicators are needed for the validation of the entire A-IQI indicator set.

MeSH terms

  • Adult
  • Aged
  • Austria
  • Female
  • Hospitals, Public / statistics & numerical data
  • Humans
  • Inpatients / statistics & numerical data
  • Male
  • Medical Errors* / prevention & control
  • Medical Errors* / statistics & numerical data
  • Middle Aged
  • Patient Safety / standards
  • Patient Safety / statistics & numerical data
  • Quality Indicators, Health Care* / statistics & numerical data