An adverse event screening tool based on routinely collected hospital-acquired diagnoses

Brand, Caroline, Tropea, Joanne, Gorelik, Alexandra, Jolley, Damien, Scott, Ian and Sundararajan, Vijaya (2012) An adverse event screening tool based on routinely collected hospital-acquired diagnoses. International Journal for Quality in Health Care, 24 3: 266-278.


Author Brand, Caroline
Tropea, Joanne
Gorelik, Alexandra
Jolley, Damien
Scott, Ian
Sundararajan, Vijaya
Title An adverse event screening tool based on routinely collected hospital-acquired diagnoses
Journal name International Journal for Quality in Health Care  (ERA 2012 Listed)    (ERA 2010 Rank A)   Check publisher's open access policy
Publication date 2012-06
Sub-type Article
DOI 10.1093/intqhc/mzs007
Volume number 24
Issue number 3
ISSN 1353-4505; 1464-3677
Start page 266
End page 278
Total pages 13
Place of publication Cary, NC, United States
Publisher Oxford University Press
Collection year 2013
Language eng
Formatted abstract Objective. The aim was to develop an electronic adverse event (AE) screening tool applicable to acute care hospital episodes
for patients admitted with chronic heart failure (CHF) and pneumonia.

Design. Consensus building using a modified Delphi method and descriptive analysis of hospital discharge data.

Participants. Consultant physicians in general medicine (n ¼ 38).

Intervention. In-hospital acquired (C-prefix) diagnoses associated with CHF and pneumonia admissions to 230 hospitals in
Victoria, Australia, were extracted from the Victorian Admitted Episodes Data Set between July 2004 and June 2007. A 9-
point rating scale was used to prioritize diagnoses acquired during hospitalization (routinely coded as a ‘C-prefix’ diagnosis to
distinguish from diagnoses present on admission) for inclusion within an AE screening tool. Diagnoses rated a group median
score between 7 and 9 by the physician panel were included.

Main Outcome Measures. Selection of C-prefix diagnoses with a group median rating of 7–9 in a screening tool, and the
level of physician agreement, as assessed using the Interpercentile Range Adjusted for Symmetry.

Results. Of 697 initial C-prefix diagnoses, there were high levels of agreement to include 113 (16.2%) in the AE screening
tool. Using these selected diagnoses, a potential AE was flagged in 14% of all admissions for the two index conditions. Intrarater
reliability for each clinician ranged from kappa 0.482 to 1.0.

Conclusions. A high level of physician agreement was obtained in selecting in-hospital diagnoses for inclusion in an AE
screening tool based on routinely collected data. These results support further tool validation
Keyword Adverse events
Patient safety
Quality improvement
Quality management
Risk management
Patient safety
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article
Collections: Official 2013 Collection
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