Exploring in-hospital adverse drug events using ICD-10 codes

Parikh, S., Christensen, D., Stuchberry, P., Peterson, J., Hutchinson, A. F. and Jackson, T. J. 2014, Exploring in-hospital adverse drug events using ICD-10 codes, Australian health review, vol. 38, no. 4, pp. 454-460, doi: 10.1071/AH13166.

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Title Exploring in-hospital adverse drug events using ICD-10 codes
Alternative title ADEs in ICD10
Author(s) Parikh, S.
Christensen, D.
Stuchberry, P.
Peterson, J.
Hutchinson, A. F.ORCID iD for Hutchinson, A. F. orcid.org/0000-0002-0014-689X
Jackson, T. J.
Journal name Australian health review
Volume number 38
Issue number 4
Start page 454
End page 460
Total pages 7
Publisher CSIRO Publishing
Place of publication Melbourne, Vic
Publication date 2014-05
ISSN 0156-5788
Keyword(s) adverse drug events
adverse drug reaction reporting systems
drug toxicity classification
drug toxicity diagnosis
international classification of diseases
patient admission
prescriptions
statistics and numerical data
Summary  Abstract
Objective Adverse drug events (ADEs) during hospital admissions are a widespread problem associated with adverse patient outcomes. The ‘external cause’ codes in the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) provide opportunities for identifying the incidence of ADEs acquired during hospital stays that may assist in targeting interventions to decrease their occurrence. The aim of the present study was to use routine administrative data to identify ADEs acquired during hospital admissions in a suburban healthcare network in Melbourne, Australia.

Methods Thirty-nine secondary diagnosis fields of hospital discharge data for a 1-year period were reviewed for ‘diagnoses not present on admission’ and assigned to the Classification of Hospital Acquired Diagnoses (CHADx) subclasses. Discharges with one or more ADE subclass were extracted for retrospective analysis.

Results From 57 205 hospital discharges, 7891 discharges (13.8%) had at least one CHADx, and 402 discharges (0.7%) had an ADE recorded. The highest proportion of ADEs was due to administration of analgesics (27%) and systemic antibiotics (23%). Other major contributors were anticoagulation (13%), anaesthesia (9%) and medications with cardiovascular side-effects (9%).

Conclusion Hospital data coded in ICD-10 can be used to identify ADEs that occur during hospital stays and also clinical conditions, therapeutic drug classes and treating units where these occur. Using the CHADx algorithm on administrative datasets provides a consistent and economical method for such ADE monitoring.

What is known about the topic? Adverse drug events (ADEs) can result in several different physical consequences, ranging from allergic reactions to death, thereby posing a significant burden on patients and the health system. Numerous studies have compared manual, written incident reporting systems used by hospital staff with computerised automated systems to identify ADEs acquired during hospital admissions. Despite various approaches aimed at improving the detection of ADEs, they remain under-reported, as a result of which interventions to mitigate the effect of ADEs cannot be initiated effectively.

What does this paper add? This research article demonstrates major methodological advances over comparable published studies looking at the effectiveness of using routine administrative data to monitor rates of ADEs that occur during a hospital stay and reviews the type of ADEs and their frequency patterns during patient admission. It also provides an insight into the effect of ADEs that occur within different hospital treating units. The method implemented in this study is unique because it uses a grouping algorithm developed for the Australian Commission on Safety and Quality in Health Care (ACSQHC) to identify ADEs not present on admission from patient data coded in ICD-10. This algorithm links the coded external causes of ADEs with their consequences or manifestations. ADEs identified through the use of programmed code based on this algorithm have not been studied in the past and therefore this paper adds to previous knowledge in this subject area.

What are the implications for health professionals? Although not all ADEs can be prevented with current medical knowledge, this study can assist health professionals in targeting interventions that can efficiently reduce the rate of ADEs that occur during a hospital stay, and improve information available for future medication management decisions.
Language eng
DOI 10.1071/AH13166
Field of Research 111599 Pharmacology and Pharmaceutical Sciences not elsewhere classified
Socio Economic Objective 920409 Injury Control
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2014, CSIRO Publishing
Persistent URL http://hdl.handle.net/10536/DRO/DU:30062470

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Created: Fri, 11 Apr 2014, 12:14:47 EST by Ana Hutchinson

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