IDENTIFYING CAUSAL PATTERNS AND ERRORS
IN ADVERSE CLINICAL INCIDENTS
Rebecca Mitchell,Ann Williamson & Brett Molesworth
School of Aviation, University of New South Wales, Australia
This study identified precursor (PE) and associated contributing fac-
tors (CFs) of clinical incidents in health care. A random sample of
498 clinical incidents inAustralia were reviewed. Staff action was the
most common type of PE identified. Correspondence analysis for all
PEs that involved staff action by error type showed that rule-based
errors were strongly related to performing medical or monitoring
tasks and medication issues. Skill-based errors were strongly related
to misdiagnoses. Factors relating to the organisation (66.9%) or the
patient (53.2%) were the most commonly identified CFs for each
incident. This study highlights the need for targeted approaches to
tackling clinical incidents, based on an understanding of why they
occur.
Introduction
There are various approaches that have been adopted to identify the precursor and
contributing factors of adverse clinical incidents involving patients in health care.
While human factors classifications systems that have been developed for health
care are diverse in their structure, what is common across the literature is that human
factors, particularly human error, plays a leading role in clinical incidents. Errors,
defined as ‘the failure of a planned action to proceed as planned’ (US Institute
of Medicine 2000), have been retrospectively analyzed in health care, but studies
differ in the way that medical errors are classified. Many analyses used job-related
descriptions of the nature of errors. For example, in a study of errors in radiology,
the error classification included ‘request for wrong patient’, ‘illegible request’ or
‘duplicate request’(Martin 2005). This type of approach is informative in providing
direction in which task or job areas where errors are most likely to occur, but it
is not descriptive in terms of the type of cognitive failure that explains why the
particular error type occurred. The obvious advantage of cognitive classifications
of error is that they provide insight into the nature of error itself which is helpful
in understanding why it occurred.
Within New South Wales (NSW) Australia, clinical incidents that are categorized
as serious have an Root Cause Analysis (RCA) investigation conducted by health
care teams not involved in the incident. While RCAs can be useful to identify local
issues, aggregated analysis of RCA findings could be useful to implement system-
wide improvements (Wu et al. 2008; Nicolini et al. 2011). The aim of this research
http://dx.doi.org/10.1201/b13826-60
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278 R. Mitchell, A. Williamson & B. Molesworth
is to identify precursor and associated contributing factors to clinical incidents in
a hospital setting using the Human Factors Classification Framework (HFCF) for
patient safety.
Method
All clinical incidents in 2010 and 139 incidents in 2009 in NSW with a RCA
investigation report were randomly reviewed (totaling 498 incidents). The RCA
text-based reports were classified using a systematic coding framework.
Human factors classification framework for patient safety
The HFCF for patient safety was developed to identify information from narrative
reports of clinical incidents (Mitchell et al. 2011). The HFCF for patient safety was
adapted from an existing framework that identified the role of human factors in
work-related fatalities (Williamson and Feyer 1990).
Precursor events (PEs) leading to the clinical incident were defined as discrete
events which played a role in the occurrence of the incident and were linked in time
to the incident. While time separating the events is variable and may range from
seconds to days, PE1 is always closest to the incident and PE2 occurs prior to PE1 in
the temporal sequence. The framework also incorporates any other factors that play
a causal role. These are called contributing factors (CFs) and are defined as factors,
circumstances, actions or conditions that pre-existed before the precursor event
sequence began. CF’s will have played a part in the origin or development of the
incident or to increased risk of the incident occurring (World Health Organization
2009).
Each PE was coded into one of five categories then a number of subcategories. The
five main categories included: (i) Equipment; (ii) Work environment; (iii) Staff
action; (iv) Patient; and (v) Other factors. The framework allows classification of
up to four PEs leading to the clinical incident. Contributing factors were classified
into seven categories and a number of sub-categories. These included the same
five categories as the PEs focusing on pre-existing conditions and two additional
categoriesof: (i) Organizational; and (ii) Individual factors. Further detail regarding
the role of error was also classified for staff action-related classifications in the PEs
or CFs using Rasmussen’s (Rasmussen 1982) skill, rule or knowledge-based error
classifications, or a violation (Reason 1997).
Inter-rater reliability
Inter-rater reliability between four coders using the HFCF for patient safety is high,
with average percent agreement between four coders for PE’s at the first level of
coding 97% and at 73% for error type (Mitchell et al. 2011).

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