PROJECT NAME: Role of a web-based Incident Reporting
Tool in identification and analysis of medical errors in the
Emergency Department
Institution: University of Texas – Health Science Center at Houston
Primary Author: Pratik Doshi, MD
Secondary Author: Andrew Potter, MD
Project Category: Patient Safety, Timeliness, and Effectiveness
Overview:
The emergency department (ED) is a recognized, error prone environment where individual and
team performance is challenged by high decision density combined with interruptions producing
significant psychological and physical stress. The quality assurance (QA) process is designed
to identify, analyze, and remedy medical errors. For such a process to work, an environment
conducive to error assessment must exist. This work was undertaken by the department of
Emergency Medicine at the University of Texas- Health Science Center at Houston.
This project was started in 2008 as part of a departmental mission to improve the identification
of medical errors in the ED. The prior process for medical error identification relied primarily on
un-standardized referrals from other service lines and standardized medical record review using
pre-defined record screening parameters: (1) unscheduled return to the ED within 72 hours of
initial visit with admission/hospital observation, (2) death in the ED and (3) death within 72 hours
of admission. The analysis of medical errors identified using this method was limited because
clinician account of the patient encounter were, at best, obtained approximately 30-90 days after
the medical error occurred, and were therefore likely to be significantly impacted by recall bias.
The ED QA committee, which is comprised of ED faculty (including 5 C.S. and E. fellows),
nursing supervisors, midlevel providers, and residents, determined that the most effective
method of increasing medical error identification was to instate an ED-specific medical incident
reporting tool.
Aim Statement (max points 150):
We sought to increase the number of medical errors reported using the ED-specific medical
incident reporting tool by 50% in 12 months.
Measures of Success:
•
•
Frequency of medical error reporting over time
Completeness of reported incident details, as defined by clear summary of the event by
the involved clinician, as well as the suspected contributing factors.
Use of Quality Tools (max points 250):
We used the brainstorming tool to generate reasons for limited medical error identification,
inadequate reporting of the patient encounter details and potential solutions. We used a
desired-result fishbone (Figure 1) to propose a site-specific incident referral system which is
simple to use, voluntary, non-punitive, and confidential that would potentially help increase the
buy-in from the involved clinicians because the reported cases would be independent of any
power to punish and be analyzed by responsive and system/process oriented experts.
Additionally, we created a process map of information that the incident referral system would
be able to provide (Figure 2).The use of the reporting tool was monitored using runcharts
(Figure 3). ED clinicians were encouraged to report incidents using an annual orientation
presentation to the incoming class of residents prior to clinical duties, monthly presentations,
and point of care reinforcement when an incident was identified during a shift with a member QA
committee member. The effectiveness of the tool are presented using a bar chart describing
the increase in frequency of medical error reporting over the subsequent 3 years (Figure 4).
Additionally, the total number of reports by providers is described using frequency
distributions (Figure 5 and 6), and a pareto chart (Figure 7) demonstrates the constitution of
the types of incidents reported. Clustered bar charts (Figure 8) are utilized to demonstrate the
impact of the environment on the types of incident occurrence given the same group of
physicians.
FIGURE 1
FIGURE 2
FIGURE 3
FIGURE 4
FIGURE 5
FIGURE 6
FIGURE 7
FIGURE 8
Interventions (max points 150 includes points for innovation):
To our knowledge, previously developed tools have been largely hospital based rather than
departmental, incidents were reported primarily by nursing staff, and lacked the specificity to
provide adequate details to sufficiently analyze the reported incident incorporating the patient,
clinician and the environment. These hospital based tools are likely to suffer from a lack of
knowledge and therefore trust in how submission will be handled by the hospital administration.
Based on the brainstorming session and the fish bone diagram, an incident referral system that
is user-friendly, voluntary, non-punitive, confidential and timely would be required to achieve our
goal of increasing frequency of medical error reporting with adequate error environment details
surrounding the incident, as described in the process map.
A ED specific, secure, password protected web-based incident reporting tool would address all
the required characteristics of the system (Figure 9). We created a tool that satisfied all of these
requirements between January 2008 and February 2009, and was subsequently implemented in
March 2009.
FIGURE 9
Results (max points 250):
• Frequency of error reporting increased from an average of 8 errors reported per month
in 2009 to 46 errors reported per month in 2012 (Figure 3).
• In addition, this tool has allowed significant improvement in the completeness of
environmental details reported surrounding the errors through categorization into 11
predefined categories, and description of the effect of the environment on the types of
error given the same group of physicians. This has also allowed us to monitor the
characteristics of the reporters and the overall effectiveness of our comprehensive QA
program in its ability to identify medical errors and prevent recurrence of the previously
identified errors (figures 6 and 7).
Revenue Enhancement /Cost Avoidance / Generalizability (max points 200):
Identification of medical errors and the subsequent employment of strategies and process
improvements to reduce this type of error may represent an important source of cost avoidance.
Cost avoidance is difficult to calculate, however Brown, et al. published a review of closed
malpractice claims from the ED between 1985 to 2007, a total of $347,200,036 was paid as a
result of diagnostic errors alone. 2 And between 2006 and 2010, 47% of malpractice cases in the
ED were related to diagnostic errors with the average payment per case being $508,000.3
Based on this error to medico-legal cost relationship, we extrapolate a large potential cost
avoidance. It follows logically that if such a large financial risk exists due to the commission of
diagnostic errors alone, then combining all types of medical errors pose a potential greater
financial risk. Then a reporting tool is critically important in the identification and measurement
phases of the process of reducing those errors.
o
Brown, T., McCarthy, M., Kelen, G. An Epidemiologic Study of Closed Emergency
Department Malpractice Claims in a National Database of Physician Malpractice
Insurers. Academic Emergency Medicine 2010; 17:553–560.
o
Annual Benchmarking Report: Malpractice Risks in Emergency Medicine. Cambridge,
MA: CRICO/RMF Strategies; 2011.
Conclusions and Next Steps:
•
•
•
•
•
Frequency of error reporting can be dramatically improved by utilizing a web-based,
password secured, user friendly, voluntary, confidential and non-punitive error reporting
system.
The reported errors are still likely to be only the “tip of the iceberg”, because of the
existing psychological impediments of voluntary self reporting.
Medical informatics quality tools will help us gain the insights that can be used to make
those constraints more evident to clinicians, which will lead to genuine and lasting
improvements in the safety of clinical practice.
o Wears RL, Nemeth CP. Replacing hindsight with insight: toward better
understanding of diagnostic failures. Ann Emerg Med. 2007;49(2):206-209.
This project is a critical component of transforming the departmental culture to patient
centered, self critiquing, and proactive practice of medicine.
The next steps in this process include tracking the environmental situations that have
contributed to medical errors in our emergency department and create a model for error
prediction based on recurrence of those environmental conditions. Using the predictive
model we can then proactively modify our process and physical plant to maximize
patient safety.