What are incident reports telling us? A comparative study at two Australian hospitals of medication errors identified at audit, detected by staff and reported to an incident system
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Published on: June 11, 2012
Johanna I Westbrook1, Ling Li1, Elin C Lehnbom1
1Centre for Health Systems and Safety Research, Australian Institute of Health Innovation, Faculty of Medicine and Health Sciences, Macquarie University, Sydney 2109, Australia.
Objectives:
To (i) compare medication errors identified at audit and observation with medication incident reports; (ii) identify differences between two hospitals in incident report frequency and medication error rates; (iii) identify prescribing error detection rates by staff.
Design:
Audit of 3291 patient records at two hospitals to identify prescribing errors and evidence of their detection by staff. Medication administration errors were identified from a direct observational study of 180 nurses administering 7451 medications. Severity of errors was classified. Those likely to lead to patient harm were categorized as 'clinically important'.
Setting:
Two major academic teaching hospitals in Sydney, Australia.
Main Outcome Measures:
Rates of medication errors identified from audit and from direct observation were compared with reported medication incident reports.
Results:
A total of 12 567 prescribing errors were identified at audit. Of these 1.2/1000 errors (95% CI: 0.6-1.8) had incident reports. Clinically important prescribing errors (n = 539) were detected by staff at a rate of 218.9/1000 (95% CI: 184.0-253.8), but only 13.0/1000 (95% CI: 3.4-22.5) were reported. 78.1% (n = 421) of clinically important prescribing errors were not detected. A total of 2043 drug administrations (27.4%; 95% CI: 26.4-28.4%) contained ≥ 1 errors; none had an incident report. Hospital A had a higher frequency of incident reports than Hospital B, but a lower rate of errors at audit.
Conclusions:
Prescribing errors with the potential to cause harm frequently go undetected. Reported incidents do not reflect the profile of medication errors which occur in hospitals or the underlying rates. This demonstrates the inaccuracy of using incident frequency to compare patient risk or quality performance within or across hospitals. New approaches including data mining of electronic clinical information systems are required to support more effective medication error detection and mitigation.
Insights
Medication errors, particularly those causing harm, are often missed and underreported in hospitals. Incident reports do not accurately reflect the true rate or type of medication errors, hindering quality improvement efforts.
Area of Science:
- Health Services Research
- Patient Safety
- Medication Management
Background:
- Medication errors represent a significant patient safety concern in healthcare settings.
- Current methods of identifying medication errors, such as incident reporting, may not capture the full scope of the problem.
Purpose of the Study:
- To compare medication errors identified through audit and observation with those reported through incident reports.
- To investigate differences in incident reporting frequency and medication error rates between two hospitals.
- To determine the detection rates of prescribing errors by healthcare staff.
Main Methods:
- A comprehensive audit of 3291 patient records and direct observation of 7451 medication administrations across two academic teaching hospitals in Sydney, Australia.
- Medication errors were identified, classified by severity, and compared with existing incident reports.
- Prescribing error detection rates by staff were analyzed.
Main Results:
- A substantial number of prescribing errors (12,567) were identified, with only a small fraction (1.2/1000) being reported.
- Clinically important prescribing errors were frequently undetected (78.1%), and reported rates were significantly lower than actual rates.
- Medication administration errors were prevalent (27.4%), with no incident reports filed for any observed errors.
Conclusions:
- Reported medication incidents do not accurately represent the true incidence or profile of errors occurring in hospitals.
- Relying on incident frequency for comparing patient risk or quality performance is unreliable.
- Advanced methods, such as data mining of electronic health records, are needed for effective medication error detection and mitigation.
