Development of an online morbidity, mortality, and near-miss reporting system to identify patterns of adverse events in surgical patients.
OBJECTIVE
To design a Web-based system to track adverse and near-miss events, to establish an automated method to identify patterns of events, and to assess the adverse event reporting behavior of physicians.


METHODS
A Web-based system was designed to collect physician-reported adverse events including weekly Morbidity and Mortality (M&M) entries and anonymous adverse/near-miss events. An automated system was set up to help identify event patterns. Adverse event frequency was compared with hospital databases to assess reporting completeness.


METHODS
A metropolitan tertiary care center.


METHODS
Identification of adverse event patterns and completeness of reporting.


RESULTS
From September 2005 to August 2007, 15,524 surgical patients were reported including 957 (6.2%) adverse events and 34 (0.2%) anonymous reports. The automated pattern recognition system helped identify 4 event patterns from M&M reports and 3 patterns from anonymous/near-miss reporting. After multidisciplinary meetings and expert reviews, the patterns were addressed with educational initiatives, correction of systems issues, and/or intensive quality monitoring. Only 25% of complications and 42% of inpatient deaths were reported. A total of 75.2% of adverse events resulting in permanent disability or death were attributed to the nature of the disease. Interventions to improve reporting were largely unsuccessful.


CONCLUSIONS
We have developed a user-friendly Web-based system to track complications and identify patterns of adverse events. Underreporting of adverse events and attributing the complication to the nature of the disease represent a problem in reporting culture among surgeons at our institution. Similar systems should be used by surgery departments, particularly those affiliated with teaching hospitals, to identify quality improvement opportunities.
Bilimoria
Karl Y
KY
Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA. k-bilimoria@northwestern.edu
Kmiecik
Thomas E
TE
DaRosa
Debra A
DA
Halverson
Amy
A
Eskandari
Mark K
MK
Bell
Richard H
RH
Soper
Nathaniel J
NJ
Wayne
Jeffrey D
JD
D016208:Databases, Factual; D006748:Hospital Departments / Q000458:organization & administration; D006801:Humans; D020407:Internet; D019300:Medical Errors; D010363:Pattern Recognition, Automated; D011183:Postoperative Complications; D013514:Surgical Procedures, Operative / Q000009:adverse effects*