A report card system using error profile analysis and concurrent morbidity and mortality review: surgical outcome analysis, part II.
BACKGROUND
An effective report card system for adverse outcome error analysis following surgery is lacking. We hypothesized that a memorialized database could be used in conjunction with error analysis and management evaluation at Morbidity & Mortality conference to generate individualized report cards for Attending Surgeon and System performance.


METHODS
Prospectively collected data from September 2000 through April 2005 were reported following Morbidity & Mortality review on 1618 adverse outcomes, including 219 deaths, following 29,237 operative procedures, in a complete loop to approximately 60 individual surgeons and responsible system personnel.


RESULTS
A 40% reduction of gross mortality (P < 0.001) and 43% reduction of age-adjusted mortality were achieved over 4 years at the Academic Center. Quality issues were identified at a rate three times greater than required by New York State regulations and increased from a baseline 4.96% to 32.7% (odds ratio 1.94; P < 0.03) in cases associated with mortality. A detailed review demonstrated a significant increase (P < 0.001) in system errors and physician-related diagnostic and judgment errors associated with mortality highlighted those practices and processes involved, and contrasted the results between academic (43% mortality improvement) and community (no improvement) hospitals.


CONCLUSIONS
The findings suggest that structured concurrent data collection combined with non-punitive error-based case review and individualized report cards can be used to provide detailed feedback on surgical performance to individual surgeons and possibly improve clinical outcomes.
Antonacci
Anthony C
AC
Weill Medical College of Cornell University, New York, New York, USA. aantonacci@gmail.com
Lam
Steven
S
Lavarias
Valentina
V
Homel
Peter
P
Eavey
Roland A
RA
D000046:Academic Medical Centers / Q000592:standards / Q000706:statistics & numerical data; D016208:Databases, Factual; D006801:Humans; D019300:Medical Errors / Q000401:mortality / Q000706:statistics & numerical data*; D009017:Morbidity; D009519:New York City; D017063:Outcome Assessment, Health Care / Q000379:methods*; D010380:Peer Review / Q000379:methods; D011446:Prospective Studies; D011785:Quality Assurance, Health Care / Q000379:methods*; D017751:Safety Management