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.
Weill Medical College of Cornell University, New York, New York, USA. aantonacci@gmail.com
Anthony C
AC
Antonacci
Steven
S
Lam
Valentina
V
Lavarias
Peter
P
Homel
Roland A
RA
Eavey
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