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Introduction: Although mortality rates from pancreatectomy have decreased worldwide, death remains an infrequent but profound event at an individual practice level. Root-cause analysis is a retrospective method commonly employed to understand adverse events. We evaluate whether emerging mortality-risk tools sufficiently predict and account for actual clinical events that are often identified by root-cause analysis.Methods: We assembled a Pancreatic Mortality Study Group comprised of 32 pancreatic surgeons from 14 institutions in 4 countries. Mortalities after pancreatectomy (30 and 90-day) were accrued from 2000-2010. For root-cause analysis, each surgeon “deconstructed” the clinical events preceding a death to determine cause. We next tested whether mortality-risk tools (ASA, POSSUM, Charlson, NSQIP) could predict those patients who would die (n=184), and compared their prognostic accuracy against a cohort of resections in which no patient died (n=630). Results: 184 deaths (151 Whipples, 18 Distals, 15 Totals) were identified from 10,783 pancreatectomies performed by surgeons whose experience averaged 13.5 years. Overall 30- and 90-day mortalities were 0.92% and 1.71%. Individual institutional rates ranged from 0.3 - 4.7%. Only 5 patients died intraoperatively, while the other 179 succumbed at a median of 27 days. Mean patient age was 70 years old (39% were >75y). 89% of cases were for malignancy, mostly pancreatic cancer(54%). Median operative time was 370 min and EBL was 750cc (100-16,000cc). Vascular repair or multivisceral resections were required for 14% and 16% respectively. 82% had a variety of major complications before death. 84% required ICU care, 51% were transfused, and 36% were reoperated upon. 52% died during the index admission while another 9% died after a readmission. Almost half (n=85) expired between 31 and 90 days. Only 12% had autopsies. Operation-related complications contributed to 42% of deaths, with pancreatic fistula being the most evident (16%). Technical errors (23%) and poor patient selection (16%) were cited by surgeons. 5.4% of deaths had associated cancer progression - all occurring between 31-90d. Even after root-cause scrutiny, the ultimate cause of death could not be determined for 41 patients - most often between 31-90d. While assorted risk models predicted mortality with variable discrimination from non-mortalities, they consistently underestimated the actual mortality events we report (Table). Analysis with POSSUM illustrates the impact of operative performance on determining outcome.Conclusion: Root-cause analysis suggests that risk-prediction should include, if not emphasize, operative factors related to pancreatectomy. While risk models can distinguish between mortalities and non-mortalities in a collective fashion, they vastly miscalculate the actual chance of death on an individual basis.
Mortality Risk Prediction Comparison

Risk Prediction Tool (All mean values)	Mortality N=184	No Mortality N=630
ASA Score	2.48	2.47
POSSUM
Physiologic score Operative score Predicted Mortality	19.97 18.6 22.4%	19.14 15.69 13.2%
NSQIP (Whipple Resections only)
Predicted Mortality	8.18%	2.92%
Charlson
Predicted Mortality Institutional Adjusted Predicted Mortality	5.17% 1.47%	2.94% 0.86%